1570 lines
81 KiB
Plaintext
1570 lines
81 KiB
Plaintext
-----------------------
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HAProxy Starter Guide
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-----------------------
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version 2.2
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This document is an introduction to HAProxy for all those who don't know it, as
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well as for those who want to re-discover it when they know older versions. Its
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primary focus is to provide users with all the elements to decide if HAProxy is
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the product they're looking for or not. Advanced users may find here some parts
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of solutions to some ideas they had just because they were not aware of a given
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new feature. Some sizing information is also provided, the product's lifecycle
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is explained, and comparisons with partially overlapping products are provided.
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This document doesn't provide any configuration help or hints, but it explains
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where to find the relevant documents. The summary below is meant to help you
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search sections by name and navigate through the document.
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Note to documentation contributors :
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This document is formatted with 80 columns per line, with even number of
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spaces for indentation and without tabs. Please follow these rules strictly
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so that it remains easily printable everywhere. If you add sections, please
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update the summary below for easier searching.
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Summary
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-------
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1. Available documentation
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2. Quick introduction to load balancing and load balancers
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3. Introduction to HAProxy
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3.1. What HAProxy is and is not
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3.2. How HAProxy works
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3.3. Basic features
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3.3.1. Proxying
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3.3.2. SSL
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3.3.3. Monitoring
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3.3.4. High availability
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3.3.5. Load balancing
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3.3.6. Stickiness
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3.3.7. Sampling and converting information
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3.3.8. Maps
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3.3.9. ACLs and conditions
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3.3.10. Content switching
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3.3.11. Stick-tables
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3.3.12. Formatted strings
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3.3.13. HTTP rewriting and redirection
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3.3.14. Server protection
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3.3.15. Logging
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3.3.16. Statistics
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3.4. Advanced features
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3.4.1. Management
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3.4.2. System-specific capabilities
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3.4.3. Scripting
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3.5. Sizing
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3.6. How to get HAProxy
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4. Companion products and alternatives
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4.1. Apache HTTP server
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4.2. NGINX
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4.3. Varnish
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4.4. Alternatives
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1. Available documentation
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--------------------------
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The complete HAProxy documentation is contained in the following documents.
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Please ensure to consult the relevant documentation to save time and to get the
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most accurate response to your needs. Also please refrain from sending questions
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to the mailing list whose responses are present in these documents.
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- intro.txt (this document) : it presents the basics of load balancing,
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HAProxy as a product, what it does, what it doesn't do, some known traps to
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avoid, some OS-specific limitations, how to get it, how it evolves, how to
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ensure you're running with all known fixes, how to update it, complements
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and alternatives.
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- management.txt : it explains how to start haproxy, how to manage it at
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runtime, how to manage it on multiple nodes, and how to proceed with
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seamless upgrades.
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- configuration.txt : the reference manual details all configuration keywords
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and their options. It is used when a configuration change is needed.
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- coding-style.txt : this is for developers who want to propose some code to
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the project. It explains the style to adopt for the code. It is not very
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strict and not all the code base completely respects it, but contributions
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which diverge too much from it will be rejected.
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- proxy-protocol.txt : this is the de-facto specification of the PROXY
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protocol which is implemented by HAProxy and a number of third party
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products.
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- README : how to build HAProxy from sources
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2. Quick introduction to load balancing and load balancers
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----------------------------------------------------------
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Load balancing consists in aggregating multiple components in order to achieve
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a total processing capacity above each component's individual capacity, without
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any intervention from the end user and in a scalable way. This results in more
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operations being performed simultaneously by the time it takes a component to
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perform only one. A single operation however will still be performed on a single
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component at a time and will not get faster than without load balancing. It
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always requires at least as many operations as available components and an
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efficient load balancing mechanism to make use of all components and to fully
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benefit from the load balancing. A good example of this is the number of lanes
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on a highway which allows as many cars to pass during the same time frame
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without increasing their individual speed.
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Examples of load balancing :
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- Process scheduling in multi-processor systems
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- Link load balancing (e.g. EtherChannel, Bonding)
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- IP address load balancing (e.g. ECMP, DNS round-robin)
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- Server load balancing (via load balancers)
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The mechanism or component which performs the load balancing operation is
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called a load balancer. In web environments these components are called a
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"network load balancer", and more commonly a "load balancer" given that this
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activity is by far the best known case of load balancing.
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A load balancer may act :
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- at the link level : this is called link load balancing, and it consists in
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choosing what network link to send a packet to;
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- at the network level : this is called network load balancing, and it
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consists in choosing what route a series of packets will follow;
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- at the server level : this is called server load balancing and it consists
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in deciding what server will process a connection or request.
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Two distinct technologies exist and address different needs, though with some
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overlapping. In each case it is important to keep in mind that load balancing
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consists in diverting the traffic from its natural flow and that doing so always
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requires a minimum of care to maintain the required level of consistency between
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all routing decisions.
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The first one acts at the packet level and processes packets more or less
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individually. There is a 1-to-1 relation between input and output packets, so
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it is possible to follow the traffic on both sides of the load balancer using a
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regular network sniffer. This technology can be very cheap and extremely fast.
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It is usually implemented in hardware (ASICs) allowing to reach line rate, such
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as switches doing ECMP. Usually stateless, it can also be stateful (consider
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the session a packet belongs to and called layer4-LB or L4), may support DSR
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(direct server return, without passing through the LB again) if the packets
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were not modified, but provides almost no content awareness. This technology is
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very well suited to network-level load balancing, though it is sometimes used
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for very basic server load balancing at high speed.
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The second one acts on session contents. It requires that the input streams is
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reassembled and processed as a whole. The contents may be modified, and the
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output stream is segmented into new packets. For this reason it is generally
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performed by proxies and they're often called layer 7 load balancers or L7.
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This implies that there are two distinct connections on each side, and that
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there is no relation between input and output packets sizes nor counts. Clients
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and servers are not required to use the same protocol (for example IPv4 vs
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IPv6, clear vs SSL). The operations are always stateful, and the return traffic
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must pass through the load balancer. The extra processing comes with a cost so
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it's not always possible to achieve line rate, especially with small packets.
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On the other hand, it offers wide possibilities and is generally achieved by
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pure software, even if embedded into hardware appliances. This technology is
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very well suited for server load balancing.
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Packet-based load balancers are generally deployed in cut-through mode, so they
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are installed on the normal path of the traffic and divert it according to the
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configuration. The return traffic doesn't necessarily pass through the load
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balancer. Some modifications may be applied to the network destination address
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in order to direct the traffic to the proper destination. In this case, it is
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mandatory that the return traffic passes through the load balancer. If the
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routes doesn't make this possible, the load balancer may also replace the
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packets' source address with its own in order to force the return traffic to
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pass through it.
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Proxy-based load balancers are deployed as a server with their own IP addresses
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and ports, without architecture changes. Sometimes this requires to perform some
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adaptations to the applications so that clients are properly directed to the
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load balancer's IP address and not directly to the server's. Some load balancers
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may have to adjust some servers' responses to make this possible (e.g. the HTTP
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Location header field used in HTTP redirects). Some proxy-based load balancers
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may intercept traffic for an address they don't own, and spoof the client's
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address when connecting to the server. This allows them to be deployed as if
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they were a regular router or firewall, in a cut-through mode very similar to
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the packet based load balancers. This is particularly appreciated for products
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which combine both packet mode and proxy mode. In this case DSR is obviously
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still not possible and the return traffic still has to be routed back to the
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load balancer.
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A very scalable layered approach would consist in having a front router which
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receives traffic from multiple load balanced links, and uses ECMP to distribute
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this traffic to a first layer of multiple stateful packet-based load balancers
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(L4). These L4 load balancers in turn pass the traffic to an even larger number
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of proxy-based load balancers (L7), which have to parse the contents to decide
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what server will ultimately receive the traffic.
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The number of components and possible paths for the traffic increases the risk
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of failure; in very large environments, it is even normal to permanently have
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a few faulty components being fixed or replaced. Load balancing done without
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awareness of the whole stack's health significantly degrades availability. For
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this reason, any sane load balancer will verify that the components it intends
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to deliver the traffic to are still alive and reachable, and it will stop
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delivering traffic to faulty ones. This can be achieved using various methods.
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The most common one consists in periodically sending probes to ensure the
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component is still operational. These probes are called "health checks". They
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must be representative of the type of failure to address. For example a ping-
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based check will not detect that a web server has crashed and doesn't listen to
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a port anymore, while a connection to the port will verify this, and a more
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advanced request may even validate that the server still works and that the
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database it relies on is still accessible. Health checks often involve a few
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retries to cover for occasional measuring errors. The period between checks
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must be small enough to ensure the faulty component is not used for too long
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after an error occurs.
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Other methods consist in sampling the production traffic sent to a destination
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to observe if it is processed correctly or not, and to evict the components
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which return inappropriate responses. However this requires to sacrifice a part
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of the production traffic and this is not always acceptable. A combination of
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these two mechanisms provides the best of both worlds, with both of them being
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used to detect a fault, and only health checks to detect the end of the fault.
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A last method involves centralized reporting : a central monitoring agent
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periodically updates all load balancers about all components' state. This gives
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a global view of the infrastructure to all components, though sometimes with
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less accuracy or responsiveness. It's best suited for environments with many
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load balancers and many servers.
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Layer 7 load balancers also face another challenge known as stickiness or
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persistence. The principle is that they generally have to direct multiple
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subsequent requests or connections from a same origin (such as an end user) to
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the same target. The best known example is the shopping cart on an online
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store. If each click leads to a new connection, the user must always be sent
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to the server which holds his shopping cart. Content-awareness makes it easier
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to spot some elements in the request to identify the server to deliver it to,
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but that's not always enough. For example if the source address is used as a
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key to pick a server, it can be decided that a hash-based algorithm will be
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used and that a given IP address will always be sent to the same server based
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on a divide of the address by the number of available servers. But if one
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server fails, the result changes and all users are suddenly sent to a different
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server and lose their shopping cart. The solution against this issue consists
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in memorizing the chosen target so that each time the same visitor is seen,
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he's directed to the same server regardless of the number of available servers.
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The information may be stored in the load balancer's memory, in which case it
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may have to be replicated to other load balancers if it's not alone, or it may
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be stored in the client's memory using various methods provided that the client
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is able to present this information back with every request (cookie insertion,
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redirection to a sub-domain, etc). This mechanism provides the extra benefit of
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not having to rely on unstable or unevenly distributed information (such as the
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source IP address). This is in fact the strongest reason to adopt a layer 7
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load balancer instead of a layer 4 one.
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In order to extract information such as a cookie, a host header field, a URL
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or whatever, a load balancer may need to decrypt SSL/TLS traffic and even
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possibly to re-encrypt it when passing it to the server. This expensive task
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explains why in some high-traffic infrastructures, sometimes there may be a
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lot of load balancers.
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Since a layer 7 load balancer may perform a number of complex operations on the
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traffic (decrypt, parse, modify, match cookies, decide what server to send to,
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etc), it can definitely cause some trouble and will very commonly be accused of
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being responsible for a lot of trouble that it only revealed. Often it will be
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discovered that servers are unstable and periodically go up and down, or for
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web servers, that they deliver pages with some hard-coded links forcing the
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clients to connect directly to one specific server without passing via the load
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balancer, or that they take ages to respond under high load causing timeouts.
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That's why logging is an extremely important aspect of layer 7 load balancing.
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Once a trouble is reported, it is important to figure if the load balancer took
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a wrong decision and if so why so that it doesn't happen anymore.
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3. Introduction to HAProxy
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--------------------------
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HAProxy is written as "HAProxy" to designate the product, and as "haproxy" to
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designate the executable program, software package or a process. However, both
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are commonly used for both purposes, and are pronounced H-A-Proxy. Very early,
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"haproxy" used to stand for "high availability proxy" and the name was written
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in two separate words, though by now it means nothing else than "HAProxy".
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3.1. What HAProxy is and isn't
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------------------------------
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HAProxy is :
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- a TCP proxy : it can accept a TCP connection from a listening socket,
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connect to a server and attach these sockets together allowing traffic to
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flow in both directions;
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- an HTTP reverse-proxy (called a "gateway" in HTTP terminology) : it presents
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itself as a server, receives HTTP requests over connections accepted on a
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listening TCP socket, and passes the requests from these connections to
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servers using different connections.
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- an SSL terminator / initiator / offloader : SSL/TLS may be used on the
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connection coming from the client, on the connection going to the server,
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or even on both connections.
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- a TCP normalizer : since connections are locally terminated by the operating
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system, there is no relation between both sides, so abnormal traffic such as
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invalid packets, flag combinations, window advertisements, sequence numbers,
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incomplete connections (SYN floods), or so will not be passed to the other
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side. This protects fragile TCP stacks from protocol attacks, and also
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allows to optimize the connection parameters with the client without having
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to modify the servers' TCP stack settings.
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- an HTTP normalizer : when configured to process HTTP traffic, only valid
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complete requests are passed. This protects against a lot of protocol-based
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attacks. Additionally, protocol deviations for which there is a tolerance
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in the specification are fixed so that they don't cause problem on the
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servers (e.g. multiple-line headers).
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- an HTTP fixing tool : it can modify / fix / add / remove / rewrite the URL
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or any request or response header. This helps fixing interoperability issues
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in complex environments.
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- a content-based switch : it can consider any element from the request to
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decide what server to pass the request or connection to. Thus it is possible
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to handle multiple protocols over a same port (e.g. HTTP, HTTPS, SSH).
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- a server load balancer : it can load balance TCP connections and HTTP
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requests. In TCP mode, load balancing decisions are taken for the whole
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connection. In HTTP mode, decisions are taken per request.
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- a traffic regulator : it can apply some rate limiting at various points,
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protect the servers against overloading, adjust traffic priorities based on
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the contents, and even pass such information to lower layers and outer
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network components by marking packets.
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- a protection against DDoS and service abuse : it can maintain a wide number
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of statistics per IP address, URL, cookie, etc and detect when an abuse is
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happening, then take action (slow down the offenders, block them, send them
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to outdated contents, etc).
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- an observation point for network troubleshooting : due to the precision of
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the information reported in logs, it is often used to narrow down some
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network-related issues.
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- an HTTP compression offloader : it can compress responses which were not
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compressed by the server, thus reducing the page load time for clients with
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poor connectivity or using high-latency, mobile networks.
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HAProxy is not :
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- an explicit HTTP proxy, i.e. the proxy that browsers use to reach the
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internet. There are excellent open-source software dedicated for this task,
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such as Squid. However HAProxy can be installed in front of such a proxy to
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provide load balancing and high availability.
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- a caching proxy : it will return the contents received from the server as-is
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and will not interfere with any caching policy. There are excellent
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open-source software for this task such as Varnish. HAProxy can be installed
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in front of such a cache to provide SSL offloading, and scalability through
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smart load balancing.
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- a data scrubber : it will not modify the body of requests nor responses.
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- a web server : during startup, it isolates itself inside a chroot jail and
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drops its privileges, so that it will not perform any single file-system
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access once started. As such it cannot be turned into a web server. There
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are excellent open-source software for this such as Apache or Nginx, and
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HAProxy can be installed in front of them to provide load balancing and
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high availability.
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- a packet-based load balancer : it will not see IP packets nor UDP datagrams,
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will not perform NAT or even less DSR. These are tasks for lower layers.
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Some kernel-based components such as IPVS (Linux Virtual Server) already do
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this pretty well and complement perfectly with HAProxy.
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3.2. How HAProxy works
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----------------------
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HAProxy is a single-threaded, event-driven, non-blocking engine combining a very
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fast I/O layer with a priority-based scheduler. As it is designed with a data
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forwarding goal in mind, its architecture is optimized to move data as fast as
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possible with the least possible operations. As such it implements a layered
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model offering bypass mechanisms at each level ensuring data doesn't reach
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higher levels unless needed. Most of the processing is performed in the kernel,
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and HAProxy does its best to help the kernel do the work as fast as possible by
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giving some hints or by avoiding certain operation when it guesses they could
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be grouped later. As a result, typical figures show 15% of the processing time
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spent in HAProxy versus 85% in the kernel in TCP or HTTP close mode, and about
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30% for HAProxy versus 70% for the kernel in HTTP keep-alive mode.
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A single process can run many proxy instances; configurations as large as
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300000 distinct proxies in a single process were reported to run fine. Thus
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there is usually no need to start more than one process for all instances.
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It is possible to make HAProxy run over multiple processes, but it comes with
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a few limitations. In general it doesn't make sense in HTTP close or TCP modes
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because the kernel-side doesn't scale very well with some operations such as
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connect(). It scales pretty well for HTTP keep-alive mode but the performance
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that can be achieved out of a single process generally outperforms common needs
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by an order of magnitude. It does however make sense when used as an SSL
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offloader, and this feature is well supported in multi-process mode.
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HAProxy only requires the haproxy executable and a configuration file to run.
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For logging it is highly recommended to have a properly configured syslog daemon
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and log rotations in place. The configuration files are parsed before starting,
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then HAProxy tries to bind all listening sockets, and refuses to start if
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anything fails. Past this point it cannot fail anymore. This means that there
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are no runtime failures and that if it accepts to start, it will work until it
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is stopped.
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Once HAProxy is started, it does exactly 3 things :
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- process incoming connections;
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- periodically check the servers' status (known as health checks);
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- exchange information with other haproxy nodes.
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Processing incoming connections is by far the most complex task as it depends
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on a lot of configuration possibilities, but it can be summarized as the 9 steps
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below :
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- accept incoming connections from listening sockets that belong to a
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configuration entity known as a "frontend", which references one or multiple
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listening addresses;
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- apply the frontend-specific processing rules to these connections that may
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result in blocking them, modifying some headers, or intercepting them to
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execute some internal applets such as the statistics page or the CLI;
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- pass these incoming connections to another configuration entity representing
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a server farm known as a "backend", which contains the list of servers and
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the load balancing strategy for this server farm;
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- apply the backend-specific processing rules to these connections;
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- decide which server to forward the connection to according to the load
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balancing strategy;
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- apply the backend-specific processing rules to the response data;
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- apply the frontend-specific processing rules to the response data;
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- emit a log to report what happened in fine details;
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- in HTTP, loop back to the second step to wait for a new request, otherwise
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close the connection.
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Frontends and backends are sometimes considered as half-proxies, since they only
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look at one side of an end-to-end connection; the frontend only cares about the
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clients while the backend only cares about the servers. HAProxy also supports
|
|
full proxies which are exactly the union of a frontend and a backend. When HTTP
|
|
processing is desired, the configuration will generally be split into frontends
|
|
and backends as they open a lot of possibilities since any frontend may pass a
|
|
connection to any backend. With TCP-only proxies, using frontends and backends
|
|
rarely provides a benefit and the configuration can be more readable with full
|
|
proxies.
|
|
|
|
|
|
3.3. Basic features
|
|
-------------------
|
|
|
|
This section will enumerate a number of features that HAProxy implements, some
|
|
of which are generally expected from any modern load balancer, and some of
|
|
which are a direct benefit of HAProxy's architecture. More advanced features
|
|
will be detailed in the next section.
|
|
|
|
|
|
3.3.1. Basic features : Proxying
|
|
--------------------------------
|
|
|
|
Proxying is the action of transferring data between a client and a server over
|
|
two independent connections. The following basic features are supported by
|
|
HAProxy regarding proxying and connection management :
|
|
|
|
- Provide the server with a clean connection to protect them against any
|
|
client-side defect or attack;
|
|
|
|
- Listen to multiple IP addresses and/or ports, even port ranges;
|
|
|
|
- Transparent accept : intercept traffic targeting any arbitrary IP address
|
|
that doesn't even belong to the local system;
|
|
|
|
- Server port doesn't need to be related to listening port, and may even be
|
|
translated by a fixed offset (useful with ranges);
|
|
|
|
- Transparent connect : spoof the client's (or any) IP address if needed
|
|
when connecting to the server;
|
|
|
|
- Provide a reliable return IP address to the servers in multi-site LBs;
|
|
|
|
- Offload the server thanks to buffers and possibly short-lived connections
|
|
to reduce their concurrent connection count and their memory footprint;
|
|
|
|
- Optimize TCP stacks (e.g. SACK), congestion control, and reduce RTT impacts;
|
|
|
|
- Support different protocol families on both sides (e.g. IPv4/IPv6/Unix);
|
|
|
|
- Timeout enforcement : HAProxy supports multiple levels of timeouts depending
|
|
on the stage the connection is, so that a dead client or server, or an
|
|
attacker cannot be granted resources for too long;
|
|
|
|
- Protocol validation: HTTP, SSL, or payload are inspected and invalid
|
|
protocol elements are rejected, unless instructed to accept them anyway;
|
|
|
|
- Policy enforcement : ensure that only what is allowed may be forwarded;
|
|
|
|
- Both incoming and outgoing connections may be limited to certain network
|
|
namespaces (Linux only), making it easy to build a cross-container,
|
|
multi-tenant load balancer;
|
|
|
|
- PROXY protocol presents the client's IP address to the server even for
|
|
non-HTTP traffic. This is an HAProxy extension that was adopted by a number
|
|
of third-party products by now, at least these ones at the time of writing :
|
|
- client : haproxy, stud, stunnel, exaproxy, ELB, squid
|
|
- server : haproxy, stud, postfix, exim, nginx, squid, node.js, varnish
|
|
|
|
|
|
3.3.2. Basic features : SSL
|
|
---------------------------
|
|
|
|
HAProxy's SSL stack is recognized as one of the most featureful according to
|
|
Google's engineers (http://istlsfastyet.com/). The most commonly used features
|
|
making it quite complete are :
|
|
|
|
- SNI-based multi-hosting with no limit on sites count and focus on
|
|
performance. At least one deployment is known for running 50000 domains
|
|
with their respective certificates;
|
|
|
|
- support for wildcard certificates reduces the need for many certificates ;
|
|
|
|
- certificate-based client authentication with configurable policies on
|
|
failure to present a valid certificate. This allows to present a different
|
|
server farm to regenerate the client certificate for example;
|
|
|
|
- authentication of the backend server ensures the backend server is the real
|
|
one and not a man in the middle;
|
|
|
|
- authentication with the backend server lets the backend server know it's
|
|
really the expected haproxy node that is connecting to it;
|
|
|
|
- TLS NPN and ALPN extensions make it possible to reliably offload SPDY/HTTP2
|
|
connections and pass them in clear text to backend servers;
|
|
|
|
- OCSP stapling further reduces first page load time by delivering inline an
|
|
OCSP response when the client requests a Certificate Status Request;
|
|
|
|
- Dynamic record sizing provides both high performance and low latency, and
|
|
significantly reduces page load time by letting the browser start to fetch
|
|
new objects while packets are still in flight;
|
|
|
|
- permanent access to all relevant SSL/TLS layer information for logging,
|
|
access control, reporting etc. These elements can be embedded into HTTP
|
|
header or even as a PROXY protocol extension so that the offloaded server
|
|
gets all the information it would have had if it performed the SSL
|
|
termination itself.
|
|
|
|
- Detect, log and block certain known attacks even on vulnerable SSL libs,
|
|
such as the Heartbleed attack affecting certain versions of OpenSSL.
|
|
|
|
- support for stateless session resumption (RFC 5077 TLS Ticket extension).
|
|
TLS tickets can be updated from CLI which provides them means to implement
|
|
Perfect Forward Secrecy by frequently rotating the tickets.
|
|
|
|
|
|
3.3.3. Basic features : Monitoring
|
|
----------------------------------
|
|
|
|
HAProxy focuses a lot on availability. As such it cares about servers state,
|
|
and about reporting its own state to other network components :
|
|
|
|
- Servers' state is continuously monitored using per-server parameters. This
|
|
ensures the path to the server is operational for regular traffic;
|
|
|
|
- Health checks support two hysteresis for up and down transitions in order
|
|
to protect against state flapping;
|
|
|
|
- Checks can be sent to a different address/port/protocol : this makes it
|
|
easy to check a single service that is considered representative of multiple
|
|
ones, for example the HTTPS port for an HTTP+HTTPS server.
|
|
|
|
- Servers can track other servers and go down simultaneously : this ensures
|
|
that servers hosting multiple services can fail atomically and that no one
|
|
will be sent to a partially failed server;
|
|
|
|
- Agents may be deployed on the server to monitor load and health : a server
|
|
may be interested in reporting its load, operational status, administrative
|
|
status independently from what health checks can see. By running a simple
|
|
agent on the server, it's possible to consider the server's view of its own
|
|
health in addition to the health checks validating the whole path;
|
|
|
|
- Various check methods are available : TCP connect, HTTP request, SMTP hello,
|
|
SSL hello, LDAP, SQL, Redis, send/expect scripts, all with/without SSL;
|
|
|
|
- State change is notified in the logs and stats page with the failure reason
|
|
(e.g. the HTTP response received at the moment the failure was detected). An
|
|
e-mail can also be sent to a configurable address upon such a change ;
|
|
|
|
- Server state is also reported on the stats interface and can be used to take
|
|
routing decisions so that traffic may be sent to different farms depending
|
|
on their sizes and/or health (e.g. loss of an inter-DC link);
|
|
|
|
- HAProxy can use health check requests to pass information to the servers,
|
|
such as their names, weight, the number of other servers in the farm etc.
|
|
so that servers can adjust their response and decisions based on this
|
|
knowledge (e.g. postpone backups to keep more CPU available);
|
|
|
|
- Servers can use health checks to report more detailed state than just on/off
|
|
(e.g. I would like to stop, please stop sending new visitors);
|
|
|
|
- HAProxy itself can report its state to external components such as routers
|
|
or other load balancers, allowing to build very complete multi-path and
|
|
multi-layer infrastructures.
|
|
|
|
|
|
3.3.4. Basic features : High availability
|
|
-----------------------------------------
|
|
|
|
Just like any serious load balancer, HAProxy cares a lot about availability to
|
|
ensure the best global service continuity :
|
|
|
|
- Only valid servers are used ; the other ones are automatically evicted from
|
|
load balancing farms ; under certain conditions it is still possible to
|
|
force to use them though;
|
|
|
|
- Support for a graceful shutdown so that it is possible to take servers out
|
|
of a farm without affecting any connection;
|
|
|
|
- Backup servers are automatically used when active servers are down and
|
|
replace them so that sessions are not lost when possible. This also allows
|
|
to build multiple paths to reach the same server (e.g. multiple interfaces);
|
|
|
|
- Ability to return a global failed status for a farm when too many servers
|
|
are down. This, combined with the monitoring capabilities makes it possible
|
|
for an upstream component to choose a different LB node for a given service;
|
|
|
|
- Stateless design makes it easy to build clusters : by design, HAProxy does
|
|
its best to ensure the highest service continuity without having to store
|
|
information that could be lost in the event of a failure. This ensures that
|
|
a takeover is the most seamless possible;
|
|
|
|
- Integrates well with standard VRRP daemon keepalived : HAProxy easily tells
|
|
keepalived about its state and copes very well with floating virtual IP
|
|
addresses. Note: only use IP redundancy protocols (VRRP/CARP) over cluster-
|
|
based solutions (Heartbeat, ...) as they're the ones offering the fastest,
|
|
most seamless, and most reliable switchover.
|
|
|
|
|
|
3.3.5. Basic features : Load balancing
|
|
--------------------------------------
|
|
|
|
HAProxy offers a fairly complete set of load balancing features, most of which
|
|
are unfortunately not available in a number of other load balancing products :
|
|
|
|
- no less than 9 load balancing algorithms are supported, some of which apply
|
|
to input data to offer an infinite list of possibilities. The most common
|
|
ones are round-robin (for short connections, pick each server in turn),
|
|
leastconn (for long connections, pick the least recently used of the servers
|
|
with the lowest connection count), source (for SSL farms or terminal server
|
|
farms, the server directly depends on the client's source address), URI (for
|
|
HTTP caches, the server directly depends on the HTTP URI), hdr (the server
|
|
directly depends on the contents of a specific HTTP header field), first
|
|
(for short-lived virtual machines, all connections are packed on the
|
|
smallest possible subset of servers so that unused ones can be powered
|
|
down);
|
|
|
|
- all algorithms above support per-server weights so that it is possible to
|
|
accommodate from different server generations in a farm, or direct a small
|
|
fraction of the traffic to specific servers (debug mode, running the next
|
|
version of the software, etc);
|
|
|
|
- dynamic weights are supported for round-robin, leastconn and consistent
|
|
hashing ; this allows server weights to be modified on the fly from the CLI
|
|
or even by an agent running on the server;
|
|
|
|
- slow-start is supported whenever a dynamic weight is supported; this allows
|
|
a server to progressively take the traffic. This is an important feature
|
|
for fragile application servers which require to compile classes at runtime
|
|
as well as cold caches which need to fill up before being run at full
|
|
throttle;
|
|
|
|
- hashing can apply to various elements such as client's source address, URL
|
|
components, query string element, header field values, POST parameter, RDP
|
|
cookie;
|
|
|
|
- consistent hashing protects server farms against massive redistribution when
|
|
adding or removing servers in a farm. That's very important in large cache
|
|
farms and it allows slow-start to be used to refill cold caches;
|
|
|
|
- a number of internal metrics such as the number of connections per server,
|
|
per backend, the amount of available connection slots in a backend etc makes
|
|
it possible to build very advanced load balancing strategies.
|
|
|
|
|
|
3.3.6. Basic features : Stickiness
|
|
----------------------------------
|
|
|
|
Application load balancing would be useless without stickiness. HAProxy provides
|
|
a fairly comprehensive set of possibilities to maintain a visitor on the same
|
|
server even across various events such as server addition/removal, down/up
|
|
cycles, and some methods are designed to be resistant to the distance between
|
|
multiple load balancing nodes in that they don't require any replication :
|
|
|
|
- stickiness information can be individually matched and learned from
|
|
different places if desired. For example a JSESSIONID cookie may be matched
|
|
both in a cookie and in the URL. Up to 8 parallel sources can be learned at
|
|
the same time and each of them may point to a different stick-table;
|
|
|
|
- stickiness information can come from anything that can be seen within a
|
|
request or response, including source address, TCP payload offset and
|
|
length, HTTP query string elements, header field values, cookies, and so
|
|
on.
|
|
|
|
- stick-tables are replicated between all nodes in a multi-master fashion;
|
|
|
|
- commonly used elements such as SSL-ID or RDP cookies (for TSE farms) are
|
|
directly accessible to ease manipulation;
|
|
|
|
- all sticking rules may be dynamically conditioned by ACLs;
|
|
|
|
- it is possible to decide not to stick to certain servers, such as backup
|
|
servers, so that when the nominal server comes back, it automatically takes
|
|
the load back. This is often used in multi-path environments;
|
|
|
|
- in HTTP it is often preferred not to learn anything and instead manipulate
|
|
a cookie dedicated to stickiness. For this, it's possible to detect,
|
|
rewrite, insert or prefix such a cookie to let the client remember what
|
|
server was assigned;
|
|
|
|
- the server may decide to change or clean the stickiness cookie on logout,
|
|
so that leaving visitors are automatically unbound from the server;
|
|
|
|
- using ACL-based rules it is also possible to selectively ignore or enforce
|
|
stickiness regardless of the server's state; combined with advanced health
|
|
checks, that helps admins verify that the server they're installing is up
|
|
and running before presenting it to the whole world;
|
|
|
|
- an innovative mechanism to set a maximum idle time and duration on cookies
|
|
ensures that stickiness can be smoothly stopped on devices which are never
|
|
closed (smartphones, TVs, home appliances) without having to store them on
|
|
persistent storage;
|
|
|
|
- multiple server entries may share the same stickiness keys so that
|
|
stickiness is not lost in multi-path environments when one path goes down;
|
|
|
|
- soft-stop ensures that only users with stickiness information will continue
|
|
to reach the server they've been assigned to but no new users will go there.
|
|
|
|
|
|
3.3.7. Basic features : Sampling and converting information
|
|
-----------------------------------------------------------
|
|
|
|
HAProxy supports information sampling using a wide set of "sample fetch
|
|
functions". The principle is to extract pieces of information known as samples,
|
|
for immediate use. This is used for stickiness, to build conditions, to produce
|
|
information in logs or to enrich HTTP headers.
|
|
|
|
Samples can be fetched from various sources :
|
|
|
|
- constants : integers, strings, IP addresses, binary blocks;
|
|
|
|
- the process : date, environment variables, server/frontend/backend/process
|
|
state, byte/connection counts/rates, queue length, random generator, ...
|
|
|
|
- variables : per-session, per-request, per-response variables;
|
|
|
|
- the client connection : source and destination addresses and ports, and all
|
|
related statistics counters;
|
|
|
|
- the SSL client session : protocol, version, algorithm, cipher, key size,
|
|
session ID, all client and server certificate fields, certificate serial,
|
|
SNI, ALPN, NPN, client support for certain extensions;
|
|
|
|
- request and response buffers contents : arbitrary payload at offset/length,
|
|
data length, RDP cookie, decoding of SSL hello type, decoding of TLS SNI;
|
|
|
|
- HTTP (request and response) : method, URI, path, query string arguments,
|
|
status code, headers values, positional header value, cookies, captures,
|
|
authentication, body elements;
|
|
|
|
A sample may then pass through a number of operators known as "converters" to
|
|
experience some transformation. A converter consumes a sample and produces a
|
|
new one, possibly of a completely different type. For example, a converter may
|
|
be used to return only the integer length of the input string, or could turn a
|
|
string to upper case. Any arbitrary number of converters may be applied in
|
|
series to a sample before final use. Among all available sample converters, the
|
|
following ones are the most commonly used :
|
|
|
|
- arithmetic and logic operators : they make it possible to perform advanced
|
|
computation on input data, such as computing ratios, percentages or simply
|
|
converting from one unit to another one;
|
|
|
|
- IP address masks are useful when some addresses need to be grouped by larger
|
|
networks;
|
|
|
|
- data representation : URL-decode, base64, hex, JSON strings, hashing;
|
|
|
|
- string conversion : extract substrings at fixed positions, fixed length,
|
|
extract specific fields around certain delimiters, extract certain words,
|
|
change case, apply regex-based substitution;
|
|
|
|
- date conversion : convert to HTTP date format, convert local to UTC and
|
|
conversely, add or remove offset;
|
|
|
|
- lookup an entry in a stick table to find statistics or assigned server;
|
|
|
|
- map-based key-to-value conversion from a file (mostly used for geolocation).
|
|
|
|
|
|
3.3.8. Basic features : Maps
|
|
----------------------------
|
|
|
|
Maps are a powerful type of converter consisting in loading a two-columns file
|
|
into memory at boot time, then looking up each input sample from the first
|
|
column and either returning the corresponding pattern on the second column if
|
|
the entry was found, or returning a default value. The output information also
|
|
being a sample, it can in turn experience other transformations including other
|
|
map lookups. Maps are most commonly used to translate the client's IP address
|
|
to an AS number or country code since they support a longest match for network
|
|
addresses but they can be used for various other purposes.
|
|
|
|
Part of their strength comes from being updatable on the fly either from the CLI
|
|
or from certain actions using other samples, making them capable of storing and
|
|
retrieving information between subsequent accesses. Another strength comes from
|
|
the binary tree based indexation which makes them extremely fast even when they
|
|
contain hundreds of thousands of entries, making geolocation very cheap and easy
|
|
to set up.
|
|
|
|
|
|
3.3.9. Basic features : ACLs and conditions
|
|
-------------------------------------------
|
|
|
|
Most operations in HAProxy can be made conditional. Conditions are built by
|
|
combining multiple ACLs using logic operators (AND, OR, NOT). Each ACL is a
|
|
series of tests based on the following elements :
|
|
|
|
- a sample fetch method to retrieve the element to test ;
|
|
|
|
- an optional series of converters to transform the element ;
|
|
|
|
- a list of patterns to match against ;
|
|
|
|
- a matching method to indicate how to compare the patterns with the sample
|
|
|
|
For example, the sample may be taken from the HTTP "Host" header, it could then
|
|
be converted to lower case, then matched against a number of regex patterns
|
|
using the regex matching method.
|
|
|
|
Technically, ACLs are built on the same core as the maps, they share the exact
|
|
same internal structure, pattern matching methods and performance. The only real
|
|
difference is that instead of returning a sample, they only return "found" or
|
|
or "not found". In terms of usage, ACL patterns may be declared inline in the
|
|
configuration file and do not require their own file. ACLs may be named for ease
|
|
of use or to make configurations understandable. A named ACL may be declared
|
|
multiple times and it will evaluate all definitions in turn until one matches.
|
|
|
|
About 13 different pattern matching methods are provided, among which IP address
|
|
mask, integer ranges, substrings, regex. They work like functions, and just like
|
|
with any programming language, only what is needed is evaluated, so when a
|
|
condition involving an OR is already true, next ones are not evaluated, and
|
|
similarly when a condition involving an AND is already false, the rest of the
|
|
condition is not evaluated.
|
|
|
|
There is no practical limit to the number of declared ACLs, and a handful of
|
|
commonly used ones are provided. However experience has shown that setups using
|
|
a lot of named ACLs are quite hard to troubleshoot and that sometimes using
|
|
anonymous ACLs inline is easier as it requires less references out of the scope
|
|
being analyzed.
|
|
|
|
|
|
3.3.10. Basic features : Content switching
|
|
------------------------------------------
|
|
|
|
HAProxy implements a mechanism known as content-based switching. The principle
|
|
is that a connection or request arrives on a frontend, then the information
|
|
carried with this request or connection are processed, and at this point it is
|
|
possible to write ACLs-based conditions making use of these information to
|
|
decide what backend will process the request. Thus the traffic is directed to
|
|
one backend or another based on the request's contents. The most common example
|
|
consists in using the Host header and/or elements from the path (sub-directories
|
|
or file-name extensions) to decide whether an HTTP request targets a static
|
|
object or the application, and to route static objects traffic to a backend made
|
|
of fast and light servers, and all the remaining traffic to a more complex
|
|
application server, thus constituting a fine-grained virtual hosting solution.
|
|
This is quite convenient to make multiple technologies coexist as a more global
|
|
solution.
|
|
|
|
Another use case of content-switching consists in using different load balancing
|
|
algorithms depending on various criteria. A cache may use a URI hash while an
|
|
application would use round-robin.
|
|
|
|
Last but not least, it allows multiple customers to use a small share of a
|
|
common resource by enforcing per-backend (thus per-customer connection limits).
|
|
|
|
Content switching rules scale very well, though their performance may depend on
|
|
the number and complexity of the ACLs in use. But it is also possible to write
|
|
dynamic content switching rules where a sample value directly turns into a
|
|
backend name and without making use of ACLs at all. Such configurations have
|
|
been reported to work fine at least with 300000 backends in production.
|
|
|
|
|
|
3.3.11. Basic features : Stick-tables
|
|
-------------------------------------
|
|
|
|
Stick-tables are commonly used to store stickiness information, that is, to keep
|
|
a reference to the server a certain visitor was directed to. The key is then the
|
|
identifier associated with the visitor (its source address, the SSL ID of the
|
|
connection, an HTTP or RDP cookie, the customer number extracted from the URL or
|
|
from the payload, ...) and the stored value is then the server's identifier.
|
|
|
|
Stick tables may use 3 different types of samples for their keys : integers,
|
|
strings and addresses. Only one stick-table may be referenced in a proxy, and it
|
|
is designated everywhere with the proxy name. Up to 8 keys may be tracked in
|
|
parallel. The server identifier is committed during request or response
|
|
processing once both the key and the server are known.
|
|
|
|
Stick-table contents may be replicated in active-active mode with other HAProxy
|
|
nodes known as "peers" as well as with the new process during a reload operation
|
|
so that all load balancing nodes share the same information and take the same
|
|
routing decision if client's requests are spread over multiple nodes.
|
|
|
|
Since stick-tables are indexed on what allows to recognize a client, they are
|
|
often also used to store extra information such as per-client statistics. The
|
|
extra statistics take some extra space and need to be explicitly declared. The
|
|
type of statistics that may be stored includes the input and output bandwidth,
|
|
the number of concurrent connections, the connection rate and count over a
|
|
period, the amount and frequency of errors, some specific tags and counters,
|
|
etc. In order to support keeping such information without being forced to
|
|
stick to a given server, a special "tracking" feature is implemented and allows
|
|
to track up to 3 simultaneous keys from different tables at the same time
|
|
regardless of stickiness rules. Each stored statistics may be searched, dumped
|
|
and cleared from the CLI and adds to the live troubleshooting capabilities.
|
|
|
|
While this mechanism can be used to surclass a returning visitor or to adjust
|
|
the delivered quality of service depending on good or bad behavior, it is
|
|
mostly used to fight against service abuse and more generally DDoS as it allows
|
|
to build complex models to detect certain bad behaviors at a high processing
|
|
speed.
|
|
|
|
|
|
3.3.12. Basic features : Formatted strings
|
|
-----------------------------------------
|
|
|
|
There are many places where HAProxy needs to manipulate character strings, such
|
|
as logs, redirects, header additions, and so on. In order to provide the
|
|
greatest flexibility, the notion of Formatted strings was introduced, initially
|
|
for logging purposes, which explains why it's still called "log-format". These
|
|
strings contain escape characters allowing to introduce various dynamic data
|
|
including variables and sample fetch expressions into strings, and even to
|
|
adjust the encoding while the result is being turned into a string (for example,
|
|
adding quotes). This provides a powerful way to build header contents or to
|
|
customize log lines. Additionally, in order to remain simple to build most
|
|
common strings, about 50 special tags are provided as shortcuts for information
|
|
commonly used in logs.
|
|
|
|
|
|
3.3.13. Basic features : HTTP rewriting and redirection
|
|
-------------------------------------------------------
|
|
|
|
Installing a load balancer in front of an application that was never designed
|
|
for this can be a challenging task without the proper tools. One of the most
|
|
commonly requested operation in this case is to adjust requests and response
|
|
headers to make the load balancer appear as the origin server and to fix hard
|
|
coded information. This comes with changing the path in requests (which is
|
|
strongly advised against), modifying Host header field, modifying the Location
|
|
response header field for redirects, modifying the path and domain attribute
|
|
for cookies, and so on. It also happens that a number of servers are somewhat
|
|
verbose and tend to leak too much information in the response, making them more
|
|
vulnerable to targeted attacks. While it's theoretically not the role of a load
|
|
balancer to clean this up, in practice it's located at the best place in the
|
|
infrastructure to guarantee that everything is cleaned up.
|
|
|
|
Similarly, sometimes the load balancer will have to intercept some requests and
|
|
respond with a redirect to a new target URL. While some people tend to confuse
|
|
redirects and rewriting, these are two completely different concepts, since the
|
|
rewriting makes the client and the server see different things (and disagree on
|
|
the location of the page being visited) while redirects ask the client to visit
|
|
the new URL so that it sees the same location as the server.
|
|
|
|
In order to do this, HAProxy supports various possibilities for rewriting and
|
|
redirects, among which :
|
|
|
|
- regex-based URL and header rewriting in requests and responses. Regex are
|
|
the most commonly used tool to modify header values since they're easy to
|
|
manipulate and well understood;
|
|
|
|
- headers may also be appended, deleted or replaced based on formatted strings
|
|
so that it is possible to pass information there (e.g. client side TLS
|
|
algorithm and cipher);
|
|
|
|
- HTTP redirects can use any 3xx code to a relative, absolute, or completely
|
|
dynamic (formatted string) URI;
|
|
|
|
- HTTP redirects also support some extra options such as setting or clearing
|
|
a specific cookie, dropping the query string, appending a slash if missing,
|
|
and so on;
|
|
|
|
- all operations support ACL-based conditions;
|
|
|
|
|
|
3.3.14. Basic features : Server protection
|
|
------------------------------------------
|
|
|
|
HAProxy does a lot to maximize service availability, and for this it takes
|
|
large efforts to protect servers against overloading and attacks. The first
|
|
and most important point is that only complete and valid requests are forwarded
|
|
to the servers. The initial reason is that HAProxy needs to find the protocol
|
|
elements it needs to stay synchronized with the byte stream, and the second
|
|
reason is that until the request is complete, there is no way to know if some
|
|
elements will change its semantics. The direct benefit from this is that servers
|
|
are not exposed to invalid or incomplete requests. This is a very effective
|
|
protection against slowloris attacks, which have almost no impact on HAProxy.
|
|
|
|
Another important point is that HAProxy contains buffers to store requests and
|
|
responses, and that by only sending a request to a server when it's complete and
|
|
by reading the whole response very quickly from the local network, the server
|
|
side connection is used for a very short time and this preserves server
|
|
resources as much as possible.
|
|
|
|
A direct extension to this is that HAProxy can artificially limit the number of
|
|
concurrent connections or outstanding requests to a server, which guarantees
|
|
that the server will never be overloaded even if it continuously runs at 100% of
|
|
its capacity during traffic spikes. All excess requests will simply be queued to
|
|
be processed when one slot is released. In the end, this huge resource savings
|
|
most often ensures so much better server response times that it ends up actually
|
|
being faster than by overloading the server. Queued requests may be redispatched
|
|
to other servers, or even aborted in queue when the client aborts, which also
|
|
protects the servers against the "reload effect", where each click on "reload"
|
|
by a visitor on a slow-loading page usually induces a new request and maintains
|
|
the server in an overloaded state.
|
|
|
|
The slow-start mechanism also protects restarting servers against high traffic
|
|
levels while they're still finalizing their startup or compiling some classes.
|
|
|
|
Regarding the protocol-level protection, it is possible to relax the HTTP parser
|
|
to accept non standard-compliant but harmless requests or responses and even to
|
|
fix them. This allows bogus applications to be accessible while a fix is being
|
|
developed. In parallel, offending messages are completely captured with a
|
|
detailed report that help developers spot the issue in the application. The most
|
|
dangerous protocol violations are properly detected and dealt with and fixed.
|
|
For example malformed requests or responses with two Content-length headers are
|
|
either fixed if the values are exactly the same, or rejected if they differ,
|
|
since it becomes a security problem. Protocol inspection is not limited to HTTP,
|
|
it is also available for other protocols like TLS or RDP.
|
|
|
|
When a protocol violation or attack is detected, there are various options to
|
|
respond to the user, such as returning the common "HTTP 400 bad request",
|
|
closing the connection with a TCP reset, or faking an error after a long delay
|
|
("tarpit") to confuse the attacker. All of these contribute to protecting the
|
|
servers by discouraging the offending client from pursuing an attack that
|
|
becomes very expensive to maintain.
|
|
|
|
HAProxy also proposes some more advanced options to protect against accidental
|
|
data leaks and session crossing. Not only it can log suspicious server responses
|
|
but it will also log and optionally block a response which might affect a given
|
|
visitors' confidentiality. One such example is a cacheable cookie appearing in a
|
|
cacheable response and which may result in an intermediary cache to deliver it
|
|
to another visitor, causing an accidental session sharing.
|
|
|
|
|
|
3.3.15. Basic features : Logging
|
|
--------------------------------
|
|
|
|
Logging is an extremely important feature for a load balancer, first because a
|
|
load balancer is often wrongly accused of causing the problems it reveals, and
|
|
second because it is placed at a critical point in an infrastructure where all
|
|
normal and abnormal activity needs to be analyzed and correlated with other
|
|
components.
|
|
|
|
HAProxy provides very detailed logs, with millisecond accuracy and the exact
|
|
connection accept time that can be searched in firewalls logs (e.g. for NAT
|
|
correlation). By default, TCP and HTTP logs are quite detailed and contain
|
|
everything needed for troubleshooting, such as source IP address and port,
|
|
frontend, backend, server, timers (request receipt duration, queue duration,
|
|
connection setup time, response headers time, data transfer time), global
|
|
process state, connection counts, queue status, retries count, detailed
|
|
stickiness actions and disconnect reasons, header captures with a safe output
|
|
encoding. It is then possible to extend or replace this format to include any
|
|
sampled data, variables, captures, resulting in very detailed information. For
|
|
example it is possible to log the number of cumulative requests or number of
|
|
different URLs visited by a client.
|
|
|
|
The log level may be adjusted per request using standard ACLs, so it is possible
|
|
to automatically silent some logs considered as pollution and instead raise
|
|
warnings when some abnormal behavior happen for a small part of the traffic
|
|
(e.g. too many URLs or HTTP errors for a source address). Administrative logs
|
|
are also emitted with their own levels to inform about the loss or recovery of a
|
|
server for example.
|
|
|
|
Each frontend and backend may use multiple independent log outputs, which eases
|
|
multi-tenancy. Logs are preferably sent over UDP, maybe JSON-encoded, and are
|
|
truncated after a configurable line length in order to guarantee delivery.
|
|
|
|
|
|
3.3.16. Basic features : Statistics
|
|
-----------------------------------
|
|
|
|
HAProxy provides a web-based statistics reporting interface with authentication,
|
|
security levels and scopes. It is thus possible to provide each hosted customer
|
|
with his own page showing only his own instances. This page can be located in a
|
|
hidden URL part of the regular web site so that no new port needs to be opened.
|
|
This page may also report the availability of other HAProxy nodes so that it is
|
|
easy to spot if everything works as expected at a glance. The view is synthetic
|
|
with a lot of details accessible (such as error causes, last access and last
|
|
change duration, etc), which are also accessible as a CSV table that other tools
|
|
may import to draw graphs. The page may self-refresh to be used as a monitoring
|
|
page on a large display. In administration mode, the page also allows to change
|
|
server state to ease maintenance operations.
|
|
|
|
|
|
3.4. Advanced features
|
|
----------------------
|
|
|
|
3.4.1. Advanced features : Management
|
|
-------------------------------------
|
|
|
|
HAProxy is designed to remain extremely stable and safe to manage in a regular
|
|
production environment. It is provided as a single executable file which doesn't
|
|
require any installation process. Multiple versions can easily coexist, meaning
|
|
that it's possible (and recommended) to upgrade instances progressively by
|
|
order of importance instead of migrating all of them at once. Configuration
|
|
files are easily versioned. Configuration checking is done off-line so it
|
|
doesn't require to restart a service that will possibly fail. During
|
|
configuration checks, a number of advanced mistakes may be detected (e.g. a rule
|
|
hiding another one, or stickiness that will not work) and detailed warnings and
|
|
configuration hints are proposed to fix them. Backwards configuration file
|
|
compatibility goes very far away in time, with version 1.5 still fully
|
|
supporting configurations for versions 1.1 written 13 years before, and 1.6
|
|
only dropping support for almost unused, obsolete keywords that can be done
|
|
differently. The configuration and software upgrade mechanism is smooth and non
|
|
disruptive in that it allows old and new processes to coexist on the system,
|
|
each handling its own connections. System status, build options, and library
|
|
compatibility are reported on startup.
|
|
|
|
Some advanced features allow an application administrator to smoothly stop a
|
|
server, detect when there's no activity on it anymore, then take it off-line,
|
|
stop it, upgrade it and ensure it doesn't take any traffic while being upgraded,
|
|
then test it again through the normal path without opening it to the public, and
|
|
all of this without touching HAProxy at all. This ensures that even complicated
|
|
production operations may be done during opening hours with all technical
|
|
resources available.
|
|
|
|
The process tries to save resources as much as possible, uses memory pools to
|
|
save on allocation time and limit memory fragmentation, releases payload buffers
|
|
as soon as their contents are sent, and supports enforcing strong memory limits
|
|
above which connections have to wait for a buffer to become available instead of
|
|
allocating more memory. This system helps guarantee memory usage in certain
|
|
strict environments.
|
|
|
|
A command line interface (CLI) is available as a UNIX or TCP socket, to perform
|
|
a number of operations and to retrieve troubleshooting information. Everything
|
|
done on this socket doesn't require a configuration change, so it is mostly used
|
|
for temporary changes. Using this interface it is possible to change a server's
|
|
address, weight and status, to consult statistics and clear counters, dump and
|
|
clear stickiness tables, possibly selectively by key criteria, dump and kill
|
|
client-side and server-side connections, dump captured errors with a detailed
|
|
analysis of the exact cause and location of the error, dump, add and remove
|
|
entries from ACLs and maps, update TLS shared secrets, apply connection limits
|
|
and rate limits on the fly to arbitrary frontends (useful in shared hosting
|
|
environments), and disable a specific frontend to release a listening port
|
|
(useful when daytime operations are forbidden and a fix is needed nonetheless).
|
|
|
|
For environments where SNMP is mandatory, at least two agents exist, one is
|
|
provided with the HAProxy sources and relies on the Net-SNMP Perl module.
|
|
Another one is provided with the commercial packages and doesn't require Perl.
|
|
Both are roughly equivalent in terms of coverage.
|
|
|
|
It is often recommended to install 4 utilities on the machine where HAProxy is
|
|
deployed :
|
|
|
|
- socat (in order to connect to the CLI, though certain forks of netcat can
|
|
also do it to some extents);
|
|
|
|
- halog from the latest HAProxy version : this is the log analysis tool, it
|
|
parses native TCP and HTTP logs extremely fast (1 to 2 GB per second) and
|
|
extracts useful information and statistics such as requests per URL, per
|
|
source address, URLs sorted by response time or error rate, termination
|
|
codes etc. It was designed to be deployed on the production servers to
|
|
help troubleshoot live issues so it has to be there ready to be used;
|
|
|
|
- tcpdump : this is highly recommended to take the network traces needed to
|
|
troubleshoot an issue that was made visible in the logs. There is a moment
|
|
where application and haproxy's analysis will diverge and the network traces
|
|
are the only way to say who's right and who's wrong. It's also fairly common
|
|
to detect bugs in network stacks and hypervisors thanks to tcpdump;
|
|
|
|
- strace : it is tcpdump's companion. It will report what HAProxy really sees
|
|
and will help sort out the issues the operating system is responsible for
|
|
from the ones HAProxy is responsible for. Strace is often requested when a
|
|
bug in HAProxy is suspected;
|
|
|
|
|
|
3.4.2. Advanced features : System-specific capabilities
|
|
-------------------------------------------------------
|
|
|
|
Depending on the operating system HAProxy is deployed on, certain extra features
|
|
may be available or needed. While it is supported on a number of platforms,
|
|
HAProxy is primarily developed on Linux, which explains why some features are
|
|
only available on this platform.
|
|
|
|
The transparent bind and connect features, the support for binding connections
|
|
to a specific network interface, as well as the ability to bind multiple
|
|
processes to the same IP address and ports are only available on Linux and BSD
|
|
systems, though only Linux performs a kernel-side load balancing of the incoming
|
|
requests between the available processes.
|
|
|
|
On Linux, there are also a number of extra features and optimizations including
|
|
support for network namespaces (also known as "containers") allowing HAProxy to
|
|
be a gateway between all containers, the ability to set the MSS, Netfilter marks
|
|
and IP TOS field on the client side connection, support for TCP FastOpen on the
|
|
listening side, TCP user timeouts to let the kernel quickly kill connections
|
|
when it detects the client has disappeared before the configured timeouts, TCP
|
|
splicing to let the kernel forward data between the two sides of a connections
|
|
thus avoiding multiple memory copies, the ability to enable the "defer-accept"
|
|
bind option to only get notified of an incoming connection once data become
|
|
available in the kernel buffers, and the ability to send the request with the
|
|
ACK confirming a connect (sometimes called "piggy-back") which is enabled with
|
|
the "tcp-smart-connect" option. On Linux, HAProxy also takes great care of
|
|
manipulating the TCP delayed ACKs to save as many packets as possible on the
|
|
network.
|
|
|
|
Some systems have an unreliable clock which jumps back and forth in the past
|
|
and in the future. This used to happen with some NUMA systems where multiple
|
|
processors didn't see the exact same time of day, and recently it became more
|
|
common in virtualized environments where the virtual clock has no relation with
|
|
the real clock, resulting in huge time jumps (sometimes up to 30 seconds have
|
|
been observed). This causes a lot of trouble with respect to timeout enforcement
|
|
in general. Due to this flaw of these systems, HAProxy maintains its own
|
|
monotonic clock which is based on the system's clock but where drift is measured
|
|
and compensated for. This ensures that even with a very bad system clock, timers
|
|
remain reasonably accurate and timeouts continue to work. Note that this problem
|
|
affects all the software running on such systems and is not specific to HAProxy.
|
|
The common effects are spurious timeouts or application freezes. Thus if this
|
|
behavior is detected on a system, it must be fixed, regardless of the fact that
|
|
HAProxy protects itself against it.
|
|
|
|
|
|
3.4.3. Advanced features : Scripting
|
|
------------------------------------
|
|
|
|
HAProxy can be built with support for the Lua embedded language, which opens a
|
|
wide area of new possibilities related to complex manipulation of requests or
|
|
responses, routing decisions, statistics processing and so on. Using Lua it is
|
|
even possible to establish parallel connections to other servers to exchange
|
|
information. This way it becomes possible (though complex) to develop an
|
|
authentication system for example. Please refer to the documentation in the file
|
|
"doc/lua-api/index.rst" for more information on how to use Lua.
|
|
|
|
|
|
3.5. Sizing
|
|
-----------
|
|
|
|
Typical CPU usage figures show 15% of the processing time spent in HAProxy
|
|
versus 85% in the kernel in TCP or HTTP close mode, and about 30% for HAProxy
|
|
versus 70% for the kernel in HTTP keep-alive mode. This means that the operating
|
|
system and its tuning have a strong impact on the global performance.
|
|
|
|
Usages vary a lot between users, some focus on bandwidth, other ones on request
|
|
rate, others on connection concurrency, others on SSL performance. This section
|
|
aims at providing a few elements to help with this task.
|
|
|
|
It is important to keep in mind that every operation comes with a cost, so each
|
|
individual operation adds its overhead on top of the other ones, which may be
|
|
negligible in certain circumstances, and which may dominate in other cases.
|
|
|
|
When processing the requests from a connection, we can say that :
|
|
|
|
- forwarding data costs less than parsing request or response headers;
|
|
|
|
- parsing request or response headers cost less than establishing then closing
|
|
a connection to a server;
|
|
|
|
- establishing an closing a connection costs less than a TLS resume operation;
|
|
|
|
- a TLS resume operation costs less than a full TLS handshake with a key
|
|
computation;
|
|
|
|
- an idle connection costs less CPU than a connection whose buffers hold data;
|
|
|
|
- a TLS context costs even more memory than a connection with data;
|
|
|
|
So in practice, it is cheaper to process payload bytes than header bytes, thus
|
|
it is easier to achieve high network bandwidth with large objects (few requests
|
|
per volume unit) than with small objects (many requests per volume unit). This
|
|
explains why maximum bandwidth is always measured with large objects, while
|
|
request rate or connection rates are measured with small objects.
|
|
|
|
Some operations scale well on multiple processes spread over multiple CPUs,
|
|
and others don't scale as well. Network bandwidth doesn't scale very far because
|
|
the CPU is rarely the bottleneck for large objects, it's mostly the network
|
|
bandwidth and data buses to reach the network interfaces. The connection rate
|
|
doesn't scale well over multiple processors due to a few locks in the system
|
|
when dealing with the local ports table. The request rate over persistent
|
|
connections scales very well as it doesn't involve much memory nor network
|
|
bandwidth and doesn't require to access locked structures. TLS key computation
|
|
scales very well as it's totally CPU-bound. TLS resume scales moderately well,
|
|
but reaches its limits around 4 processes where the overhead of accessing the
|
|
shared table offsets the small gains expected from more power.
|
|
|
|
The performance numbers one can expect from a very well tuned system are in the
|
|
following range. It is important to take them as orders of magnitude and to
|
|
expect significant variations in any direction based on the processor, IRQ
|
|
setting, memory type, network interface type, operating system tuning and so on.
|
|
|
|
The following numbers were found on a Core i7 running at 3.7 GHz equipped with
|
|
a dual-port 10 Gbps NICs running Linux kernel 3.10, HAProxy 1.6 and OpenSSL
|
|
1.0.2. HAProxy was running as a single process on a single dedicated CPU core,
|
|
and two extra cores were dedicated to network interrupts :
|
|
|
|
- 20 Gbps of maximum network bandwidth in clear text for objects 256 kB or
|
|
higher, 10 Gbps for 41kB or higher;
|
|
|
|
- 4.6 Gbps of TLS traffic using AES256-GCM cipher with large objects;
|
|
|
|
- 83000 TCP connections per second from client to server;
|
|
|
|
- 82000 HTTP connections per second from client to server;
|
|
|
|
- 97000 HTTP requests per second in server-close mode (keep-alive with the
|
|
client, close with the server);
|
|
|
|
- 243000 HTTP requests per second in end-to-end keep-alive mode;
|
|
|
|
- 300000 filtered TCP connections per second (anti-DDoS)
|
|
|
|
- 160000 HTTPS requests per second in keep-alive mode over persistent TLS
|
|
connections;
|
|
|
|
- 13100 HTTPS requests per second using TLS resumed connections;
|
|
|
|
- 1300 HTTPS connections per second using TLS connections renegotiated with
|
|
RSA2048;
|
|
|
|
- 20000 concurrent saturated connections per GB of RAM, including the memory
|
|
required for system buffers; it is possible to do better with careful tuning
|
|
but this result it easy to achieve.
|
|
|
|
- about 8000 concurrent TLS connections (client-side only) per GB of RAM,
|
|
including the memory required for system buffers;
|
|
|
|
- about 5000 concurrent end-to-end TLS connections (both sides) per GB of
|
|
RAM including the memory required for system buffers;
|
|
|
|
Thus a good rule of thumb to keep in mind is that the request rate is divided
|
|
by 10 between TLS keep-alive and TLS resume, and between TLS resume and TLS
|
|
renegotiation, while it's only divided by 3 between HTTP keep-alive and HTTP
|
|
close. Another good rule of thumb is to remember that a high frequency core
|
|
with AES instructions can do around 5 Gbps of AES-GCM per core.
|
|
|
|
Having more cores rarely helps (except for TLS) and is even counter-productive
|
|
due to the lower frequency. In general a small number of high frequency cores
|
|
is better.
|
|
|
|
Another good rule of thumb is to consider that on the same server, HAProxy will
|
|
be able to saturate :
|
|
|
|
- about 5-10 static file servers or caching proxies;
|
|
|
|
- about 100 anti-virus proxies;
|
|
|
|
- and about 100-1000 application servers depending on the technology in use.
|
|
|
|
|
|
3.6. How to get HAProxy
|
|
-----------------------
|
|
|
|
HAProxy is an open source project covered by the GPLv2 license, meaning that
|
|
everyone is allowed to redistribute it provided that access to the sources is
|
|
also provided upon request, especially if any modifications were made.
|
|
|
|
HAProxy evolves as a main development branch called "master" or "mainline", from
|
|
which new branches are derived once the code is considered stable. A lot of web
|
|
sites run some development branches in production on a voluntarily basis, either
|
|
to participate to the project or because they need a bleeding edge feature, and
|
|
their feedback is highly valuable to fix bugs and judge the overall quality and
|
|
stability of the version being developed.
|
|
|
|
The new branches that are created when the code is stable enough constitute a
|
|
stable version and are generally maintained for several years, so that there is
|
|
no emergency to migrate to a newer branch even when you're not on the latest.
|
|
Once a stable branch is issued, it may only receive bug fixes, and very rarely
|
|
minor feature updates when that makes users' life easier. All fixes that go into
|
|
a stable branch necessarily come from the master branch. This guarantees that no
|
|
fix will be lost after an upgrade. For this reason, if you fix a bug, please
|
|
make the patch against the master branch, not the stable branch. You may even
|
|
discover it was already fixed. This process also ensures that regressions in a
|
|
stable branch are extremely rare, so there is never any excuse for not upgrading
|
|
to the latest version in your current branch.
|
|
|
|
Branches are numbered with two digits delimited with a dot, such as "1.6". A
|
|
complete version includes one or two sub-version numbers indicating the level of
|
|
fix. For example, version 1.5.14 is the 14th fix release in branch 1.5 after
|
|
version 1.5.0 was issued. It contains 126 fixes for individual bugs, 24 updates
|
|
on the documentation, and 75 other backported patches, most of which were needed
|
|
to fix the aforementioned 126 bugs. An existing feature may never be modified
|
|
nor removed in a stable branch, in order to guarantee that upgrades within the
|
|
same branch will always be harmless.
|
|
|
|
HAProxy is available from multiple sources, at different release rhythms :
|
|
|
|
- The official community web site : http://www.haproxy.org/ : this site
|
|
provides the sources of the latest development release, all stable releases,
|
|
as well as nightly snapshots for each branch. The release cycle is not fast,
|
|
several months between stable releases, or between development snapshots.
|
|
Very old versions are still supported there. Everything is provided as
|
|
sources only, so whatever comes from there needs to be rebuilt and/or
|
|
repackaged;
|
|
|
|
- A number of operating systems such as Linux distributions and BSD ports.
|
|
These systems generally provide long-term maintained versions which do not
|
|
always contain all the fixes from the official ones, but which at least
|
|
contain the critical fixes. It often is a good option for most users who do
|
|
not seek advanced configurations and just want to keep updates easy;
|
|
|
|
- Commercial versions from http://www.haproxy.com/ : these are supported
|
|
professional packages built for various operating systems or provided as
|
|
appliances, based on the latest stable versions and including a number of
|
|
features backported from the next release for which there is a strong
|
|
demand. It is the best option for users seeking the latest features with
|
|
the reliability of a stable branch, the fastest response time to fix bugs,
|
|
or simply support contracts on top of an open source product;
|
|
|
|
|
|
In order to ensure that the version you're using is the latest one in your
|
|
branch, you need to proceed this way :
|
|
|
|
- verify which HAProxy executable you're running : some systems ship it by
|
|
default and administrators install their versions somewhere else on the
|
|
system, so it is important to verify in the startup scripts which one is
|
|
used;
|
|
|
|
- determine which source your HAProxy version comes from. For this, it's
|
|
generally sufficient to type "haproxy -v". A development version will
|
|
appear like this, with the "dev" word after the branch number :
|
|
|
|
HA-Proxy version 1.6-dev3-385ecc-68 2015/08/18
|
|
|
|
A stable version will appear like this, as well as unmodified stable
|
|
versions provided by operating system vendors :
|
|
|
|
HA-Proxy version 1.5.14 2015/07/02
|
|
|
|
And a nightly snapshot of a stable version will appear like this with an
|
|
hexadecimal sequence after the version, and with the date of the snapshot
|
|
instead of the date of the release :
|
|
|
|
HA-Proxy version 1.5.14-e4766ba 2015/07/29
|
|
|
|
Any other format may indicate a system-specific package with its own
|
|
patch set. For example HAProxy Enterprise versions will appear with the
|
|
following format (<branch>-<latest commit>-<revision>) :
|
|
|
|
HA-Proxy version 1.5.0-994126-357 2015/07/02
|
|
|
|
- for system-specific packages, you have to check with your vendor's package
|
|
repository or update system to ensure that your system is still supported,
|
|
and that fixes are still provided for your branch. For community versions
|
|
coming from haproxy.org, just visit the site, verify the status of your
|
|
branch and compare the latest version with yours to see if you're on the
|
|
latest one. If not you can upgrade. If your branch is not maintained
|
|
anymore, you're definitely very late and will have to consider an upgrade
|
|
to a more recent branch (carefully read the README when doing so).
|
|
|
|
HAProxy will have to be updated according to the source it came from. Usually it
|
|
follows the system vendor's way of upgrading a package. If it was taken from
|
|
sources, please read the README file in the sources directory after extracting
|
|
the sources and follow the instructions for your operating system.
|
|
|
|
|
|
4. Companion products and alternatives
|
|
--------------------------------------
|
|
|
|
HAProxy integrates fairly well with certain products listed below, which is why
|
|
they are mentioned here even if not directly related to HAProxy.
|
|
|
|
|
|
4.1. Apache HTTP server
|
|
-----------------------
|
|
|
|
Apache is the de-facto standard HTTP server. It's a very complete and modular
|
|
project supporting both file serving and dynamic contents. It can serve as a
|
|
frontend for some application servers. It can even proxy requests and cache
|
|
responses. In all of these use cases, a front load balancer is commonly needed.
|
|
Apache can work in various modes, some being heavier than others. Certain
|
|
modules still require the heavier pre-forked model and will prevent Apache from
|
|
scaling well with a high number of connections. In this case HAProxy can provide
|
|
a tremendous help by enforcing the per-server connection limits to a safe value
|
|
and will significantly speed up the server and preserve its resources that will
|
|
be better used by the application.
|
|
|
|
Apache can extract the client's address from the X-Forwarded-For header by using
|
|
the "mod_rpaf" extension. HAProxy will automatically feed this header when
|
|
"option forwardfor" is specified in its configuration. HAProxy may also offer a
|
|
nice protection to Apache when exposed to the internet, where it will better
|
|
resist a wide number of types of DoS attacks.
|
|
|
|
|
|
4.2. NGINX
|
|
----------
|
|
|
|
NGINX is the second de-facto standard HTTP server. Just like Apache, it covers a
|
|
wide range of features. NGINX is built on a similar model as HAProxy so it has
|
|
no problem dealing with tens of thousands of concurrent connections. When used
|
|
as a gateway to some applications (e.g. using the included PHP FPM) it can often
|
|
be beneficial to set up some frontend connection limiting to reduce the load
|
|
on the PHP application. HAProxy will clearly be useful there both as a regular
|
|
load balancer and as the traffic regulator to speed up PHP by decongesting
|
|
it. Also since both products use very little CPU thanks to their event-driven
|
|
architecture, it's often easy to install both of them on the same system. NGINX
|
|
implements HAProxy's PROXY protocol, thus it is easy for HAProxy to pass the
|
|
client's connection information to NGINX so that the application gets all the
|
|
relevant information. Some benchmarks have also shown that for large static
|
|
file serving, implementing consistent hash on HAProxy in front of NGINX can be
|
|
beneficial by optimizing the OS' cache hit ratio, which is basically multiplied
|
|
by the number of server nodes.
|
|
|
|
|
|
4.3. Varnish
|
|
------------
|
|
|
|
Varnish is a smart caching reverse-proxy, probably best described as a web
|
|
application accelerator. Varnish doesn't implement SSL/TLS and wants to dedicate
|
|
all of its CPU cycles to what it does best. Varnish also implements HAProxy's
|
|
PROXY protocol so that HAProxy can very easily be deployed in front of Varnish
|
|
as an SSL offloader as well as a load balancer and pass it all relevant client
|
|
information. Also, Varnish naturally supports decompression from the cache when
|
|
a server has provided a compressed object, but doesn't compress however. HAProxy
|
|
can then be used to compress outgoing data when backend servers do not implement
|
|
compression, though it's rarely a good idea to compress on the load balancer
|
|
unless the traffic is low.
|
|
|
|
When building large caching farms across multiple nodes, HAProxy can make use of
|
|
consistent URL hashing to intelligently distribute the load to the caching nodes
|
|
and avoid cache duplication, resulting in a total cache size which is the sum of
|
|
all caching nodes.
|
|
|
|
|
|
4.4. Alternatives
|
|
-----------------
|
|
|
|
Linux Virtual Server (LVS or IPVS) is the layer 4 load balancer included within
|
|
the Linux kernel. It works at the packet level and handles TCP and UDP. In most
|
|
cases it's more a complement than an alternative since it doesn't have layer 7
|
|
knowledge at all.
|
|
|
|
Pound is another well-known load balancer. It's much simpler and has much less
|
|
features than HAProxy but for many very basic setups both can be used. Its
|
|
author has always focused on code auditability first and wants to maintain the
|
|
set of features low. Its thread-based architecture scales less well with high
|
|
connection counts, but it's a good product.
|
|
|
|
Pen is a quite light load balancer. It supports SSL, maintains persistence using
|
|
a fixed-size table of its clients' IP addresses. It supports a packet-oriented
|
|
mode allowing it to support direct server return and UDP to some extents. It is
|
|
meant for small loads (the persistence table only has 2048 entries).
|
|
|
|
NGINX can do some load balancing to some extents, though it's clearly not its
|
|
primary function. Production traffic is used to detect server failures, the
|
|
load balancing algorithms are more limited, and the stickiness is very limited.
|
|
But it can make sense in some simple deployment scenarios where it is already
|
|
present. The good thing is that since it integrates very well with HAProxy,
|
|
there's nothing wrong with adding HAProxy later when its limits have been
|
|
reached.
|
|
|
|
Varnish also does some load balancing of its backend servers and does support
|
|
real health checks. It doesn't implement stickiness however, so just like with
|
|
NGINX, as long as stickiness is not needed that can be enough to start with.
|
|
And similarly, since HAProxy and Varnish integrate so well together, it's easy
|
|
to add it later into the mix to complement the feature set.
|
|
|