Move rulemanager to it's own package to break cicrular dependency.
Make NewTestTieredStorage available to tests, remove duplication.
Change-Id: I33b321245a44aa727bfc3614a7c9ae5005b34e03
This was initially motivated by wanting to distribute the rule checker
tool under `tools/rule_checker`. However, this was not possible without
also distributing the LevelDB dynamic libraries because the tool
transitively depended on Levigo:
rule checker -> query layer -> tiered storage layer -> leveldb
This change separates external storage interfaces from the
implementation (tiered storage, leveldb storage, memory storage) by
putting them into separate packages:
- storage/metric: public, implementation-agnostic interfaces
- storage/metric/tiered: tiered storage implementation, including memory
and LevelDB storage.
I initially also considered splitting up the implementation into
separate packages for tiered storage, memory storage, and LevelDB
storage, but these are currently so intertwined that it would be another
major project in itself.
The query layers and most other parts of Prometheus now have notion of
the storage implementation anymore and just use whatever implementation
they get passed in via interfaces.
The rule_checker is now a static binary :)
Change-Id: I793bbf631a8648ca31790e7e772ecf9c2b92f7a0
The closing of Prometheus now using a sync.Once wrapper to prevent
any accidental multiple invocations of it, which could trigger
corruption or a race condition. The shutdown process is made more
verbose through logging.
A not-enabled by default web handler has been provided to trigger a
remote shutdown if requested for debugging purposes.
Change-Id: If4fee75196bbff1fb1e4a4ef7e1cfa53fef88f2e
The idiomatic pattern for signalling a one-time message to multiple
consumers from a single producer is as follows:
```
c := make(chan struct{})
w := new(sync.WaitGroup) // Boilerplate to ensure synchronization.
for i := 0; i < 1000; i++ {
w.Add(1)
go func() {
defer w.Done()
for {
select {
case _, ok := <- c:
if !ok {
return
}
default:
// Do something here.
}
}
}()
}
close(c) // Signal the one-to-many single-use message.
w.Wait()
```
Change-Id: I755f73ba4c70a923afd342a4dea63365bdf2144b
Idiomatic semaphore usage in Go, unless it is wrapping a concrete type,
should use anonymous empty structs (``struct{}``). This has several
features that are worthwhile:
1. It conveys that the object in the channel is likely used for
resource limiting / semaphore use. This is by idiom.
2. Due to magic under the hood, empty structs have a width of zero,
meaning they consume little space. It is presumed that slices,
channels, and other values of them can be represented specially
with alternative optimizations. Dmitry Vyukov has done
investigations into improvements that can be made to the channel
design and Go and concludes that there are already nice short
circuiting behaviors at work with this type.
This is the first change of several that apply this type of change to
suitable places.
In this one change, we fix a bug in the previous revision, whereby a
semaphore can be acquired for curation and never released back for
subsequent work: http://goo.gl/70Y2qK. Compare that versus the
compaction definition above.
On top of that, the use of the semaphore in the mode better supports
system shutdown idioms through the closing of channels.
Change-Id: Idb4fca310f26b73c9ec690bbdd4136180d14c32d
Prometheus needs long-term storage. Since we don't have enough resources
to build our own timeseries storage from scratch ontop of Riak,
Cassandra or a similar distributed datastore at the moment, we're
planning on using OpenTSDB as long-term storage for Prometheus. It's
data model is roughly compatible with that of Prometheus, with some
caveats.
As a first step, this adds write-only replication from Prometheus to
OpenTSDB, with the following things worth noting:
1)
I tried to keep the integration lightweight, meaning that anything
related to OpenTSDB is isolated to its own package and only main knows
about it (essentially it tees all samples to both the existing storage
and TSDB). It's not touching the existing TieredStorage at all to avoid
more complexity in that area. This might change in the future,
especially if we decide to implement a read path for OpenTSDB through
Prometheus as well.
2)
Backpressure while sending to OpenTSDB is handled by simply dropping
samples on the floor when the in-memory queue of samples destined for
OpenTSDB runs full. Prometheus also only attempts to send samples once,
rather than implementing a complex retry algorithm. Thus, replication to
OpenTSDB is best-effort for now. If needed, this may be extended in the
future.
3)
Samples are sent in batches of limited size to OpenTSDB. The optimal
batch size, timeout parameters, etc. may need to be adjusted in the
future.
4)
OpenTSDB has different rules for legal characters in tag (label) values.
While Prometheus allows any characters in label values, OpenTSDB limits
them to a to z, A to Z, 0 to 9, -, _, . and /. Currently any illegal
characters in Prometheus label values are simply replaced by an
underscore. Especially when integrating OpenTSDB with the read path in
Prometheus, we'll need to reconsider this: either we'll need to
introduce the same limitations for Prometheus labels or escape/encode
illegal characters in OpenTSDB in such a way that they are fully
decodable again when reading through Prometheus, so that corresponding
timeseries in both systems match in their labelsets.
Change-Id: I8394c9c55dbac3946a0fa497f566d5e6e2d600b5
So far we've been using Go's native time.Time for anything related to sample
timestamps. Since the range of time.Time is much bigger than what we need, this
has created two problems:
- there could be time.Time values which were out of the range/precision of the
time type that we persist to disk, therefore causing incorrectly ordered keys.
One bug caused by this was:
https://github.com/prometheus/prometheus/issues/367
It would be good to use a timestamp type that's more closely aligned with
what the underlying storage supports.
- sizeof(time.Time) is 192, while Prometheus should be ok with a single 64-bit
Unix timestamp (possibly even a 32-bit one). Since we store samples in large
numbers, this seriously affects memory usage. Furthermore, copying/working
with the data will be faster if it's smaller.
*MEMORY USAGE RESULTS*
Initial memory usage comparisons for a running Prometheus with 1 timeseries and
100,000 samples show roughly a 13% decrease in total (VIRT) memory usage. In my
tests, this advantage for some reason decreased a bit the more samples the
timeseries had (to 5-7% for millions of samples). This I can't fully explain,
but perhaps garbage collection issues were involved.
*WHEN TO USE THE NEW TIMESTAMP TYPE*
The new clientmodel.Timestamp type should be used whenever time
calculations are either directly or indirectly related to sample
timestamps.
For example:
- the timestamp of a sample itself
- all kinds of watermarks
- anything that may become or is compared to a sample timestamp (like the timestamp
passed into Target.Scrape()).
When to still use time.Time:
- for measuring durations/times not related to sample timestamps, like duration
telemetry exporting, timers that indicate how frequently to execute some
action, etc.
*NOTE ON OPERATOR OPTIMIZATION TESTS*
We don't use operator optimization code anymore, but it still lives in
the code as dead code. It still has tests, but I couldn't get all of them to
pass with the new timestamp format. I commented out the failing cases for now,
but we should probably remove the dead code soon. I just didn't want to do that
in the same change as this.
Change-Id: I821787414b0debe85c9fffaeb57abd453727af0f
This commit fixes a critique of the old storage API design, whereby
the input parameters were always as raw bytes and never Protocol
Buffer messages that encapsulated the data, meaning every place a
read or mutation was conducted needed to manually perform said
translations on its own. This is taxing.
Change-Id: I4786938d0d207cefb7782bd2bd96a517eead186f
The background curation should be staggered to ensure that disk
I/O yields to user-interactive operations in a timely manner. The
lack of routine prioritization necessitates this.
Change-Id: I9b498a74ccd933ffb856e06fedc167430e521d86
Curation is an expensive process. We can perform it less frequently;
and in the case of compaction processors, we can afford to let them
group more together.
Change-Id: I421e27958ed7a98dfacaababefad19462772b6a3
The ConsoleLinkForExpression() function now escapes console URLs in such a way
that works both in emails and in HTML.
Change-Id: I917bae0b526cbbac28ccd2a4ec3c5ac03ee4c647
Again, playing around.
Change-Id: I5413f7723a38ae18792802c5ed91753101adf491
Moving order of arguments by priority.
Testing out patch sets.
Change-Id: I5413f7723a38ae18792802c5ed91753101adf491
This includes required refactorings to enable replacing the http client (for
testing) and moving the NotificationReq type definitions to the "notifications"
package, so that this package doesn't need to depend on "rules" anymore and
that it can instead use a representation of the required data which only
includes the necessary fields.
In order to help corroborate whether a Prometheus instance has
flapped until meta-monitoring is in-place, we ought to provide the
instance's start time in the console to aid in diagnostics.
This commit simplifies the way that compactions across a database's
keyspace occur due to reading the LevelDB internals. Secondarily it
introduces the database size estimation mechanisms.
Include database health and help interfaces.
Add database statistics; remove status goroutines.
This commit kills the use of Go routines to expose status throughout
the web components of Prometheus. It also dumps raw LevelDB status
on a separate /databases endpoint.
This commit introduces the long-tail deletion mechanism, which will
automatically cull old sample values. It is an acceptable
hold-over until we get a resampling pipeline implemented.
Kill legacy OS X documentation, too.
This does two things:
1) Make TieredStorage.AppendSamples() write directly to memory instead of
buffering to a channel first. This is needed in cases where a rule might
immediately need the data generated by a previous rule.
2) Replace the single storage mutex by two new ones:
- memoryMutex - needs to be locked at any time that two concurrent
goroutines could be accessing (via read or write) the
TieredStorage memoryArena.
- memoryDeleteMutex - used to prevent any deletion of samples from
memoryArena as long as renderView is running and
assembling data from it.
The LevelDB disk storage does not need to be protected by a mutex when
rendering a view since renderView works off a LevelDB snapshot.
The rationale against adding memoryMutex directly to the memory storage: taking
a mutex does come with a small inherent time cost, and taking it is only
required in few places. In fact, no locking is required for the memory storage
instance which is part of a view (and not the TieredStorage).
