Clicking on a rule, either the name or the expression, opens the rule
result (or the corresponding expression, repsectively) in the
expression browser. This should by default happen in the console tab,
as, more often than not, displaying it in the graph tab runs into a
timeout.
* Move fingerprint to Hash()
* Move away from tsdb.MultiError
* 0777 -> 0666 for files
* checkOverflow of extra fields
Signed-off-by: Goutham Veeramachaneni <cs14btech11014@iith.ac.in>
Usually rules don't more around, and if they do it's likely
that rules/alerts with the same name stay in the same order.
If rules/alerts with the same name are added/removed this
could cause a blip for one cycle, but this is unavoidable
without requiring rule and alert names to be unique - which we don't
want to do.
In case the execution of all rules takes longer than the configured rule
evaluation interval, one or more iterations will be skipped. This needs
to be visible to the opterator.
This is based on https://github.com/prometheus/prometheus/pull/1997.
This adds contexts to the relevant Storage methods and already passes
PromQL's new per-query context into the storage's query methods.
The immediate motivation supporting multi-tenancy in Frankenstein, but
this could also be used by Prometheus's normal local storage to support
cancellations and timeouts at some point.
For Weaveworks' Frankenstein, we need to support multitenancy. In
Frankenstein, we initially solved this without modifying the promql
package at all: we constructed a new promql.Engine for every
query and injected a storage implementation into that engine which would
be primed to only collect data for a given user.
This is problematic to upstream, however. Prometheus assumes that there
is only one engine: the query concurrency gate is part of the engine,
and the engine contains one central cancellable context to shut down all
queries. Also, creating a new engine for every query seems like overkill.
Thus, we want to be able to pass per-query contexts into a single engine.
This change gets rid of the promql.Engine's built-in base context and
allows passing in a per-query context instead. Central cancellation of
all queries is still possible by deriving all passed-in contexts from
one central one, but this is now the responsibility of the caller. The
central query context is now created in main() and passed into the
relevant components (web handler / API, rule manager).
In a next step, the per-query context would have to be passed to the
storage implementation, so that the storage can implement multi-tenancy
or other features based on the contextual information.
So far, out-of-order samples during rule evaluation were not logged,
and neither scrape health samples. The latter are unlikely to cause
any errors. That's why I'm logging them always now. (It's alway highly
irregular should it happen.) For rules, I have used the same plumbing
as for samples, just with a different wording in the message to mark
them as a result of rule evaluation.
This considers static labels in the equality of alerts to
avoid falsely copying state from a different alert definition with
the same name across reloads.
To be safe, it also copies the state map rather than just its pointer
so that remaining collisions disappear after one evaluation interval.
This gives up on the idea to communicate throuh the Append() call (by
either not returning as it is now or returning an error as
suggested/explored elsewhere). Here I have added a Throttled() call,
which has the advantage that it can be called before a whole _batch_
of Append()'s. Scrapes will happen completely or not at all. Same for
rule group evaluations. That's a highly desired behavior (as discussed
elsewhere). The code is even simpler now as the whole ingestion buffer
could be removed.
Logging of throttled mode has been streamlined and will create at most
one message per minute.
When an evaluation group runs initially, it waits a deterministic
amount of time. During that time it also has to accept
a termination singnal so shutdown doesn't hang during the first
evaluation iteration after a configuration reload.
Fixes#1307
This is with `golint -min_confidence=0.5`.
I left several lint warnings untouched because they were either
incorrect or I felt it was better not to change them at the moment.
This moves the concern of resolving the files relative to the config
file into the configuration loading itself.
It also fixes#921 which did not load the cert and token files relatively.
Besides fixing https://github.com/prometheus/prometheus/issues/805 by
making the entire externally reachable server URL configurable, this
adds tests for the "globalURL" template function and makes it easier to
test other such functions in the future.
This breaks the `web.Hostname` flag (and introduces `web.external-url`).
This flag is likely only used by few users, so I hope that's
justifiable.
Fixes https://github.com/prometheus/prometheus/issues/805
This change is conceptually very simple, although the diff is large. It
switches logging from "github.com/golang/glog" to
"github.com/prometheus/log", while not actually changing any log
messages. V(1)-style logging has been changed to be log.Debug*().
With this commit, sending SIGHUP to the Prometheus process will reload
and apply the configuration file. The different components attempt
to handle failing changes gracefully.
This commits renames the RuleManager to Manager as the package
name is 'rules' now. The unused layer of abstraction of the
RuleManager interface is removed.
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
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
The ConsoleLinkForExpression() function now escapes console URLs in such a way
that works both in emails and in HTML.
Change-Id: I917bae0b526cbbac28ccd2a4ec3c5ac03ee4c647
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.
This commit adds telemetry for the Prometheus expression rule
evaluator, which will enable meta-Prometheus monitoring of customers
to ensure that no instance is falling behind in answering routine
queries.
A few other sundry simplifications are introduced, too.
Fabian Reinartz