Add unit tests for Web API's query endpoint (GET/POST).
Also modify the endpoint handler to use context.WithDeadline instead of
context.WithTimeout, so the deadline is deterministic for the tests.
Signed-off-by: Arve Knudsen <arve.knudsen@gmail.com>
Return annotations (warnings and infos) from PromQL queries
This generalizes the warnings we have already used before (but only for problems with remote read) as "annotations".
Annotations can be warnings or infos (the latter could be false positives). We do not treat them different in the API for now and return them all as "warnings". It would be easy to distinguish them and return infos separately, should that appear useful in the future.
The new annotations are then used to create a lot of warnings or infos during PromQL evaluations. Partially these are things we have wanted for a long time (e.g. inform the user that they have applied `rate` to a metric that doesn't look like a counter), but the new native histograms have created even more needs for those annotations (e.g. if a query tries to aggregate float numbers with histograms).
The annotations added here are not yet complete. A prominent example would be a warning about a range too short for a rate calculation. But such a warnings is more tricky to create with good fidelity and we will tackle it later.
Another TODO is to take annotations into account when evaluating recording rules.
---------
Signed-off-by: Jeanette Tan <jeanette.tan@grafana.com>
It's possible (quite common on Kubernetes) to have a service discovery
return thousands of targets then drop most of them in relabel rules.
The main place this data is used is to display in the web UI, where
you don't want thousands of lines of display.
The new limit is `keep_dropped_targets`, which defaults to 0
for backwards-compatibility.
Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
* Add OTLP Ingestion endpoint
We copy files from the otel-collector-contrib. See the README in
`storage/remote/otlptranslator/README.md`.
This supersedes: https://github.com/prometheus/prometheus/pull/11965
Signed-off-by: gouthamve <gouthamve@gmail.com>
* Return a 200 OK
It is what the OTEL Golang SDK expect :(
https://github.com/open-telemetry/opentelemetry-go/issues/4363
Signed-off-by: Goutham <gouthamve@gmail.com>
---------
Signed-off-by: gouthamve <gouthamve@gmail.com>
Signed-off-by: Goutham <gouthamve@gmail.com>
Convert QueryOpts to an interface so that downstream projects like
https://github.com/thanos-community/promql-engine could extend the query
options with engine specific options that are not in the original
engine.
Will be used to enable query analysis per-query.
Signed-off-by: Giedrius Statkevičius <giedrius.statkevicius@vinted.com>
Wiser coders than myself have come to the conclusion that a `switch`
statement is almost always superior to a statement that includes any
`else if`.
The exceptions that I have found in our codebase are just these two:
* The `if else` is followed by an additional statement before the next
condition (separated by a `;`).
* The whole thing is within a `for` loop and `break` statements are
used. In this case, using `switch` would require tagging the `for`
loop, which probably tips the balance.
Why are `switch` statements more readable?
For one, fewer curly braces. But more importantly, the conditions all
have the same alignment, so the whole thing follows the natural flow
of going down a list of conditions. With `else if`, in contrast, all
conditions but the first are "hidden" behind `} else if `, harder to
spot and (for no good reason) presented differently from the first
condition.
I'm sure the aforemention wise coders can list even more reasons.
In any case, I like it so much that I have found myself recommending
it in code reviews. I would like to make it a habit in our code base,
without making it a hard requirement that we would test on the CI. But
for that, there has to be a role model, so this commit eliminates all
`if else` occurrences, unless it is autogenerated code or fits one of
the exceptions above.
Signed-off-by: beorn7 <beorn@grafana.com>
We haven't updated golint-ci in our CI yet, but this commit prepares
for that.
There are a lot of new warnings, and it is mostly because the "revive"
linter got updated. I agree with most of the new warnings, mostly
around not naming unused function parameters (although it is justified
in some cases for documentation purposes – while things like mocks are
a good example where not naming the parameter is clearer).
I'm pretty upset about the "empty block" warning to include `for`
loops. It's such a common pattern to do something in the head of the
`for` loop and then have an empty block. There is still an open issue
about this: https://github.com/mgechev/revive/issues/810 I have
disabled "revive" altogether in files where empty blocks are used
excessively, and I have made the effort to add individual
`// nolint:revive` where empty blocks are used just once or twice.
It's borderline noisy, though, but let's go with it for now.
I should mention that none of the "empty block" warnings for `for`
loop bodies were legitimate.
Signed-off-by: beorn7 <beorn@grafana.com>
Introduces support for a new query parameter in the `/rules` API endpoint that allows filtering by rule names.
If all the rules of a group are filtered, we skip the group entirely.
Signed-off-by: gotjosh <josue.abreu@gmail.com>
In other words: Instead of having a “polymorphous” `Point` that can
either contain a float value or a histogram value, use an `FPoint` for
floats and an `HPoint` for histograms.
This seemingly small change has a _lot_ of repercussions throughout
the codebase.
The idea here is to avoid the increase in size of `Point` arrays that
happened after native histograms had been added.
The higher-level data structures (`Sample`, `Series`, etc.) are still
“polymorphous”. The same idea could be applied to them, but at each
step the trade-offs needed to be evaluated.
The idea with this change is to do the minimum necessary to get back
to pre-histogram performance for functions that do not touch
histograms. Here are comparisons for the `changes` function. The test
data doesn't include histograms yet. Ideally, there would be no change
in the benchmark result at all.
First runtime v2.39 compared to directly prior to this commit:
```
name old time/op new time/op delta
RangeQuery/expr=changes(a_one[1d]),steps=1-16 391µs ± 2% 542µs ± 1% +38.58% (p=0.000 n=9+8)
RangeQuery/expr=changes(a_one[1d]),steps=10-16 452µs ± 2% 617µs ± 2% +36.48% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_one[1d]),steps=100-16 1.12ms ± 1% 1.36ms ± 2% +21.58% (p=0.000 n=8+10)
RangeQuery/expr=changes(a_one[1d]),steps=1000-16 7.83ms ± 1% 8.94ms ± 1% +14.21% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_ten[1d]),steps=1-16 2.98ms ± 0% 3.30ms ± 1% +10.67% (p=0.000 n=9+10)
RangeQuery/expr=changes(a_ten[1d]),steps=10-16 3.66ms ± 1% 4.10ms ± 1% +11.82% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_ten[1d]),steps=100-16 10.5ms ± 0% 11.8ms ± 1% +12.50% (p=0.000 n=8+10)
RangeQuery/expr=changes(a_ten[1d]),steps=1000-16 77.6ms ± 1% 87.4ms ± 1% +12.63% (p=0.000 n=9+9)
RangeQuery/expr=changes(a_hundred[1d]),steps=1-16 30.4ms ± 2% 32.8ms ± 1% +8.01% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=10-16 37.1ms ± 2% 40.6ms ± 2% +9.64% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=100-16 105ms ± 1% 117ms ± 1% +11.69% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=1000-16 783ms ± 3% 876ms ± 1% +11.83% (p=0.000 n=9+10)
```
And then runtime v2.39 compared to after this commit:
```
name old time/op new time/op delta
RangeQuery/expr=changes(a_one[1d]),steps=1-16 391µs ± 2% 547µs ± 1% +39.84% (p=0.000 n=9+8)
RangeQuery/expr=changes(a_one[1d]),steps=10-16 452µs ± 2% 616µs ± 2% +36.15% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_one[1d]),steps=100-16 1.12ms ± 1% 1.26ms ± 1% +12.20% (p=0.000 n=8+10)
RangeQuery/expr=changes(a_one[1d]),steps=1000-16 7.83ms ± 1% 7.95ms ± 1% +1.59% (p=0.000 n=10+8)
RangeQuery/expr=changes(a_ten[1d]),steps=1-16 2.98ms ± 0% 3.38ms ± 2% +13.49% (p=0.000 n=9+10)
RangeQuery/expr=changes(a_ten[1d]),steps=10-16 3.66ms ± 1% 4.02ms ± 1% +9.80% (p=0.000 n=10+9)
RangeQuery/expr=changes(a_ten[1d]),steps=100-16 10.5ms ± 0% 10.8ms ± 1% +3.08% (p=0.000 n=8+10)
RangeQuery/expr=changes(a_ten[1d]),steps=1000-16 77.6ms ± 1% 78.1ms ± 1% +0.58% (p=0.035 n=9+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=1-16 30.4ms ± 2% 33.5ms ± 4% +10.18% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=10-16 37.1ms ± 2% 40.0ms ± 1% +7.98% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=100-16 105ms ± 1% 107ms ± 1% +1.92% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=1000-16 783ms ± 3% 775ms ± 1% -1.02% (p=0.019 n=9+9)
```
In summary, the runtime doesn't really improve with this change for
queries with just a few steps. For queries with many steps, this
commit essentially reinstates the old performance. This is good
because the many-step queries are the one that matter most (longest
absolute runtime).
In terms of allocations, though, this commit doesn't make a dent at
all (numbers not shown). The reason is that most of the allocations
happen in the sampleRingIterator (in the storage package), which has
to be addressed in a separate commit.
Signed-off-by: beorn7 <beorn@grafana.com>
This commit adds a new 'keep_firing_for' field to Prometheus alerting
rules. The 'resolve_delay' field specifies the minimum amount of time
that an alert should remain firing, even if the expression does not
return any results.
This feature was discussed at a previous dev summit, and it was
determined that a feature like this would be useful in order to allow
the expression time to stabilize and prevent confusing resolved messages
from being propagated through Alertmanager.
This approach is simpler than having two PromQL queries, as was
sometimes discussed, and it should be easy to implement.
This commit does not include tests for the 'resolve_delay' field. This
is intentional, as the purpose of this commit is to gather comments on
the proposed design of the 'resolve_delay' field before implementing
tests. Once the design of the 'resolve_delay' field has been finalized,
a follow-up commit will be submitted with tests."
See https://github.com/prometheus/prometheus/issues/11570
Signed-off-by: Julien Pivotto <roidelapluie@o11y.eu>
* Add API endpoints for getting scrape pool names
This adds api/v1/scrape_pools endpoint that returns the list of *names* of all the scrape pools configured.
Having it allows to find out what scrape pools are defined without having to list and parse all targets.
The second change is adding scrapePool query parameter support in api/v1/targets endpoint, that allows to
filter returned targets by only finding ones for passed scrape pool name.
Both changes allow to query for a specific scrape pool data, rather than getting all the targets for all possible scrape pools.
The problem with api/v1/targets endpoint is that it returns huge amount of data if you configure a lot of scrape pools.
Signed-off-by: Łukasz Mierzwa <l.mierzwa@gmail.com>
* Add a scrape pool selector on /targets page
Current targets page lists all possible targets. This works great if you only have a few scrape pools configured,
but for systems with a lot of scrape pools and targets this slow things down a lot.
Not only does the /targets page load very slowly in such case (waiting for huge API response) but it also take
a long time to render, due to huge number of elements.
This change adds a dropdown selector so it's possible to select only intersting scrape pool to view.
There's also scrapePool query param that will open selected pool automatically.
Signed-off-by: Łukasz Mierzwa <l.mierzwa@gmail.com>
Signed-off-by: Łukasz Mierzwa <l.mierzwa@gmail.com>
* wrap api error on get series/labels on `returnAPIError` function
Signed-off-by: Alan Protasio <approtas@amazon.com>
* lint
Signed-off-by: Alan Protasio <approtas@amazon.com>
* query exemplars
Signed-off-by: Alan Protasio <approtas@amazon.com>
Signed-off-by: Alan Protasio <approtas@amazon.com>
