|
|
|
|
load 5m
|
|
|
|
|
http_requests{job="api-server", instance="0", group="production"} 0+10x10
|
|
|
|
|
http_requests{job="api-server", instance="1", group="production"} 0+20x10
|
|
|
|
|
http_requests{job="api-server", instance="0", group="canary"} 0+30x10
|
|
|
|
|
http_requests{job="api-server", instance="1", group="canary"} 0+40x10
|
|
|
|
|
http_requests{job="app-server", instance="0", group="production"} 0+50x10
|
|
|
|
|
http_requests{job="app-server", instance="1", group="production"} 0+60x10
|
|
|
|
|
http_requests{job="app-server", instance="0", group="canary"} 0+70x10
|
|
|
|
|
http_requests{job="app-server", instance="1", group="canary"} 0+80x10
|
|
|
|
|
|
|
|
|
|
load 5m
|
|
|
|
|
vector_matching_a{l="x"} 0+1x100
|
|
|
|
|
vector_matching_a{l="y"} 0+2x50
|
|
|
|
|
vector_matching_b{l="x"} 0+4x25
|
|
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|
|
|
|
|
|
|
|
|
|
|
eval instant at 50m SUM(http_requests) BY (job) - COUNT(http_requests) BY (job)
|
|
|
|
|
{job="api-server"} 996
|
|
|
|
|
{job="app-server"} 2596
|
|
|
|
|
|
|
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|
|
eval instant at 50m 2 - SUM(http_requests) BY (job)
|
|
|
|
|
{job="api-server"} -998
|
|
|
|
|
{job="app-server"} -2598
|
|
|
|
|
|
Optimise PromQL (#3966)
* Move range logic to 'eval'
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make aggregegate range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* PromQL is statically typed, so don't eval to find the type.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Extend rangewrapper to multiple exprs
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Start making function evaluation ranged
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make instant queries a special case of range queries
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Eliminate evalString
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Evaluate range vector functions one series at a time
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make unary operators range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make binops range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Pass time to range-aware functions.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make simple _over_time functions range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Reduce allocs when working with matrix selectors
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Add basic benchmark for range evaluation
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Reuse objects for function arguments
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Do dropmetricname and allocating output vector only once.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Add range-aware support for range vector functions with params
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Optimise holt_winters, cut cpu and allocs by ~25%
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make rate&friends range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make more functions range aware. Document calling convention.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make date functions range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make simple math functions range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Convert more functions to be range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make more functions range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Specialcase timestamp() with vector selector arg for range awareness
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Remove transition code for functions
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Remove the rest of the engine transition code
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Remove more obselete code
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Remove the last uses of the eval* functions
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Remove engine finalizers to prevent corruption
The finalizers set by matrixSelector were being called
just before the value they were retruning to the pool
was then being provided to the caller. Thus a concurrent query
could corrupt the data that the user has just been returned.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Add new benchmark suite for range functinos
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Migrate existing benchmarks to new system
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Expand promql benchmarks
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Simply test by removing unused range code
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* When testing instant queries, check range queries too.
To protect against subsequent steps in a range query being
affected by the previous steps, add a test that evaluates
an instant query that we know works again as a range query
with the tiimestamp we care about not being the first step.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Reuse ring for matrix iters. Put query results back in pool.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Reuse buffer when iterating over matrix selectors
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Unary minus should remove metric name
Cut down benchmarks for faster runs.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Reduce repetition in benchmark test cases
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Work series by series when doing normal vectorSelectors
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Optimise benchmark setup, cuts time by 60%
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Have rangeWrapper use an evalNodeHelper to cache across steps
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Use evalNodeHelper with functions
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Cache dropMetricName within a node evaluation.
This saves both the calculations and allocs done by dropMetricName
across steps.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Reuse input vectors in rangewrapper
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Reuse the point slices in the matrixes input/output by rangeWrapper
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make benchmark setup faster using AddFast
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Simplify benchmark code.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Add caching in VectorBinop
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Use xor to have one-level resultMetric hash key
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Add more benchmarks
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Call Query.Close in apiv1
This allows point slices allocated for the response data
to be reused by later queries, saving allocations.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Optimise histogram_quantile
It's now 5-10% faster with 97% less garbage generated for 1k steps
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make the input collection in rangeVector linear rather than quadratic
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Optimise label_replace, for 1k steps 15x fewer allocs and 3x faster
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Optimise label_join, 1.8x faster and 11x less memory for 1k steps
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Expand benchmarks, cleanup comments, simplify numSteps logic.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Address Fabian's comments
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Comments from Alin.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Address jrv's comments
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Remove dead code
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Address Simon's comments.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Rename populateIterators, pre-init some sizes
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Handle case where function has non-matrix args first
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Split rangeWrapper out to rangeEval function, improve comments
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Cleanup and make things more consistent
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make EvalNodeHelper public
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Fabian's comments.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
7 years ago
|
|
|
eval instant at 50m -http_requests{job="api-server",instance="0",group="production"}
|
|
|
|
|
{job="api-server",instance="0",group="production"} -100
|
|
|
|
|
|
|
|
|
|
eval instant at 50m +http_requests{job="api-server",instance="0",group="production"}
|
|
|
|
|
http_requests{job="api-server",instance="0",group="production"} 100
|
|
|
|
|
|
|
|
|
|
eval instant at 50m - - - SUM(http_requests) BY (job)
|
|
|
|
|
{job="api-server"} -1000
|
|
|
|
|
{job="app-server"} -2600
|
|
|
|
|
|
|
|
|
|
eval instant at 50m - - - 1
|
|
|
|
|
-1
|
|
|
|
|
|
|
|
|
|
eval instant at 50m 1000 / SUM(http_requests) BY (job)
|
|
|
|
|
{job="api-server"} 1
|
|
|
|
|
{job="app-server"} 0.38461538461538464
|
|
|
|
|
|
|
|
|
|
eval instant at 50m SUM(http_requests) BY (job) - 2
|
|
|
|
|
{job="api-server"} 998
|
|
|
|
|
{job="app-server"} 2598
|
|
|
|
|
|
|
|
|
|
eval instant at 50m SUM(http_requests) BY (job) % 3
|
|
|
|
|
{job="api-server"} 1
|
|
|
|
|
{job="app-server"} 2
|
|
|
|
|
|
|
|
|
|
eval instant at 50m SUM(http_requests) BY (job) % 0.3
|
|
|
|
|
{job="api-server"} 0.1
|
|
|
|
|
{job="app-server"} 0.2
|
|
|
|
|
|
|
|
|
|
eval instant at 50m SUM(http_requests) BY (job) ^ 2
|
|
|
|
|
{job="api-server"} 1000000
|
|
|
|
|
{job="app-server"} 6760000
|
|
|
|
|
|
|
|
|
|
eval instant at 50m SUM(http_requests) BY (job) % 3 ^ 2
|
|
|
|
|
{job="api-server"} 1
|
|
|
|
|
{job="app-server"} 8
|
|
|
|
|
|
|
|
|
|
eval instant at 50m SUM(http_requests) BY (job) % 2 ^ (3 ^ 2)
|
|
|
|
|
{job="api-server"} 488
|
|
|
|
|
{job="app-server"} 40
|
|
|
|
|
|
|
|
|
|
eval instant at 50m SUM(http_requests) BY (job) % 2 ^ 3 ^ 2
|
|
|
|
|
{job="api-server"} 488
|
|
|
|
|
{job="app-server"} 40
|
|
|
|
|
|
|
|
|
|
eval instant at 50m SUM(http_requests) BY (job) % 2 ^ 3 ^ 2 ^ 2
|
|
|
|
|
{job="api-server"} 1000
|
|
|
|
|
{job="app-server"} 2600
|
|
|
|
|
|
|
|
|
|
eval instant at 50m COUNT(http_requests) BY (job) ^ COUNT(http_requests) BY (job)
|
|
|
|
|
{job="api-server"} 256
|
|
|
|
|
{job="app-server"} 256
|
|
|
|
|
|
|
|
|
|
eval instant at 50m SUM(http_requests) BY (job) / 0
|
|
|
|
|
{job="api-server"} +Inf
|
|
|
|
|
{job="app-server"} +Inf
|
|
|
|
|
|
|
|
|
|
eval instant at 50m SUM(http_requests) BY (job) + SUM(http_requests) BY (job)
|
|
|
|
|
{job="api-server"} 2000
|
|
|
|
|
{job="app-server"} 5200
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
eval instant at 50m http_requests{job="api-server", group="canary"}
|
|
|
|
|
http_requests{group="canary", instance="0", job="api-server"} 300
|
|
|
|
|
http_requests{group="canary", instance="1", job="api-server"} 400
|
|
|
|
|
|
|
|
|
|
eval instant at 50m http_requests{job="api-server", group="canary"} + rate(http_requests{job="api-server"}[5m]) * 5 * 60
|
|
|
|
|
{group="canary", instance="0", job="api-server"} 330
|
|
|
|
|
{group="canary", instance="1", job="api-server"} 440
|
|
|
|
|
|
|
|
|
|
eval instant at 50m rate(http_requests[25m]) * 25 * 60
|
|
|
|
|
{group="canary", instance="0", job="api-server"} 150
|
|
|
|
|
{group="canary", instance="0", job="app-server"} 350
|
|
|
|
|
{group="canary", instance="1", job="api-server"} 200
|
|
|
|
|
{group="canary", instance="1", job="app-server"} 400
|
|
|
|
|
{group="production", instance="0", job="api-server"} 50
|
|
|
|
|
{group="production", instance="0", job="app-server"} 249.99999999999997
|
|
|
|
|
{group="production", instance="1", job="api-server"} 100
|
|
|
|
|
{group="production", instance="1", job="app-server"} 300
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
eval instant at 50m http_requests{group="canary"} and http_requests{instance="0"}
|
|
|
|
|
http_requests{group="canary", instance="0", job="api-server"} 300
|
|
|
|
|
http_requests{group="canary", instance="0", job="app-server"} 700
|
|
|
|
|
|
|
|
|
|
eval instant at 50m (http_requests{group="canary"} + 1) and http_requests{instance="0"}
|
|
|
|
|
{group="canary", instance="0", job="api-server"} 301
|
|
|
|
|
{group="canary", instance="0", job="app-server"} 701
|
|
|
|
|
|
|
|
|
|
eval instant at 50m (http_requests{group="canary"} + 1) and on(instance, job) http_requests{instance="0", group="production"}
|
|
|
|
|
{group="canary", instance="0", job="api-server"} 301
|
|
|
|
|
{group="canary", instance="0", job="app-server"} 701
|
|
|
|
|
|
|
|
|
|
eval instant at 50m (http_requests{group="canary"} + 1) and on(instance) http_requests{instance="0", group="production"}
|
|
|
|
|
{group="canary", instance="0", job="api-server"} 301
|
|
|
|
|
{group="canary", instance="0", job="app-server"} 701
|
|
|
|
|
|
|
|
|
|
eval instant at 50m (http_requests{group="canary"} + 1) and ignoring(group) http_requests{instance="0", group="production"}
|
|
|
|
|
{group="canary", instance="0", job="api-server"} 301
|
|
|
|
|
{group="canary", instance="0", job="app-server"} 701
|
|
|
|
|
|
|
|
|
|
eval instant at 50m (http_requests{group="canary"} + 1) and ignoring(group, job) http_requests{instance="0", group="production"}
|
|
|
|
|
{group="canary", instance="0", job="api-server"} 301
|
|
|
|
|
{group="canary", instance="0", job="app-server"} 701
|
|
|
|
|
|
|
|
|
|
eval instant at 50m http_requests{group="canary"} or http_requests{group="production"}
|
|
|
|
|
http_requests{group="canary", instance="0", job="api-server"} 300
|
|
|
|
|
http_requests{group="canary", instance="0", job="app-server"} 700
|
|
|
|
|
http_requests{group="canary", instance="1", job="api-server"} 400
|
|
|
|
|
http_requests{group="canary", instance="1", job="app-server"} 800
|
|
|
|
|
http_requests{group="production", instance="0", job="api-server"} 100
|
|
|
|
|
http_requests{group="production", instance="0", job="app-server"} 500
|
|
|
|
|
http_requests{group="production", instance="1", job="api-server"} 200
|
|
|
|
|
http_requests{group="production", instance="1", job="app-server"} 600
|
|
|
|
|
|
|
|
|
|
# On overlap the rhs samples must be dropped.
|
|
|
|
|
eval instant at 50m (http_requests{group="canary"} + 1) or http_requests{instance="1"}
|
|
|
|
|
{group="canary", instance="0", job="api-server"} 301
|
|
|
|
|
{group="canary", instance="0", job="app-server"} 701
|
|
|
|
|
{group="canary", instance="1", job="api-server"} 401
|
|
|
|
|
{group="canary", instance="1", job="app-server"} 801
|
|
|
|
|
http_requests{group="production", instance="1", job="api-server"} 200
|
|
|
|
|
http_requests{group="production", instance="1", job="app-server"} 600
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
# Matching only on instance excludes everything that has instance=0/1 but includes
|
|
|
|
|
# entries without the instance label.
|
|
|
|
|
eval instant at 50m (http_requests{group="canary"} + 1) or on(instance) (http_requests or cpu_count or vector_matching_a)
|
|
|
|
|
{group="canary", instance="0", job="api-server"} 301
|
|
|
|
|
{group="canary", instance="0", job="app-server"} 701
|
|
|
|
|
{group="canary", instance="1", job="api-server"} 401
|
|
|
|
|
{group="canary", instance="1", job="app-server"} 801
|
|
|
|
|
vector_matching_a{l="x"} 10
|
|
|
|
|
vector_matching_a{l="y"} 20
|
|
|
|
|
|
|
|
|
|
eval instant at 50m (http_requests{group="canary"} + 1) or ignoring(l, group, job) (http_requests or cpu_count or vector_matching_a)
|
|
|
|
|
{group="canary", instance="0", job="api-server"} 301
|
|
|
|
|
{group="canary", instance="0", job="app-server"} 701
|
|
|
|
|
{group="canary", instance="1", job="api-server"} 401
|
|
|
|
|
{group="canary", instance="1", job="app-server"} 801
|
|
|
|
|
vector_matching_a{l="x"} 10
|
|
|
|
|
vector_matching_a{l="y"} 20
|
|
|
|
|
|
|
|
|
|
eval instant at 50m http_requests{group="canary"} unless http_requests{instance="0"}
|
|
|
|
|
http_requests{group="canary", instance="1", job="api-server"} 400
|
|
|
|
|
http_requests{group="canary", instance="1", job="app-server"} 800
|
|
|
|
|
|
|
|
|
|
eval instant at 50m http_requests{group="canary"} unless on(job) http_requests{instance="0"}
|
|
|
|
|
|
|
|
|
|
eval instant at 50m http_requests{group="canary"} unless on(job, instance) http_requests{instance="0"}
|
|
|
|
|
http_requests{group="canary", instance="1", job="api-server"} 400
|
|
|
|
|
http_requests{group="canary", instance="1", job="app-server"} 800
|
|
|
|
|
|
|
|
|
|
eval instant at 50m http_requests{group="canary"} / on(instance,job) http_requests{group="production"}
|
|
|
|
|
{instance="0", job="api-server"} 3
|
|
|
|
|
{instance="0", job="app-server"} 1.4
|
|
|
|
|
{instance="1", job="api-server"} 2
|
|
|
|
|
{instance="1", job="app-server"} 1.3333333333333333
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eval instant at 50m http_requests{group="canary"} unless ignoring(group, instance) http_requests{instance="0"}
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eval instant at 50m http_requests{group="canary"} unless ignoring(group) http_requests{instance="0"}
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http_requests{group="canary", instance="1", job="api-server"} 400
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http_requests{group="canary", instance="1", job="app-server"} 800
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eval instant at 50m http_requests{group="canary"} / ignoring(group) http_requests{group="production"}
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{instance="0", job="api-server"} 3
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{instance="0", job="app-server"} 1.4
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{instance="1", job="api-server"} 2
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{instance="1", job="app-server"} 1.3333333333333333
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# https://github.com/prometheus/prometheus/issues/1489
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eval instant at 50m http_requests AND ON (dummy) vector(1)
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http_requests{group="canary", instance="0", job="api-server"} 300
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http_requests{group="canary", instance="0", job="app-server"} 700
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http_requests{group="canary", instance="1", job="api-server"} 400
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http_requests{group="canary", instance="1", job="app-server"} 800
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http_requests{group="production", instance="0", job="api-server"} 100
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http_requests{group="production", instance="0", job="app-server"} 500
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http_requests{group="production", instance="1", job="api-server"} 200
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http_requests{group="production", instance="1", job="app-server"} 600
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eval instant at 50m http_requests AND IGNORING (group, instance, job) vector(1)
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http_requests{group="canary", instance="0", job="api-server"} 300
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http_requests{group="canary", instance="0", job="app-server"} 700
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http_requests{group="canary", instance="1", job="api-server"} 400
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http_requests{group="canary", instance="1", job="app-server"} 800
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http_requests{group="production", instance="0", job="api-server"} 100
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http_requests{group="production", instance="0", job="app-server"} 500
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http_requests{group="production", instance="1", job="api-server"} 200
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http_requests{group="production", instance="1", job="app-server"} 600
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# Comparisons.
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eval instant at 50m SUM(http_requests) BY (job) > 1000
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{job="app-server"} 2600
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eval instant at 50m 1000 < SUM(http_requests) BY (job)
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{job="app-server"} 1000
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eval instant at 50m SUM(http_requests) BY (job) <= 1000
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{job="api-server"} 1000
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|
eval instant at 50m SUM(http_requests) BY (job) != 1000
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{job="app-server"} 2600
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|
eval instant at 50m SUM(http_requests) BY (job) == 1000
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{job="api-server"} 1000
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eval instant at 50m SUM(http_requests) BY (job) == bool 1000
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{job="api-server"} 1
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{job="app-server"} 0
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|
eval instant at 50m SUM(http_requests) BY (job) == bool SUM(http_requests) BY (job)
|
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|
{job="api-server"} 1
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{job="app-server"} 1
|
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|
eval instant at 50m SUM(http_requests) BY (job) != bool SUM(http_requests) BY (job)
|
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{job="api-server"} 0
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{job="app-server"} 0
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eval instant at 50m 0 == bool 1
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0
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eval instant at 50m 1 == bool 1
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1
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|
eval instant at 50m http_requests{job="api-server", instance="0", group="production"} == bool 100
|
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|
{job="api-server", instance="0", group="production"} 1
|
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|
# group_left/group_right.
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|
|
clear
|
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|
|
load 5m
|
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|
|
node_var{instance="abc",job="node"} 2
|
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node_role{instance="abc",job="node",role="prometheus"} 1
|
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|
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|
|
load 5m
|
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|
|
node_cpu{instance="abc",job="node",mode="idle"} 3
|
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|
|
node_cpu{instance="abc",job="node",mode="user"} 1
|
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|
|
node_cpu{instance="def",job="node",mode="idle"} 8
|
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|
|
node_cpu{instance="def",job="node",mode="user"} 2
|
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|
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|
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|
|
load 5m
|
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|
|
random{foo="bar"} 1
|
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|
|
|
|
|
|
load 5m
|
|
|
|
|
threshold{instance="abc",job="node",target="a@b.com"} 0
|
|
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|
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|
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|
|
# Copy machine role to node variable.
|
|
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|
|
eval instant at 5m node_role * on (instance) group_right (role) node_var
|
|
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|
|
{instance="abc",job="node",role="prometheus"} 2
|
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|
|
|
|
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|
|
eval instant at 5m node_var * on (instance) group_left (role) node_role
|
|
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|
|
{instance="abc",job="node",role="prometheus"} 2
|
|
|
|
|
|
|
|
|
|
eval instant at 5m node_var * ignoring (role) group_left (role) node_role
|
|
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|
|
{instance="abc",job="node",role="prometheus"} 2
|
|
|
|
|
|
|
|
|
|
eval instant at 5m node_role * ignoring (role) group_right (role) node_var
|
|
|
|
|
{instance="abc",job="node",role="prometheus"} 2
|
|
|
|
|
|
|
|
|
|
# Copy machine role to node variable with instrumentation labels.
|
|
|
|
|
eval instant at 5m node_cpu * ignoring (role, mode) group_left (role) node_role
|
|
|
|
|
{instance="abc",job="node",mode="idle",role="prometheus"} 3
|
|
|
|
|
{instance="abc",job="node",mode="user",role="prometheus"} 1
|
|
|
|
|
|
|
|
|
|
eval instant at 5m node_cpu * on (instance) group_left (role) node_role
|
|
|
|
|
{instance="abc",job="node",mode="idle",role="prometheus"} 3
|
|
|
|
|
{instance="abc",job="node",mode="user",role="prometheus"} 1
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
# Ratio of total.
|
|
|
|
|
eval instant at 5m node_cpu / on (instance) group_left sum by (instance,job)(node_cpu)
|
|
|
|
|
{instance="abc",job="node",mode="idle"} .75
|
|
|
|
|
{instance="abc",job="node",mode="user"} .25
|
|
|
|
|
{instance="def",job="node",mode="idle"} .80
|
|
|
|
|
{instance="def",job="node",mode="user"} .20
|
|
|
|
|
|
|
|
|
|
eval instant at 5m sum by (mode, job)(node_cpu) / on (job) group_left sum by (job)(node_cpu)
|
|
|
|
|
{job="node",mode="idle"} 0.7857142857142857
|
|
|
|
|
{job="node",mode="user"} 0.21428571428571427
|
|
|
|
|
|
|
|
|
|
eval instant at 5m sum(sum by (mode, job)(node_cpu) / on (job) group_left sum by (job)(node_cpu))
|
|
|
|
|
{} 1.0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
eval instant at 5m node_cpu / ignoring (mode) group_left sum without (mode)(node_cpu)
|
|
|
|
|
{instance="abc",job="node",mode="idle"} .75
|
|
|
|
|
{instance="abc",job="node",mode="user"} .25
|
|
|
|
|
{instance="def",job="node",mode="idle"} .80
|
|
|
|
|
{instance="def",job="node",mode="user"} .20
|
|
|
|
|
|
|
|
|
|
eval instant at 5m node_cpu / ignoring (mode) group_left(dummy) sum without (mode)(node_cpu)
|
|
|
|
|
{instance="abc",job="node",mode="idle"} .75
|
|
|
|
|
{instance="abc",job="node",mode="user"} .25
|
|
|
|
|
{instance="def",job="node",mode="idle"} .80
|
|
|
|
|
{instance="def",job="node",mode="user"} .20
|
|
|
|
|
|
|
|
|
|
eval instant at 5m sum without (instance)(node_cpu) / ignoring (mode) group_left sum without (instance, mode)(node_cpu)
|
|
|
|
|
{job="node",mode="idle"} 0.7857142857142857
|
|
|
|
|
{job="node",mode="user"} 0.21428571428571427
|
|
|
|
|
|
|
|
|
|
eval instant at 5m sum(sum without (instance)(node_cpu) / ignoring (mode) group_left sum without (instance, mode)(node_cpu))
|
|
|
|
|
{} 1.0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
# Copy over label from metric with no matching labels, without having to list cross-job target labels ('job' here).
|
|
|
|
|
eval instant at 5m node_cpu + on(dummy) group_left(foo) random*0
|
|
|
|
|
{instance="abc",job="node",mode="idle",foo="bar"} 3
|
|
|
|
|
{instance="abc",job="node",mode="user",foo="bar"} 1
|
|
|
|
|
{instance="def",job="node",mode="idle",foo="bar"} 8
|
|
|
|
|
{instance="def",job="node",mode="user",foo="bar"} 2
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
# Use threshold from metric, and copy over target.
|
|
|
|
|
eval instant at 5m node_cpu > on(job, instance) group_left(target) threshold
|
|
|
|
|
node_cpu{instance="abc",job="node",mode="idle",target="a@b.com"} 3
|
|
|
|
|
node_cpu{instance="abc",job="node",mode="user",target="a@b.com"} 1
|
|
|
|
|
|
|
|
|
|
# Use threshold from metric, and a default (1) if it's not present.
|
|
|
|
|
eval instant at 5m node_cpu > on(job, instance) group_left(target) (threshold or on (job, instance) (sum by (job, instance)(node_cpu) * 0 + 1))
|
|
|
|
|
node_cpu{instance="abc",job="node",mode="idle",target="a@b.com"} 3
|
|
|
|
|
node_cpu{instance="abc",job="node",mode="user",target="a@b.com"} 1
|
|
|
|
|
node_cpu{instance="def",job="node",mode="idle"} 8
|
|
|
|
|
node_cpu{instance="def",job="node",mode="user"} 2
|
|
|
|
|
|
|
|
|
|
clear
|
|
|
|
|
|
|
|
|
|
load 5m
|
|
|
|
|
random{foo="bar"} 2
|
|
|
|
|
metricA{baz="meh"} 3
|
|
|
|
|
metricB{baz="meh"} 4
|
|
|
|
|
|
|
|
|
|
# On with no labels, for metrics with no common labels.
|
|
|
|
|
eval instant at 5m random + on() metricA
|
|
|
|
|
{} 5
|
|
|
|
|
|
|
|
|
|
# Ignoring with no labels is the same as no ignoring.
|
|
|
|
|
eval instant at 5m metricA + ignoring() metricB
|
|
|
|
|
{baz="meh"} 7
|
|
|
|
|
|
|
|
|
|
eval instant at 5m metricA + metricB
|
|
|
|
|
{baz="meh"} 7
|
