scheduler/

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Published: Dec 16, 2024 License: Apache-2.0

README

Scalability test

Is a test meant to detect regressions in the Kueue's overall scheduling capabilities.

Components

In order to achieve this the following components are used:

Runner

An application able to:

  • generate a set of Kueue specific objects based on a config following the schema of default_generator_config
  • mimic the execution of the workloads
  • monitor the created object and generate execution statistics based on the received events

Optionally it's able to run an instance of minimalkueue in a dedicated envtest environment.

MinimalKueue

A light version of the Kueue's controller manager consisting only of the core controllers and the scheduler.

It is designed to offer the Kueue scheduling capabilities without any additional components which may flood the optional cpu profiles taken during it's execution.

Checker

Checks the results of a performance-scheduler against a set of expected value defined as default_rangespec.

Usage

Run in an existing cluster

make run-performance-scheduler-in-cluster

Will run a performance-scheduler scenario against an existing cluster (connectable by the host's default kubeconfig), and store the resulting artifacts are stored in $(PROJECT_DIR)/bin/run-performance-scheduler-in-cluster.

The generation config to be used can be set in SCALABILITY_GENERATOR_CONFIG by default using $(PROJECT_DIR)/test/performance/scheduler/default_generator_config.yaml

Setting SCALABILITY_SCRAPE_INTERVAL to an interval value and SCALABILITY_SCRAPE_URL to an URL exposing kueue's metrics will cause the scalability runner to scrape that URL every interval and store the results in $(PROJECT_DIR)/bin/run-performance-scheduler-in-cluster/metricsDump.tgz.

Check installation guide for cluster and observability.

Run with minimalkueue

make run-performance-scheduler

Will run a performance-scheduler scenario against an envtest environment and an instance of minimalkueue. The resulting artifacts are stored in $(PROJECT_DIR)/bin/run-performance-scheduler.

The generation config to be used can be set in SCALABILITY_GENERATOR_CONFIG by default using $(PROJECT_DIR)/test/performance/scheduler/default_generator_config.yaml

Setting SCALABILITY_CPU_PROFILE=1 will generate a cpuprofile of minimalkueue in $(PROJECT_DIR)/bin/run-performance-scheduler/minimalkueue.cpu.prof

Setting SCALABILITY_KUEUE_LOGS=1 will save the logs of minimalkueue in $(PROJECT_DIR)/bin/run-performance-scheduler/minimalkueue.out.log and $(PROJECT_DIR)/bin/run-performance-scheduler/minimalkueue.err.log

Setting SCALABILITY_SCRAPE_INTERVAL to an interval value (e.g. 1s) will expose the metrics of minimalkueue and have them collected by the scalability runner in $(PROJECT_DIR)/bin/run-performance-scheduler/metricsDump.tgz every interval.

Run performance-scheduler test

make test-performance-scheduler

Runs the performance-scheduler with minimalkueue and checks the results against $(PROJECT_DIR)/test/performance-scheduler/default_rangespec.yaml

Scrape result

The scrape result metricsDump.tgz contains a set of <ts>.prometheus files, where ts is the millisecond representation of the epoch time at the moment each scrape was stared and can be used during the import in a visualization tool.

If an instance of VictoriaMetrics listening at http://localhost:8428 is used, a metrics dump can be imported like:

 TMPDIR=$(mktemp -d)
 tar -xf ./bin/run-performance-scheduler/metricsDump.tgz -C $TMPDIR
 for file in ${TMPDIR}/*.prometheus; do timestamp=$(basename "$file" .prometheus);  curl -vX POST -T "$file" http://localhost:8428/api/v1/import/prometheus?timestamp="$timestamp"; done
 rm -r $TMPDIR

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