Bigquery metrics

This folder contains config files describing metrics that summarize data in our Bigquery test result database. Config files are consumed by the metrics-bigquery periodic prow job that runs the bigquery image and scenario. Each metric consists of a bigquery query and a jq filter. The query is run every 24 hours to produce a json data file containing the complete raw query results named with the format 'raw-yyyy-mm-dd.json'. The raw file is then filtered with the associated jq filter and the results are stored in 'daily-yyyy-mm-dd.json'. These files are stored in the k8s-metrics GCS bucket in a directory named with the metric name and persist for a year after their creation. Additionally, the latest filtered results for a metric are stored in the root of the k8s-metrics bucket and named with the format 'METRICNAME-latest.json'.

Metrics

• failures - find jobs that have been failing the longest
  • Config
  • failures-latest.json
• flakes - find the flakiest jobs this week (and the flakiest tests in each job).
  • Config
  • flakes-latest.json
• job-flakes - compute consistency of all jobs
  • Config
  • job-flakes-latest.json
• weekly-consistency - compute overall weekly consistency for PRs
  • Config
  • weekly-consistency-latest.json

Adding a new metric

To add a new metric, create a PR that adds a new yaml config file specifying the metric name, the bigquery query to execute, and a jq filter to filter the data for the daily and latest files. Find the new metric on GCS 24 hours after merging.

Consistency

Consistency means the test, job, pr always produced the same answer. For example suppose we run a build of a job 5 times at the same commit:

• 5 passing runs, 0 failing runs: consistent
• 0 passing runs, 5 failing runs: consistent
• 1-4 passing runs, 1-4 failing runs: inconsistent aka flaked