feat(kubernetes_logs): Add backoff for watchers#17009
feat(kubernetes_logs): Add backoff for watchers#17009spencergilbert merged 2 commits intovectordotdev:masterfrom
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Signed-off-by: m.nabokikh <maksim.nabokikh@flant.com>
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Regression Detector ResultsRun ID: 6de870c1-6e0a-497a-bd12-365543bf210d ExplanationA regression test is an integrated performance test for The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values mean that baseline is faster, positive comparison. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed. No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%. Fine details of change detection per experiment.
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LGTM, @nabokihms do you mind pushing an empty commit to trigger the k8s tests, just to be on the safe side? |
Signed-off-by: m.nabokikh <maksim.nabokikh@flant.com>
Regression Detector ResultsRun ID: f12bdd09-68ef-417d-8296-b636f71d7193 ExplanationA regression test is an integrated performance test for The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values mean that baseline is faster, positive comparison. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed. No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%. Fine details of change detection per experiment.
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spencergilbert
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🤷 some spurious failures in the e2e tests that were resolved on a retry. Would be nice if I had a better idea why those intermittently fail, but it's not a priority right now 🙂
Description
On startup, if Kubernetes API is unavailable or responds with an error, vector, without waiting, tries to send a request again.
Vector logs:
Pay attention to timestamps. These messages continue until vector consumes all the CPU and memory and dies.
Solution
Add default backoff to watchers.
https://docs.rs/kube/latest/kube/runtime/utils/struct.StreamBackoff.html
https://docs.rs/kube/latest/kube/runtime/watcher/fn.default_backoff.html
More context can be found here
kube-rs/kube#717 (comment)