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Danny Kopping beed298549 Dynamic client-side throttling to avoid object storage rate-limits (GCS only) (#10140) ... **What this PR does / why we need it**: Across the various cloud providers' object storage services, there are different rate-limits implemented. Rate-limits can be imposed under multiple conditions, such as server-side scale up (ramping up from low volume to high, "local" limit), reaching some defined upper limit ("absolute" limit), etc. We cannot know apriori when these rate-limits will be imposed, so we can't set up a client-side limiter to only allow a certain number of requests through per second. Additionally, that would require global coordination between queriers - which is difficult. With the above constraints, I have instead taken inspiration from TCP's [congestion control algorithms](https://en.wikipedia.org/wiki/TCP_congestion_control). This PR implements [AIMD](https://en.wikipedia.org/wiki/Additive_increase/multiplicative_decrease) (Additive Increase, Multiplicative Decrease), which is used in the congestion _avoidance_ phase of congestion control. The default window size (object store requests per second) is 2000; in other words, we skip the "slow start" phase. The controller uses the Go [`rate.Limiter`](https://pkg.go.dev/golang.org/x/time/rate), which implements the token-bucket algorithm. To put it simply: - every successful request widens the window (per second client rate-limit) - every rate-limited response reduces the window size by a backoff factor (0.5 by default, so it will halve) - when the limit has been reached, the querier will be delayed from making further requests until tokens are available		2 years ago
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inmemory_storage_client.go	Dynamic client-side throttling to avoid object storage rate-limits (GCS only) (#10140)	2 years ago
testutils.go	Refactoring of the Loki storage (#5833)	4 years ago