Incident Library
  • Root cause
  • Component
  • Symptom
  • Contributing factor
  • Case

Cases2 cases

1 to 2 of 2

  1. Symptoms

    On 19 and 20 October 2022, Linode Object Storage in Newark and Atlanta slowed down, became less available and rate limited many requests with "503 - Slow Down" HTTP responses, after the clusters received extremely high inbound traffic in both request count and bandwidth.

    Trigger

    Extremely high inbound traffic, in both total requests and throughput, reached the Newark and Atlanta Object Storage clusters on 19 and 20 October 2022.

    Root cause
    Component
    Contributing factor
    Remediation
    • Fixed the edge rate limiting so it enforces the advertised 750 requests per second per bucket
    • Adjusted Ceph tunables to stop runaway memory use during high-pressure storage events
    • Moved internal Object Storage components hit by resource contention to less busy, higher-performance infrastructure
    • Adjusted performance tunables on internal components and back-end clusters so customers were not rate limited too early
    Action items
    • Refine throughput and bandwidth throttling
    • Scale up the internal Object Storage infrastructure to spread load more efficiently
    • Look for further hardware performance improvements for the internal Object Storage infrastructure
    • Tune the load balancing algorithms to avoid hotspots in the clusters
    Lessons

    Linode's per-bucket rate limiting at the edge is meant to keep excess load off the back end; when it works as intended, the back-end limits, which throttle every client alike, should never come into play.

  2. Symptoms

    From 9:37AM PST on February 28th, 2017, Amazon S3 in the Northern Virginia (US-EAST-1) Region could not serve requests. AWS services in the region that store data in S3 failed with it, including the S3 console, new Amazon EC2 instance launches, Amazon EBS volumes that needed data from an S3 snapshot, and AWS Lambda.

    Trigger

    While debugging an S3 billing system that was progressing more slowly than expected, an authorized S3 team member followed an established playbook to remove a small number of servers from one S3 subsystem used by the billing process, and entered one input of the command incorrectly.

    Root cause
    Component
    Contributing factor
    Remediation
    • Restarted the index subsystem, which served GET, LIST and DELETE again from 12:26PM PST
    • Restarted the placement subsystem after the index subsystem worked, restoring PUT by 1:54PM PST
    Action items
    • Change the capacity removal tool to remove capacity more slowly
    • Add safeguards that stop capacity removal when it would take a subsystem below its minimum required capacity
    • Audit other operational tools for similar safety checks
    • Improve the recovery time of key S3 subsystems and start the planned further partitioning of the index subsystem into cells now
    • Run the SHD administration console across multiple AWS regions
Check your cluster for this

These 2 cases involve Object storage and Cloud block storage. kubegap audits a Kubernetes cluster for gaps like these, read-only, from Claude Code or Codex; its checks cite public reports like the ones in this library.

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