Incident Library
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  1. Symptoms

    Reports came in of more WORKER_JOB_ERROR errors, which tell Transloadit there is a communication problem between its Uploaders, the machines that receive files and orchestrate Assemblies, and its Drones, the machines that run encoding tasks. Many Assemblies became much slower because retries with exponential back-off kicked in, and a few could not be replayed.

    Trigger

    A steep increase in HLS traffic, together with more Drones online processing the same volume faster, which put more load on the central Redis nodes.

    Root cause
    Component
    Contributing factor
    Detection

    Reports of an increased number of WORKER_JOB_ERROR errors.

    Remediation
    • Re-added lost messages and relaxed heartbeat monitoring as a stopgap
    • Upgraded Redis to the latest stable version
    • Doubled the Redis cluster to six nodes and then added three more, which made it worse
    • Brought the number of read replicas down to one, which cut traffic and failure rates
    • Capped how far Drones scale up in each region
    Action items
    • Add logging and alarms for approaching saturation
    • Find ways to decentralise the traffic between the Redis nodes and the Drones and Uploaders
    • Add sharding per Uploader on top of the sharding per region
    Lessons

    To handle more traffic Transloadit had to use fewer Redis nodes, not more: each added replica multiplied the replication traffic from the single leader that takes every write, so scaling up the number of nodes was the wrong call. Bandwidth had not been among the monitored Redis metrics.

Check your cluster for this

This case involves In-memory cache and Database replication. 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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