Cases12 cases

5 to 9 of 12

1. IL-0123 A response buffer allocated anew in a loop made OpenAI's routing layer nodes hit their memory limits and fail readiness checks on a morning with more completions than any day before, causing 502 and 503 errors across all models

   OpenAI2023

   Symptoms

   Between 5:42 AM and 7:16 AM PT on 8 November 2023 a large share of requests to OpenAI failed with 502 or 503 errors. Every model and API endpoint saw significant failures.

   High error rateService outageProbe failures

   Trigger

   A morning with dramatically more completions than any previous day pushed the routing layer nodes, which already had a chronic memory problem, past their memory limits.

   Root cause

   Software defect

   Component

   Model request routingContainer memory limit

   Contributing factor

   No alert on limitNo headroom

   Remediation

   • limited incoming traffic
   • redeployed the routing service en masse
   • ramped traffic back up slowly

   Action items

   • Pre-allocate the responseBuffer and reuse it instead of allocating a new one in a loop (3X improvement in memory and CPU usage)
   • Adjust the configured memory limits to an appropriate level so the service has significant headroom
   • Add rate limit controls to shed traffic more gracefully
   • Increase the service's capacity
   • Change alerting to catch the underlying memory behaviour before it escalates into service issues
   • Configure autoscaling for the service, which was not possible before because added capacity could hurt an upstream service

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2. IL-0132 A faulty resource cleanup process marked Vertex AI prediction endpoints as deleted worldwide, undeploying customers' models and failing predictions for 4 hours 20 minutes

   Google Cloud2022

   Symptoms

   From 10:10 US/Pacific on 2 June 2022, Vertex AI Online Prediction returned errors for 30% up to 100% of requests per region, depending on how each customer used the service.

   High error rateResources deletedService outage

   Trigger

   A faulty resource cleanup process marked Vertex Prediction Endpoints as deleted, globally.

   Root cause

   Software defect

   Component

   Model request routing

   Contributing factor

   Automation amplificationExcessive blast radius

   Detection

   The first public status update was posted at 13:58 US/Pacific and gave the start as 10:20 US/Pacific; the later mini incident report gives 10:10.

   Remediation

   • restored the Vertex Prediction Endpoints that had been marked as deleted

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3. IL-0106 A malformed Traefik IngressRoute triggered a Traefik v2 bug once a node rollover restarted every Traefik pod, and all Kubernetes services returned 404

   DFDS2021

   Symptoms

   At 08:00 UTC on 2021-09-06 every service in DFDS's Kubernetes cluster answered with 404. Investigation started five minutes later.

   Service outageHigh error rateProbe failures

   Trigger

   The automated Kubernetes node rollover on 2021-09-06 restarted all the Traefik v2 pods, five days after a malformed IngressRoute manifest had been applied.

   Root cause

   Software defect

   Component

   Ingress controllerCloud load balancer

   Contributing factor

   Change with a delayed effectNo configuration testsExcessive blast radius

   Detection

   All services returned 404 from 08:00 UTC and root cause investigation started at 08:05. Time to detection was 5 minutes.

   Remediation

   • changed the ALB health check path, which made the targets healthy but did not stop the 404s
   • rolled back by hand to Traefik v1 as the main ingress controller
   • deleted the malformed IngressRoute by hand and confirmed the Traefik v2 bug
   • applied the changes upstream

   Action items

   • Upgrade Traefik to v2.5, where the bug is fixed, and verify that it removes the bug
   • Change the Traefik v2 health check path to something more robust
   • Set up an external liveness probe on the ingress controller
   • Consider workload segmentation to limit the blast zone
   • Look into monitoring the Traefik v2 API for rapid changes
   • Look into smoke testing during and after node rollover

   Lessons

   A malformed IngressRoute did nothing visible for five days and then took down all ingress when every Traefik v2 pod had restarted during a node rollover. Because Traefik v2 failed gracefully, the first signals pointed at the ALB health checks instead of at Traefik. On incident handling, the team concluded that appointing an incident manager could have helped, that the war room meeting should be recorded and a log book kept, that people not involved should only make suggestions in writing, and that a short first round of sharing thoughts and gut feelings is useful.

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4. IL-0196 Adding a second Redis replica and lowering memory limits in one RedisFailover change restarted the only Redis pod that held data, and Sentinel promoted the empty new replica, erasing the data

   Palark2020

   Symptoms

   Right after an updated RedisFailover resource was rolled out, the large Redis database lost all its data and the service went down; the data had to be restored from a backup taken just before the change.

   Data lossService outage

   Trigger

   A RedisFailover change that raised the number of Redis replicas from one to two and, in the same rollout, lowered the containers' memory requests and limits from 22 GB to 19 GB.

   Root cause

   Software defect

   Component

   Application databasePersistent volumes and stateful setsContainer memory limit

   Contributing factor

   No staged rolloutSingle point of failureUnverified assumption

   Remediation

   • restored the Redis data from the backup prepared before the rollout

   Action items

   • Report the readiness probe flaw to the Redis Operator project and test the developers' fix
   • Reconsider the use of the Spotahome Redis Operator
   • Clean up the Redis databases and fix the application code that created the excess keys
   • Consider Redis built-in clustering and sharding

   Lessons

   Changing the replica count and the pod resources in one rollout turned a seemingly harmless change into a rolling restart of the only pod with data while the new replica was still empty. A readiness probe that only checks that Redis answers a ping does not tell whether a replica has finished syncing. Operators for critical stateful components need to be evaluated for maturity before production use, and the dump.rdb file should be backed up before any change to the Redis cluster.

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5. IL-0051 A third-party log shipping client leaked file descriptors with every new container until nodes failed with too many open files

   thredUP2018

   Symptoms

   While thredUP's move to Kubernetes seemed to be going well, Datadog showed the number of open files on the nodes climbing steadily, with no obvious reason.

   Service outageFile descriptor exhaustion

   Trigger

   Containers starting on a node, which in Kubernetes happens constantly with every deploy and every pod that moves between nodes.

   Root cause

   Software defect

   Component

   Telemetry agent

   Contributing factor

   Unverified assumption

   Detection

   Datadog showed the number of open files on the nodes rising.

   Remediation

   • killed the affected node, brought up a new one and redeployed

   Action items

   • Move away from the log aggregation vendor

   Lessons

   Libraries and agents that worked with the EC2 deployment lifecycle may not cope with Kubernetes, where containers start, stop and move between nodes constantly. Each one needs to be checked against the new lifecycle instead of being trusted because it worked before.

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