Cases4 cases

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1. IL-0150 A latent race condition in DynamoDB's DNS automation left an empty DNS record for dynamodb.us-east-1.amazonaws.com, and the DynamoDB and EC2 launch failures that followed caused EKS, ECS and Fargate container launch failures and cluster scaling delays in us-east-1

   Amazon Web Services2025

   Symptoms

   At 11:48 PM PDT on 19 October 2025, every system that reached DynamoDB in us-east-1 through the public regional endpoint started getting DNS failures and could not connect. This included customer traffic and internal AWS services that depend on DynamoDB. DynamoDB global table replicas in other regions still answered but fell behind in replication to and from us-east-1.

   DNS resolution failuresHigh error rateScale-up failureIntermittent connection failuresHigh latency

   Trigger

   One DNS Enactor, slowed by unusually high retry delays, applied a much older DNS plan to the regional DynamoDB endpoint just as another Enactor that had applied the newest plan ran its clean-up, which deleted that older plan and with it every IP address of the endpoint.

   Root cause

   Software defect

   Component

   Authoritative DNS servers and recordsDatabaseCloud load balancer

   Contributing factor

   Automation amplificationRetry stormNo runbook

   Detection

   DNS failures to DynamoDB began immediately at 11:48 PM PDT and the engineering teams of affected AWS services were engaged at once; by 12:38 AM they had identified DynamoDB's DNS state as the source. The later NLB health check problem was detected by monitoring at 6:52 AM.

   Remediation

   • applied temporary mitigations by 1:15 AM that let some internal services reach DynamoDB and repaired key internal tooling
   • restored all DynamoDB DNS information by 2:25 AM through manual operator intervention
   • throttled incoming work and selectively restarted DWFM hosts from 4:14 AM so droplet leases could be re-established
   • reduced the load on Network Manager to bring network configuration propagation times back to normal by 10:36 AM
   • disabled automatic health check failover for NLB at 9:36 AM, and re-enabled it at 2:09 PM after EC2 recovered
   • relaxed the EC2 request throttles from 11:23 AM until all EC2 APIs and launches were normal at 1:50 PM

   Action items

   • Disable the DynamoDB DNS Planner and DNS Enactor automation worldwide
   • Fix the race condition and add protections against applying incorrect DNS plans before re-enabling the DNS automation
   • Add a velocity control to NLB that limits how much capacity a single load balancer can remove when health check failures cause availability zone failover
   • Build an additional EC2 test suite that exercises the DWFM recovery workflow at scale
   • Improve throttling in EC2 data propagation systems so incoming work is rate limited by the size of the waiting queue

   Lessons

   A single DNS record that automation can empty is enough to take a widely used regional endpoint off the network, and every service built on it fails in turn. A check made once at the start of a long operation can be stale by the time the operation writes its result. Recovery of the dependency is not recovery of the dependents: systems that lost state during the outage, such as EC2's droplet leases and network propagation backlog, can collapse under their own catch-up work, and container services that rely on new instance launches keep failing to launch and scale until that work is done.

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2. IL-0347 About 25% of Scaleway FR-PAR-1 hypervisors lost VPC connectivity when both VPC BGP route reflectors got stuck

   Scaleway2024

   Symptoms

   On 18 October 2024, from 7:50 to 8:01 UTC, about 25% of the hypervisors in Scaleway's FR-PAR-1 availability zone lost VPC connectivity with the rest of the region, and products that use VPC failed with them. Public internet connectivity and Elastic Metal VPC connectivity were not affected.

   Network unreachablePacket lossNode NotReady

   Trigger

   At 6:20 UTC a Top of Rack switch in FR-PAR-1 had a software crash. One of the two BGP route reflectors for VPC ran on a hypervisor in that rack and was left in an abnormal state.

   Root cause

   Software defect

   Component

   Network control plane (SDN)BGP routingNetwork switchDatabaseManaged Kubernetes control plane and provider API

   Contributing factor

   Excessive blast radiusAutomation amplification

   Detection

   Health-check monitoring on both route reflectors detected the anomaly, and the Scaleway Customer Excellence and SRE teams detected the customer impact and opened an incident.

   Remediation

   • Fixed both VPC route reflectors by manual action

   Action items

   • Fixed the autohealing mechanism that had failed to fix route reflectors stuck in a stale state; the fix is https://github.com/FRRouting/frr/pull/17163
   • Run different software versions on the route reflectors so a single bug cannot stop several instances
   • Investigate the software issue that left the route reflectors in a stale state

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3. IL-0462 Some MySQL pods on Shopify's GKE clusters took up to 30 minutes to start, slowing instance replacement

   Shopify2021

   Symptoms

   In 2021 Shopify's KateSQL, a database-as-a-service platform that runs several hundred production MySQL instances on GKE, found that some MySQL pods started and shut down much more slowly than similar pods with the same data set. Instance replacement, the procedure that creates a new MySQL replica pod and stops the old one, showed pod creation times ranging from 10 to 30 minutes, which held up maintenance such as configuration changes and upgrades.

   Slow pod startup or shutdownHigh latency

   Root cause

   Software defect

   Component

   Linux kernelNode operating system imageDatabase

   Contributing factor

   Unpatched known bug

   Detection

   KateSQL's instance replacement operations showed inconsistent MySQL pod creation times, and the team then measured the mysql-init container and MySQL startup times across pods.

   Remediation

   • Cordoned older nodes, moved MySQL pods to new nodes through instance replacement and drained the old nodes
   • Forced the kubepods memory cgroup to empty its dead cgroups on an affected node to test the fix
   • Created new GKE 1.18 clusters and started creating MySQL pods on them

   Lessons

   The investigation was one of the longest the Database Platform group had carried out, because of the nature of the problem, how hard it was to reproduce and the lack of an established method to follow; once the cause was known, there were several ways to fix it.

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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

   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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