Cases5 cases

1 to 5 of 5

1. IL-0213 Roblox was down for 73 hours because key-value writes on its single Consul cluster slowed from under 300 ms to 2 seconds

   Roblox2021

   Symptoms

   On the afternoon of 28 October 2021 (13:37 PST), Vault performance at Roblox degraded and a single Consul server showed high CPU load. Consul cluster metrics showed that writes to its key-value (KV) store had a 50th percentile latency of 2 seconds instead of the usual under 300 ms. Players were not yet affected.

   High latencySustained high node CPUService outageMonitoring outage

   Trigger

   On 27 October at 14:00, one day before the outage, Roblox enabled the Consul streaming feature on the backend service responsible for traffic routing and, to prepare for end-of-year traffic, added 50% more nodes to traffic routing.

   Root cause

   Software defect

   Component

   Coordination and key-value storeService discoveryIn-memory cache

   Contributing factor

   Single point of failureOverlapping failuresMonitoring blind spotHarmful manual actionChange with a delayed effect

   Detection

   Roblox engineers began investigating when Vault performance degraded and a single Consul server had high CPU load, before players were affected. Consul cluster metrics then showed elevated KV write latency.

   Remediation

   • Replaced one Consul cluster node on the suspicion of degraded hardware
   • Replaced all Consul nodes with 128-core machines with faster NVMe SSDs
   • Shut down the Consul cluster and reset its state from a snapshot taken at the start of the outage, with access blocked by iptables
   • Blocked external traffic, disabled all non-essential Consul use, scaled services down and lowered health check frequency from 60 seconds to 10 minutes
   • Moved the Consul cluster back to 64-core servers
   • Disabled the streaming feature for all Consul systems, which brought KV write latency back to 300ms
   • Kept the slow Consul servers from staying elected as leader
   • Redeployed the caching system and fixed its wrong scheduling data and failed deployments
   • Restarted the stopped services at the right capacity levels
   • Let players back in with DNS steering in roughly 10% steps while checking database load, cache performance and stability

   Action items

   • HashiCorp builds laboratory benchmarks and scale tests that reproduce the streaming contention
   • HashiCorp improves the design of streaming so it does not contend under extreme load
   • Compact the BoltDB database with existing BoltDB tooling
   • Remove the circular dependency between the telemetry systems and Consul
   • Extend telemetry with targeted alerts on Consul and BoltDB performance and with visibility into traffic between services and Consul
   • Run the backend in an additional, geographically distinct data center and in multiple availability zones
   • Split critical services into their own dedicated Consul clusters
   • Move data that core services keep directly in the Consul KV store to a more suitable storage system
   • Delete obsolete KV data from Consul
   • Upgrade to a Consul version that replaces BoltDB with bbolt, in Q1
   • Redesign cache deployment so the cache system can be brought up quickly from a standing start
   • Deploy Nomad enhancements that make it easier to turn up large jobs after a long period of unavailability
   • Use mechanisms for faster machine configuration changes
   • Reintroduce streaming only after a new implementation has been tested at Roblox's scale and workload

   Lessons

   Two mostly unrelated problems deep inside Consul, contention in streaming under very high read and write load and BoltDB freelist growth, were hard to diagnose, and that difficulty was the main reason the outage lasted so long. A single Consul cluster serving every workload made the impact larger, and monitoring that depended on Consul hid the cause when it was needed most. Faster hardware did not help and may have hurt, because the contention was worse on NUMA machines. HashiCorp had benchmarked streaming at a similar scale, but the problem needed both a large number of streams and a high churn rate. Restarting a platform from a fully stopped state, including warming caches, took a long time and needed tools built for bootstrapping rather than incremental change.

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2. IL-0271 An empty etcd service entry crashed Discord's Elixir chat nodes, and Discord was down for most users for an hour

   Discord2020sev1

   Symptoms

   On 16 March 2020 at 14:19 PDT most of Discord's Elixir services, which handle real-time connections and chat message processing, crashed at once. Discord lost much of its real-time capacity, the failure cascaded into dependent systems, and most users could not connect for about an hour.

   Service outageHigh error rate

   Trigger

   At 14:18 the Google Cloud managed instance group autoscaler added a node to Discord's API cluster, and the TCP connection of its first announce request to etcd was reset after the request headers were sent but before the body.

   Root cause

   Software defect

   Component

   Coordination and key-value storeService discovery

   Contributing factor

   Automation amplification

   Detection

   At 14:21 several internal alarms fired on a drop in key metrics, along with anomaly alerts for cluster utilization, and a SEV1 incident was declared.

   Remediation

   • Restarted the lost real-time capacity and repaired the failed nodes
   • Throttled connections to Discord to help services recover
   • Stopped anti-entropy repairs on two ScyllaDB clusters so reconnecting users would not starve them of resources
   • Raised the connection throttle step by step to let more users reconnect

   Action items

   • Make the etcd clients send each announce request in a single TCP packet, so headers and body arrive together or not at all
   • Add error handling that ignores services whose key value is corrupt instead of crash-looping
   • File an upstream bug report with the Go project about net/http not checking the body against Content-Length

   Lessons

   Discord's service discovery code handled many etcd failure modes but did not expect a client to write a key without a value because of a transient network error. Go's net/http accepts a request whose body is shorter than its Content-Length header, which breaks the HTTP 1.1 specification and added a failure case nobody had anticipated.

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3. IL-0277 Patching Elastic Cloud's ZooKeeper ensemble in us-east-1 lost quorum, and hosted clusters and Kibana went unreachable

   Elastic2019

   Symptoms

   On 4 February 2019 at about 02:50 UTC, Elastic Cloud customers with deployments in AWS us-east-1 lost stable access to their Elasticsearch clusters, and an increase in HTTP 5xx errors showed on the load balancer. Deployments were partially or completely unavailable until 09:28 UTC, Kibana access was disrupted for most customers in the region, and the Elastic Cloud User Console timed out when customers tried to view their deployments.

   High error rateService outageIntermittent timeoutsNode kernel panic

   Trigger

   A routine patching procedure in AWS us-east-1 replaced the first and second members of the three-node ZooKeeper ensemble with patched hosts between 02:25 and 02:45 UTC, following the same documented process used in the other 12 regions.

   Root cause

   Software defect

   Component

   Coordination and key-value storeContainer runtimeLinux kernelElasticsearch or OpenSearchconntrack table

   Contributing factor

   Monitoring blind spotRetry stormHealth check tied to a dependencyOverlapping failuresHarmful manual action

   Detection

   An increase in HTTP 5xx errors on the load balancer was identified at 02:50 UTC, the time the ZooKeeper ensemble lost its leader.

   Remediation

   • Restarted internal services in sweeping restarts at 03:22 and 06:00 to reduce client connection problems
   • Isolated the ZooKeeper ensemble by cutting off client connections
   • Rolled back the remaining ensemble member after its host became unstable
   • Rolled back the second ensemble member after its host became unstable
   • Rebooted the ZooKeeper hosts made unresponsive by the runc CPU softlocks
   • Re-established ZooKeeper quorum by removing client load and operator debugging, then reintroduced client load gradually
   • Increased the initLimit setting of the ZooKeeper observer layer used by the proxies
   • Scaled the proxy fleet up and out to handle the increased traffic
   • Applied a runbook that restarted the internal proxying containers and Kibana instances and set sysctl limits

   Action items

   • Reduce the dataset size carried by the ZooKeeper ensembles by over 60%
   • Reduce the number of health checks and intervals needed before a healthy proxy node joins the load balancing layer
   • Stop counting ZooKeeper connectivity in the proxy health checks once a proxy has its configuration and routes
   • Canary the rewritten proxy v2 architecture, which decouples the proxy service from ZooKeeper state, in production regions
   • Improve visibility into ZooKeeper with better logging and metrics for the ZooKeeper processes, the JVM and the container and host systems
   • Make Kibana route discovery more resilient
   • Fix the Kibana issues that amplify internal HTTP requests during availability events
   • Fix the Kibana issues that leak connections
   • Make internal monitoring agents use backoff with jitter
   • Formalize a maintenance matrix with set timeframes per region, so failures of critical services fall in non-critical times
   • Give runbooks for coordination layer maintenance a better decision criteria matrix
   • Set up a feedback loop with support leadership for incident communications through support and the status page

   Lessons

   Service metrics that reported the ZooKeeper hosts healthy were not enough to show the state of individual hosts or of the ensemble, so they gave a false signal that maintenance could continue. Because the platform depended on the coordination layer, losing its quorum caused a major service disruption in which every Elasticsearch cluster in the region saw some failures, and fixes that worked one by one fell short at the scale of the failure.

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4. IL-0587 Elastic Cloud proxies in AWS eu-west-1 flooded an overloaded ZooKeeper and ran out of memory, cutting cluster access

   Elastic2019

   Symptoms

   On 18 January 2019 from 09:09 UTC the leader of the three-node Apache ZooKeeper ensemble behind Elastic Cloud in AWS eu-west-1 (Ireland) ran at heavy CPU load, and its clients lost their connections. From about 10:08 UTC customers in the region had severely degraded access to their Elasticsearch and Kibana deployments for roughly 3 hours, and for about 20 minutes every deployment in the region was unavailable.

   Database overloadService outageOOMKilled

   Trigger

   At 09:09 UTC the leader server of the ZooKeeper ensemble in the eu-west-1 coordination layer hit a high CPU threshold, which caused client disconnections.

   Root cause

   Software defect

   Component

   Coordination and key-value storeService discovery

   Contributing factor

   Retry stormUnpatched known bug

   Detection

   The on-call SREs received alerts about service degradation in the coordination layer at 09:35 UTC, after the high CPU on the ZooKeeper leader had caused client disconnections, and started a production incident.

   Remediation

   • Scaled the proxy layer up and out to take the surging client traffic hitting the load balancers
   • Triggered a leader election in the ZooKeeper ensemble and stabilised it

   Action items

   • Replace Curator's TreeCache with TreeWatcher across all Elasticsearch Service providers and regions
   • Contribute TreeWatcher upstream to the Apache Curator project
   • Roll out a new proxy layer that keeps the routing table in a versioned local file, so it can route traffic while the ZooKeeper connection is lost or flaky

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5. IL-0536 Amazon SimpleDB in US East returned HTTP 500 to nearly all API calls for two hours after its nodes left the cluster

   Amazon Web Services2014

   Symptoms

   From 9:16 PM to 11:16 PM PDT on June 13, Amazon SimpleDB in the US East Region was unavailable to all API calls except a fraction of eventually consistent reads, and SimpleDB API requests returned server-side errors (http response code 500).

   Service outageHigh error rate

   Trigger

   Power was lost to the servers that hosted several SimpleDB storage nodes in a single data center, and those storage nodes became unavailable at the same time.

   Root cause

   Software defect

   Component

   DatabaseCoordination and key-value storeData center power and cooling

   Contributing factor

   Automation amplification

   Remediation

   • Raised the lock service handshake timeout values by hand
   • Restarted a subset of metadata nodes, which could then authorize the storage nodes to rejoin the cluster
   • Throttled CreateDomain and DeleteDomain calls until 1:30 AM while the remaining metadata nodes recovered

   Action items

   • Set a longer lock service handshake timeout in all SimpleDB Regions
   • Make nodes wait and retry handshakes later with a longer timeout instead of removing themselves from the cluster after repeated timeouts

   Lessons

   The short handshake timeout had been chosen to detect replica failures quickly, and AWS concluded it was too low. Nodes removing themselves from the cluster right after several handshake timeouts widened the event and caused the API errors; the nodes should have waited and retried with a longer timeout.

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