Cases8 cases

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1. IL-0268 AdGuard DNS resolvers in Amsterdam, Frankfurt and London overloaded and answered with timeouts and SERVFAIL

   AdGuard DNS2025

   Symptoms

   Between about 15:30 and 18:00 UTC on 25 November 2025 some AdGuard DNS users saw slow or failed DNS resolution, with timeouts and SERVFAIL responses. Alerts fired for increased DNS error rates and server load, and a significant part of the traffic in several European locations, primarily Amsterdam, Frankfurt and London, had intermittent DNS failures for up to 2.5 hours.

   DNS resolution failuresIntermittent timeoutsHigh latencyMemory pressure

   Trigger

   A new version of AdGuard DNS, deployed on 25 November to improve how resolvers cache user data, had a bug that saved only the recently changed subset of user data into the local cache file. The first deployment failed partway on a network issue and left about half the servers on the new version; the second attempt made many resolvers start full synchronizations at once.

   Root cause

   Faulty deployment

   Component

   Recursive DNS resolver serviceLanguage runtime settings

   Contributing factor

   Dependence on a warm cacheRetry stormHarmful manual actionGap in automated tests

   Detection

   Alerts for increased DNS error rates and server load fired during the second deployment attempt, between 15:30 and 16:00 UTC.

   Remediation

   • Rolled back the buggy version on all servers
   • Partially rerouted Amsterdam's traffic to other European locations
   • Reduced connection concurrency and request pipeline depth in Frankfurt and London, from 5 to 1 in Frankfurt
   • Adjusted limits to the actual hardware capacity
   • Repaired corrupted cache files and user data snapshots to stop further full synchronizations
   • Normalised the traffic distribution once the rollback was complete

   Action items

   • Add automated tests that the full user dataset is correctly written to and restored from the local cache file, including detection of empty or truncated caches
   • Add integration tests that simulate resolver startup with an empty or corrupted cache under realistic load
   • Standardize server hardware profiles per location, or keep separate configurations per hardware class
   • Review and adjust connlimit, cache sizes and connection limits for each standard node type
   • Reevaluate and lower pipelining depth where needed
   • Reevaluate how connections and goroutines are limited so resource use stays bounded with decent throughput after a connection break
   • Monitor Go heap size, GC time, GC cycles per second and per-cluster request latency distributions
   • Alert on sustained increases in SERVFAIL rate and request duration while upstreams are healthy
   • Refine DNS resolver deployment and rollback procedures to avoid simultaneous cache invalidation across a large part of the fleet
   • Document and rehearse playbooks for adjusting pipeline depth, connection limits and connlimit during live incidents

   Lessons

   How nodes behaved depended on the interaction between available RAM, Go's garbage collector and the connlimit setting. On 64-GiB nodes a high limit let the heap grow large under heavy concurrency and pipelining, and the garbage collector then spent more and more CPU, a known worst case for high-memory applications in which memory is not exhausted but latency rises and throughput falls. On 32-GiB nodes the same configuration reached practical memory limits sooner because it had not been scaled down. Together with high pipelining and client retries, GC pressure, connection saturation and retries formed a feedback loop.

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2. IL-0341 Traffic between Cloudflare and AWS us-east-1 had high latency, packet loss and origin failures for almost four hours

   Cloudflare2025

   Symptoms

   From 16:27 UTC on 21 August 2025, users connecting to Cloudflare from servers in AWS us-east-1, or receiving connections from Cloudflare there, saw high latency, packet loss and failures to reach origins. Cloudflare's network team was alerted to internal congestion in Ashburn (IAD) at 16:44 UTC.

   Packet lossHigh latencyIntermittent timeouts

   Trigger

   At about 16:27 UTC a single customer began sending many requests from AWS us-east-1 to Cloudflare for objects in Cloudflare's cache, doubling the total traffic from Cloudflare to AWS.

   Root cause

   Capacity exhaustion

   Component

   Transit gateway or network interconnectBGP routingCDN and edge network

   Contributing factor

   No headroomHarmful manual actionExcessive blast radius

   Detection

   Cloudflare's network team was alerted to internal congestion in Ashburn (IAD) at 16:44 UTC, and an incident was raised for customer impact at 17:45 UTC.

   Remediation

   • Rate limited the single customer whose traffic caused the surge
   • Took further traffic engineering actions that fully resolved the congestion
   • Asked AWS to revert its BGP prefix withdrawals, which AWS finished at 20:07 UTC

   Action items

   • Build a mechanism to deprioritise a customer's traffic when it congests the network enough to affect others
   • Speed up the Data Center Interconnect upgrades to add network capacity
   • Work with AWS so the two companies' BGP traffic engineering actions do not conflict
   • Build a traffic management system that gives each customer a network resource budget and automates the manual actions used here

   Lessons

   Cloudflare concludes that it must isolate customers better so that no single customer can take over shared network resources and degrade the platform for others, and that its network needs enough capacity to meet demand. It describes the outage as the result of insufficient network congestion management during an unusual high-traffic event.

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3. IL-0342 DigitalOcean's AMS3, LON1 and SFO2 data centers lost Internet connectivity in repeated waves as edge routers failed

   DigitalOcean2023

   Symptoms

   From 09:55 UTC on 9 August 2023, DigitalOcean's AMS3, LON1 and SFO2 datacenters lost Internet access in waves of 10 to 15 minutes, about an hour apart. Users saw connectivity issues, latency and timeout errors on Droplets and on Droplet-based services such as Load Balancers, Kubernetes and Database clusters.

   Network unreachableIntermittent timeoutsHigh latency

   Trigger

   The edge routers received an RPKI-related routing update, and the operating system software on them crashed its routing process on that update.

   Root cause

   Software defect

   Component

   BGP routing

   Contributing factor

   Excessive blast radiusHarmful manual action

   Remediation

   • Rolled out a software update to the edge routers running the affected version, site by site
   • Rebalanced traffic on the congested routes between AMS3 and FRA1
   • Rolled out the fix to the redundant networking equipment so a failover would not hit the bug

   Action items

   • Upgrade all global edge routers to remove the bug
   • Bring the network upgrades already done in Asia to Europe and North America

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4. IL-0225 An IGP purge command made every Microsoft WAN router recompute routes, causing global latency, timeouts and packet loss

   Microsoft Azure2023

   Symptoms

   From 07:08 UTC on 25 January 2023, customers saw long network latency and timeouts when connecting to resources in Azure regions and to other Microsoft services such as Microsoft 365 and Power Platform. Microsoft's monitoring detected DNS and WAN issues from 07:11 UTC.

   High latencyIntermittent timeoutsIntermittent connection failuresPacket lossNetwork unreachable

   Trigger

   A network engineer adding capacity to the global WAN in Madrid ran a step of a recently changed standard operating procedure that purged the IGP database; on the router manufacturer involved, that command runs on all IGP-joined routers instead of only the local one.

   Root cause

   Configuration change

   Component

   Backbone network (WAN)Interior routing (IGP)BGP routing

   Contributing factor

   No configuration testsUnverified assumptionExcessive blast radiusHarmful manual action

   Detection

   Monitoring detected DNS and WAN issues from 07:11 UTC and alerted the on-call engineers within 5 minutes of the command being run. The team reviewed all recent changes and identified the command by 08:20 UTC. The engineer making the change was not informed of the alerts because of the unqualified changes to the SOP.

   Remediation

   • Restarted by hand the paused WAN health and traffic engineering systems, which ended the remaining packet loss

   Action items

   • Audit and block similar widespread-impact commands across all three vendors for all WAN router roles
   • Give on-call engineers real-time visibility of approved and unqualified activity on network devices
   • Run regular mandatory operational training and attestation of following all SOPs
   • Have the Change Advisory Board review all SOPs still pending qualification within 30 days

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5. IL-0241 A database shard could not elect a new primary, and the Stripe API failed most requests in two periods on one day

   Stripe2019

   Symptoms

   On 10 July 2019 the Stripe API failed a substantial majority of requests twice, from 16:35 to 17:02 UTC and from 21:14 to 22:47 UTC. In the first period automated monitoring detected within a minute that a database cluster had failed to elect a new primary.

   High error rateFailover failureWrites rejectedIntermittent timeoutsSustained high node CPU

   Trigger

   The primary node of a database cluster failed at 16:35 UTC while one shard had several stalled nodes. The second period was set off by rolling the election protocol back to the previous minor version at 20:42 UTC.

   Root cause

   Software defect

   Component

   DatabaseDatabase failover manager

   Contributing factor

   Change with a delayed effectMonitoring blind spotExcessive blast radiusHarmful manual actionUnverified assumptionOverlapping failures

   Detection

   Automated monitoring detected the failed election within a minute, and the team was alerted at 16:36 UTC. The second period was announced at 21:14 UTC by automated alerts that some shards in the cluster were unavailable.

   Remediation

   • Restarted all nodes of the database cluster, which forced a successful primary election
   • Updated the production configuration and restarted the database cluster's nodes
   • Ramped traffic back up, putting services for user-initiated API requests first

   Action items

   • Alert when nodes stop reporting their replication lag
   • Alert when a shard enters a state that could trigger the election fault
   • Work with the database maintainers on a fix for the underlying fault
   • Add circuit breaking on failed operations to particular database clusters
   • Use fault isolation to contain the impact of a single failed shard
   • Limit the resources used by clients that keep retrying failed requests
   • Add procedures and tooling that make rapid configuration changes during incident response safer

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