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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11The AWS outage on Monday, October 20, 2025, began with a narrow but serious failure in Amazon DynamoDB’s automated DNS-management system in Northern Virginia, or us-east-1. A latent race condition allowed an older DNS plan to overwrite a newer one. Cleanup then deleted that active plan, leaving the regional DynamoDB endpoint with an empty DNS record.
That prevented new connections to dynamodb.us-east-1.amazonaws.com. The initial DynamoDB problem was largely repaired within about three hours, but dependent services continued to fail as leases expired, recovery queues accumulated, capacity launches stalled, and health checks removed otherwise usable infrastructure from service.
The outage began late Sunday and continued through Monday
The incident began at approximately 11:48 p.m. PDT on Sunday, October 19, 2025. The first customer-facing symptom was a rise in DynamoDB API errors in us-east-1.
AWS identified DynamoDB’s DNS state as the source by about 12:38 a.m. PDT. Some internal services had reconnected by approximately 1:15 a.m. AWS restored the endpoint’s DNS information by about 2:25 a.m., and cached DNS records expired between roughly 2:25 and 2:40 a.m., allowing customers to resolve the endpoint and reconnect.
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That was the end of the primary DynamoDB disruption—not the end of the broader AWS incident. AWS’s post-event summary places the event endpoint at approximately 2:20 p.m. PDT. Amazon’s public update said all AWS services were operating normally by 3:01 p.m. PDT. These are different recovery milestones, not necessarily contradictory times.
The failure was centered on Northern Virginia, but it affected customers and services elsewhere when their authentication, control-plane, monitoring, or application workflows depended on systems in that region.
What the DynamoDB DNS problem actually was
DNS translates a hostname into the network addresses a client should contact. When an application calls DynamoDB using its regional endpoint, it first needs to resolve a name such as:
dynamodb.us-east-1.amazonaws.comIn this incident, the initial problem was not described by AWS as database data corruption or data loss. The failure occurred in the automation that publishes and updates the DNS records directing clients to DynamoDB’s load balancers.
AWS maintains a large number of DynamoDB DNS records for regional, FIPS, IPv6, account-specific, and other endpoints. Its system includes:
- DNS Planner: monitors load-balancer health and capacity and creates DNS plans.
- DNS Enactor: applies those plans to Route 53.
Three independent Enactor instances operated across Availability Zones. The architecture was intended to provide redundancy, but an unusual timing interaction between the Enactors exposed a race condition.
It is important not to describe this as a worldwide Route 53 failure. AWS attributed the triggering defect to DynamoDB’s automated DNS-management system, which used Route 53 transactions. The affected endpoint was regional.
How the race condition left an empty endpoint
The failure involved two automation processes that were each behaving as designed under normal timing but interacted incorrectly when one process was delayed.
- The DNS Planner generated successive plans as it tracked capacity and health.
- One Enactor became unusually delayed while retrying updates.
- A different Enactor picked up and quickly applied a newer plan.
- The faster Enactor began cleaning up plans that it considered significantly older.
- The delayed Enactor later applied its old plan. Its earlier check that the plan was current was no longer valid by the time the update occurred.
- The old plan overwrote the newer plan for the regional DynamoDB endpoint.
- Cleanup then deleted the now-active old plan.
- The endpoint was left with no usable IP addresses and an inconsistent state.
- Normal automation could not repair that condition, so engineers had to intervene manually.
In simplified form:
Load-balancer health and capacity
↓
DNS Planner
↓
DNS plans
↓
Independent DNS Enactors
↓
Route 53 records
↓
dynamodb.us-east-1.amazonaws.comThe key issue was not simply that “a DNS record disappeared.” A delayed writer applied stale state after newer state had been published, and cleanup then removed the state that had become active. In distributed systems terms, the system lacked sufficient protection against a stale write becoming authoritative after its validation step had gone stale.
Why unrelated-looking AWS services failed
DynamoDB is used directly or indirectly by many AWS services. Once new connections to the regional DynamoDB endpoint failed, dependent systems began accumulating their own failures.
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EC2: existing instances versus new capacity
EC2’s DropletWorkflow Manager relied on DynamoDB to maintain leases for physical servers hosting EC2 instances.
Existing EC2 instances generally remained healthy. However, as lease renewals failed, leases gradually timed out. Once DynamoDB recovered, EC2 had to re-establish a large number of leases at once. That recovery workload accumulated faster than the system could process it, producing what AWS described as a congestive-collapse condition.
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Engineers throttled incoming work and selectively restarted DropletWorkflow Manager hosts. New EC2 launches recovered progressively, but a second backlog emerged while network configuration propagated to newly launched instances. AWS reported full EC2 recovery at approximately 1:50 p.m. PDT.
This distinction matters operationally: an application can appear healthy while existing servers run normally, yet fail when it needs to scale, replace an unhealthy node, roll back a deployment, or expand a cluster.
Network Load Balancer: health checks amplified the problem
Newly launched EC2 instances sometimes reached NLB health checks before their network state had fully propagated. Health results alternated between healthy and unhealthy.
NLB removed targets from service and later returned them when checks succeeded. That oscillation increased pressure on the health-check subsystem. Automatic Availability Zone DNS failover also removed capacity from service.
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This illustrates how a health mechanism can become an incident amplifier. A failed check does not always mean that an application or instance is permanently broken; it may reflect transient startup, network propagation, or dependency problems.
Lambda, SQS, and Kinesis
DynamoDB endpoint failures initially prevented some Lambda function creation and updates. SQS and Kinesis event-source processing was delayed.
A separate SQS polling subsystem did not recover automatically and required intervention. Later, NLB and EC2 capacity problems left some Lambda internal systems under-scaled. AWS throttled some asynchronous and event-source workloads to prioritize synchronous invocations and limit further overload.
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The result was a recovery problem as much as an availability problem: queued events, retries, and delayed polling had to be processed without overwhelming systems that were still rebuilding capacity.
STS, IAM, and console sign-in
STS errors initially improved after internal DynamoDB endpoints were restored, then experienced a second period of errors associated with NLB health-check failures.
IAM-user console sign-in was impaired because of dependencies on DynamoDB in us-east-1. Some customers outside Northern Virginia also encountered console sign-in problems when authentication flows depended on that region.
This is why a regional infrastructure failure can be felt globally. A service may be running in another region while its credentials, control-plane operations, or administrative interface depend on a different region.
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Redshift
Redshift cluster operations and queries in us-east-1 initially failed because Redshift relied on DynamoDB endpoints. Some clusters remained impaired after DynamoDB recovered because EC2 replacement workflows were still blocked.
A separate Redshift defect affected some queries in other regions when IAM-user credentials required an impaired IAM API in us-east-1. Customers using local Redshift users were unaffected by that specific cross-region credential issue.
Amazon Connect
Amazon Connect customers experienced problems with calls, chats, cases, dashboards, and agent sign-in. Some failures later reappeared because Connect depended on Lambda and NLB systems that remained impaired after the original DynamoDB DNS fault had been repaired.
ECS, EKS, Fargate, and other services
Container and orchestration operations, including launches or scaling in the region, were affected when they depended on impaired EC2, networking, authentication, or other control-plane systems. Amazon.com, Amazon subsidiaries, and AWS Support operations were also affected during the incident.
Why repairing DynamoDB did not immediately restore AWS
Restoring the authoritative DNS record repaired the initiating fault. It did not instantly restore the state that dependent systems had accumulated while DynamoDB was unreachable.
The recovery chain included:
- DNS repair: The DynamoDB endpoint became usable again, subject to DNS-cache expiration.
- Lease recovery: EC2 had to re-establish a large number of leases that had expired.
- Backlog pressure: Recovery work accumulated faster than internal systems could process it.
- Protective throttling: AWS limited incoming work to prevent further overload.
- Network propagation: Newly launched instances were not immediately ready for all downstream checks.
- Health-check oscillation: NLBs alternated between adding and removing targets.
- Secondary backlogs: Lambda, SQS, Redshift, Connect, and other services needed time or manual intervention to converge.
This is a classic failure-amplification and recovery-amplification pattern. A short-lived initiating fault can produce a much longer customer-impact window when dependent systems lose leases, queue work, make incorrect health decisions, or enter protective throttling states.
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DNS caching also matters. Repairing an authoritative record does not instantly change every recursive resolver, operating-system cache, SDK, connection pool, or application-level resolver. An application may continue failing after the record is repaired, and DNS failover is not the same as failing over already-open connections.
What was affected—and what was not universally affected
| Area | Observed impact or qualification |
|---|---|
| DynamoDB | New connections through the affected us-east-1 regional endpoint failed until DNS state was restored and caches expired. |
| Existing EC2 instances | Existing instances launched before the event generally remained healthy. |
| New EC2 capacity | Launches and replacement workflows were impaired while leases and network state recovered. |
| NLB | Health-check instability and automatic failover removed capacity from service. |
| Lambda | Some management operations, invocation capacity, and event-source processing were delayed or impaired. |
| STS and IAM | Authentication and credential-dependent workflows experienced errors, including some console sign-ins outside the region. |
| Redshift | Cluster operations and some queries were affected; local Redshift users avoided one IAM-dependent cross-region failure mode. |
| Amazon Connect | Calls, chats, cases, dashboards, and agent sign-in were affected. |
| DynamoDB global tables | Replicas in other regions remained accessible, but replication involving us-east-1 experienced lag. AWS said replicas fully caught up by approximately 2:32 a.m. PDT. |
| Other AWS regions | Some workloads were indirectly affected by centralized authentication or control-plane dependencies; the incident was not a total failure of every AWS region or service. |
What this means for cloud architecture
Multi-region does not automatically mean multi-region
A workload may have data replicas in several regions while still depending on one region for IAM, STS, deployment tooling, DNS, monitoring, or control-plane operations.
Separate three kinds of resilience:
- Data-plane resilience: existing application traffic and data operations continue.
- Control-plane resilience: new instances, scaling, configuration changes, deployments, and credentials continue.
- Operational resilience: engineers can observe and change the system during the incident.
DynamoDB global tables can help preserve regional data access, but they do not automatically make compute launches, authentication, queues, deployment systems, or failover routing independent of the impaired region.
Pre-provisioned capacity can matter
If new EC2 instances, ECS tasks, EKS nodes, or Fargate tasks cannot be launched, an application that relies entirely on just-in-time capacity may have no immediate recovery path.
Teams should test replacement of a failed instance, Auto Scaling, node-group expansion, task placement, Lambda concurrency recovery, deployment rollback, and failover while regional APIs or control-plane services are impaired. In some cases, retaining standby capacity is more expensive but materially reduces dependence on new launches during an outage.
Retries need limits
A service outage can become a retry storm. Use exponential backoff with jitter, bounded retry budgets, circuit breakers, queue limits, load shedding, and deliberate backlog-draining strategies.
A recovery plan should specify not only how to fail over, but also how quickly queued work may be released after the dependency returns. Uncontrolled recovery traffic can recreate the failure.
Health checks need safeguards
Use startup grace periods, separate readiness and liveness checks, hysteresis, sensible failure thresholds, capacity floors, and limits on how much capacity automated failover may remove at once.
Health-check behavior should be tested during partial network propagation, slow dependency recovery, and mixed healthy/unhealthy states—not only during a clean instance failure.
Monitoring must survive the incident
If monitoring depends on the same region, credentials, DNS path, or AWS services that are impaired, it may disappear when it is most needed.
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A layered setup should include:
- External synthetic DNS and HTTPS probes.
- Independent monitoring accounts or providers.
- Cross-region log and metric replication.
- Alerts based on successful business transactions, not only infrastructure metrics.
- A provider-independent incident communication channel.
- Runbooks that do not require the impaired AWS console.
The AWS Health documentation says the public service health view is available without an AWS account, while account-specific health information requires sign-in. Teams should not assume every operational view will remain equally accessible during an authentication or regional control-plane problem.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.A practical checklist for AWS customers
- Map every dependency on
us-east-1, including IAM, STS, DNS, deployment, authentication, and monitoring paths. - Test whether existing workloads survive when new capacity cannot be launched.
- Test replacing an EC2 instance during regional API impairment.
- Validate DynamoDB global-table replication lag, conflict handling, routing, and failover procedures.
- Use external DNS and HTTPS probes.
- Alert on successful reads, writes, logins, checkouts, calls, or other business transactions.
- Configure exponential backoff, jitter, bounded retries, and circuit breakers.
- Limit automated health-check-driven capacity removal.
- Keep emergency credentials and runbooks available outside the affected region.
- Practice recovery from backlogs, not merely regional failover.
- Decide which workloads genuinely require multi-region operation and which only have multi-region backups.
Where observability and failover products fit
The incident has a legitimate technology-spending lesson, but no monitoring or DNS product would by itself have prevented AWS’s internal DynamoDB race condition. These tools address different customer risks:
| Risk | Relevant category | Examples and qualification |
|---|---|---|
| Customers cannot distinguish DNS, connection, and application failure | External synthetic monitoring | Route 53 health checks or independent synthetic probes can test real endpoints. |
| Monitoring depends on the impaired AWS region | Independent observability | Datadog or New Relic can provide a monitoring plane outside a single AWS control-plane path. |
| Regional endpoint failure | DNS health checks and failover | Route 53 supports authoritative DNS, health checks, and routing policies, but DNS does not resolve application state or open connections. |
| Regional data-plane disruption | Multi-region database architecture | DynamoDB global tables provide replicas, but teams still need routing, conflict, authentication, and recovery procedures. |
| New capacity cannot be launched | Standby capacity and tested recovery | Observability cannot replace pre-provisioned capacity or a working control-plane strategy. |
| Retry storms and backlog growth | Queue controls and load management | Backoff, throttling, circuit breakers, and bounded recovery releases are architectural controls. |
| Hidden dependencies | Tracing and dependency mapping | Distributed tracing and service maps can reveal regional authentication or control-plane assumptions. |
For AWS-native teams, CloudWatch offers metrics, logs, alarms, dashboards, and synthetic monitoring with pay-as-you-go pricing. AWS lists a free tier that includes 5 GB of log data, 10 custom or detailed metrics, three custom dashboards, and 10 standard alarm metrics, with pricing varying by region. CloudWatch is a strong integration choice, but it should not be the only monitoring layer during an AWS regional incident.
Route 53 supports DNS and health-check-based failover. AWS lists hosted zones at $0.50 per month for the first 25 zones, standard DNS queries at $0.50 per million for the first billion queries per month, and basic health checks at $0.50 per health check per month for AWS endpoints. Actual costs depend on usage and configuration.
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Datadog provides provider-independent infrastructure monitoring, tracing, logs, synthetic checks, real-user monitoring, and dependency mapping. Its pricing is usage-based; the published page lists APM starting at $31 per host per month when billed annually and RUM Measure starting at $0.15 per 1,000 sessions per month when billed annually. High telemetry volume can make it expensive.
New Relic offers full-stack observability, logs, APM, tracing, and synthetic monitoring. Its published pricing includes 100 GB of data ingest per month in the free tier, with original data ingest listed at $0.40 per GB beyond that allowance on Standard and Pro plans, and $0.60 per GB on Data Plus. Teams should budget for ingest growth.
These products can improve detection, independent visibility, and failover management. None substitutes for tested regional recovery, capacity planning, dependency isolation, or controlled backlog recovery.
What the incident does—and does not—prove
It is too broad to say that DynamoDB “took down all of AWS” or that the incident literally took down the internet. The accurate description is a major disruption centered on us-east-1 that propagated through service dependencies and affected many internet-facing applications.
It is also inaccurate to reduce the event to “just a DNS outage.” The important mechanism was the interaction between delayed and fast Enactors, stale plan validation, cleanup, and an inconsistent endpoint state.
Nor does the event prove that another cloud provider or a multi-cloud design would automatically have prevented the outage. Multi-cloud can reduce concentration risk, but it introduces additional operational complexity, data-consistency challenges, duplicated tooling, and cost. The defensible lesson is narrower: understand provider and regional dependencies, then test the failure modes that matter to the business.
AWS’s supplied post-event summary explains the failure and recovery but does not provide a complete list of permanent engineering changes. Specific claims about code changes, new tests, or permanent safeguards should therefore not be inferred from the incident mechanics alone.
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