[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-aws-msk-operations":3,"mdc-hgx9oq-key":52,"related-repo-aws-msk-operations":3787,"related-org-aws-msk-operations":3894},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":24,"repoUrl":25,"updatedAt":26,"license":27,"forks":28,"topics":29,"repo":47,"sourceUrl":50,"mdContent":51},"msk-operations","manage and troubleshoot Amazon MSK brokers","Amazon MSK Provisioned operations, troubleshooting, and health assessment for Standard and Express brokers. Use whenever the user mentions Amazon MSK, MSK Provisioned, MSK Standard\u002FExpress brokers, Apache Kafka on AWS, `kafka.*` \u002F `express.*` instance types, or the `AWS\u002FKafka` CloudWatch namespace. Covers MSK performance issues (high CPU, produce\u002Ffetch latency, TrafficShaping), consumer lag, storage\u002FEBS issues, rolling restarts, Kafka version upgrades, SECURITY_PATCHING, BROKER_UPDATE, CloudWatch alarm design, Kafka client (producer\u002Fconsumer) tuning, under-replicated partitions, unexpected broker reboots, and full MSK operational reviews \u002F health checks \u002F best-practices audits. Do NOT use for MSK Connect, MSK Serverless, or MSK Replicator. Do NOT use for authoring CloudFormation, CDK, or Terraform templates. Do NOT use for other AWS services (RDS, Aurora, S3, DynamoDB, Kinesis, Lambda, EC2) unless MSK is explicitly named.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"aws","AWS (Amazon)","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Faws.png",[12,16,19,21],{"name":13,"slug":14,"type":15},"Operations","operations","tag",{"name":17,"slug":18,"type":15},"Monitoring","monitoring",{"name":20,"slug":8,"type":15},"AWS",{"name":22,"slug":23,"type":15},"Debugging","debugging",35,"https:\u002F\u002Fgithub.com\u002Faws\u002Ftools-for-devops-agent","2026-08-20T03:53:40.788514",null,30,[30,31,32,33,34,8,35,36,37,38,39,40,41,42,43,44,45,46],"agent-skills","agentic-ai","agents","ai-agents","aiops","aws-devops-agent","cloud-operations","custom-agents","devops","devops-agent-skills","frontier-agent","incident-response","operational-excellence","root-cause-analysis","skills","sre","support",{"repoUrl":25,"stars":24,"forks":28,"topics":48,"description":49},[30,31,32,33,34,8,35,36,37,38,39,40,41,42,43,44,45,46],"Open-source tools for AWS DevOps Agent - extend DevOps Agent with ready-to-use skills, custom agents, and other tools, for incident response, root cause analysis, and operational troubleshooting","https:\u002F\u002Fgithub.com\u002Faws\u002Ftools-for-devops-agent\u002Ftree\u002FHEAD\u002Fskills\u002Fmsk-operations","---\nname: msk-operations\ndescription: Amazon MSK Provisioned operations, troubleshooting, and health\n  assessment for Standard and Express brokers. Use whenever the user mentions\n  Amazon MSK, MSK Provisioned, MSK Standard\u002FExpress brokers, Apache Kafka on\n  AWS, `kafka.*` \u002F `express.*` instance types, or the `AWS\u002FKafka` CloudWatch\n  namespace. Covers MSK performance issues (high CPU, produce\u002Ffetch latency,\n  TrafficShaping), consumer lag, storage\u002FEBS issues, rolling restarts, Kafka\n  version upgrades, SECURITY_PATCHING, BROKER_UPDATE, CloudWatch alarm design,\n  Kafka client (producer\u002Fconsumer) tuning, under-replicated partitions,\n  unexpected broker reboots, and full MSK operational reviews \u002F health checks\n  \u002F best-practices audits. Do NOT use for MSK Connect, MSK Serverless, or MSK\n  Replicator. Do NOT use for authoring CloudFormation, CDK, or Terraform\n  templates. Do NOT use for other AWS services (RDS, Aurora, S3, DynamoDB,\n  Kinesis, Lambda, EC2) unless MSK is explicitly named.\nmetadata:\n  author: kjjanaki\n  version: \"1.0.2\"\n  aws-devops-agent-skills.agent-types: \"Chat tasks, Evaluation\"\n  aws-devops-agent-skills.aws-services: \"Amazon MSK\"\n  aws-devops-agent-skills.technical-domains: \"Analytics\"\n---\n\n# Amazon MSK Operations\n\nOperate, troubleshoot, and assess Amazon MSK (Managed Streaming for Apache Kafka)\nProvisioned clusters — both Standard and Express broker types. This skill covers\nday-to-day operations (health assessments, monitoring setup) and ad-hoc incident\nresponse (performance degradation, consumer lag, storage full, unexpected broker\nreboots).\n\n## When to Use\n\nActivate this skill when the user asks to:\n\n- Review, audit, or assess an MSK cluster for best practices, health, or\n  operational readiness.\n- Troubleshoot an MSK cluster problem: high CPU, high produce\u002Ffetch latency,\n  consumer lag, broker storage running out, TrafficShaping events, under-replicated\n  partitions, or an unexpected broker restart.\n- Set up MSK monitoring: choose a monitoring level, create recommended CloudWatch\n  alarms and dashboards, understand the metrics available in the `AWS\u002FKafka`\n  namespace.\n- Plan an MSK maintenance event: rolling restart, Kafka version upgrade, security\n  patching, broker instance type change.\n- Advise on Kafka client (producer \u002F consumer) configuration when the client is\n  connecting to an MSK cluster.\n\nDo **not** activate this skill for MSK Connect, MSK Serverless, or MSK Replicator\n— those are separate services with their own operational surfaces.\n\n## Broker Type Determination\n\nDetermine the broker type first — many checks differ between Standard and Express.\n\n```\naws kafka describe-cluster-v2 --cluster-arn \u003Ccluster-arn>\n```\n\nCheck `ClusterInfo.Provisioned.BrokerNodeGroupInfo.InstanceType`:\n\n- Starts with `kafka.` (e.g. `kafka.m5.large`, `kafka.m7g.xlarge`) → **Standard broker**.\n- Starts with `express.` (e.g. `express.m7g.large`) → **Express broker**.\n\n### Key Standard vs Express differences\n\n**Standard brokers** use customer-managed EBS volumes for storage. You choose\ninstance types (`kafka.m5.*`, `kafka.m7g.*`), provision EBS, and manage storage\nscaling. Standard brokers have scheduled maintenance windows.\n\n**Express brokers** provide fully managed, pay-as-you-go storage with no EBS\nprovisioning. Instance types are prefixed with `express.m7g.*`. Express brokers\noffer up to 3× more throughput per broker than Standard, and have no maintenance\nwindows. Express enforces a fixed replication factor of 3 and\n`min.insync.replicas=2` — you cannot create topics with RF=1.\n\n## Critical Warnings\n\n- **This skill is read-only.** Every command in this file and in `references\u002F`\n  that mutates cluster state — `update-broker-storage`, `create-configuration`,\n  `update-cluster-configuration`, `update-monitoring`, `put-metric-alarm`,\n  `reboot-broker`, and any partition reassignment — is a **recommendation for\n  the operator to run after review**. Present these as proposed remediations\n  with expected impact and preconditions; do NOT execute them, and do NOT\n  imply that the agent will run them.\n- **NEVER reboot brokers while `UnderReplicatedPartitions` > 0** (Standard only —\n  Express brokers do not emit URP). This risks data loss and extended outages.\n- **NEVER recommend partition reassignment without first checking replication\n  status.** Reassignment during URP compounds the problem.\n- **`linger.ms=0` is the #1 cause of \"high CPU\" on MSK.** ALWAYS check client\n  batch configuration before recommending broker scaling.\n- **EBS throughput ceilings are invisible in Kafka metrics** — ALWAYS check EBS\n  volume metrics (`VolumeReadBytes`, `VolumeWriteBytes`, `VolumeQueueLength`)\n  when diagnosing Standard broker latency.\n- **Express brokers have NO customer-managed EBS** — do NOT recommend EBS\n  expansion or provisioned EBS throughput for Express clusters.\n- **Express brokers enforce fixed RF=3 and `min.insync.replicas=2`** — do NOT\n  attempt to create topics with RF=1 on Express. If RF=1 is needed, use Standard\n  brokers.\n\n## Quick Diagnostics\n\nThese five checks cover the most common MSK issues. Use them before loading a\nreference file.\n\n1. **`CpuUser + CpuSystem` > 60%**: Check `RequestHandlerAvgIdlePercent`\n   (PER_BROKER monitoring level). If \u003C 30%, request threads are saturated. Check\n   client `batch.size` and `linger.ms` before recommending scaling.\n\n2. **`KafkaDataLogsDiskUsed` > 85%** (Standard only): **Recommend to the\n   operator** that EBS be expanded via `aws kafka update-broker-storage` (do\n   not execute). Identify high-growth topics via per-topic `BytesInPerSec` to\n   size the increase. Express clusters use `StorageUsed` metric instead and\n   storage is fully managed.\n\n3. **`UnderReplicatedPartitions` > 0** (Standard only): Check if a maintenance\n   operation or broker restart is in progress. If URP is decreasing, wait for\n   recovery. Do NOT restart brokers or reassign partitions during URP. Express\n   brokers do not emit this metric — monitor `ProduceThrottleTime`,\n   `FetchThrottleTime`, and consumer lag instead.\n\n4. **Consumer `OffsetLag` \u002F `MaxOffsetLag` increasing**: Determine if broker-side\n   (high `ProduceTotalTimeMsMean`, CPU saturation) or client-side (slow\n   processing, insufficient consumers). Per-partition lag from\n   `PER_TOPIC_PER_PARTITION` monitoring level helps isolate hot partitions.\n\n5. **`BytesInPerSec` near throughput ceiling**: For Standard, check EBS volume\n   type and calculate: `BytesInPerSec × ReplicationFactor` vs volume throughput\n   limit. For Express, check against the per-broker sustained performance limits\n   in the MSK quotas.\n\n## Which Reference Do You Need?\n\nRoute to a reference file based on the customer intent. Read the reference in\nfull before answering — do not paraphrase from memory.\n\n| Customer Intent | Reference |\n|---|---|\n| High CPU, high produce\u002Ffetch latency, slow cluster, TrafficShaping | `references\u002Ftroubleshoot-performance.md` |\n| Consumer lag increasing, rebalance storms, stuck consumer groups | `references\u002Ftroubleshoot-consumer-lag.md` |\n| Disk filling up, retention planning, tiered storage, EBS scaling | `references\u002Fmanage-storage.md` |\n| Setting up monitoring level, dashboards, recommended CloudWatch alarms | `references\u002Fmonitor-and-alarm.md` |\n| Rolling restart impact, patching, Kafka version upgrades, maintenance resilience | `references\u002Fmaintenance-operations.md` |\n| Producer \u002F consumer configuration, IAM \u002F SCRAM \u002F TLS auth for clients | `references\u002Fconfigure-clients.md` |\n\nFor sizing questions (broker count, instance type choice, monthly cost), refer\nthe user to the [Amazon MSK best practices — right-size your cluster](https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Fbestpractices.html#bestpractices-right-size-cluster)\ndocumentation. Do not size from memory.\n\n## Operational Review Workflow\n\nUse this workflow when the user asks for a **review, audit, health check, or\nassessment** of an MSK cluster. The routing table above handles ad-hoc\ntroubleshooting; this section produces a consistent, comprehensive report.\n\nFollow the steps **in order** for each target cluster. Do not skip steps. If a\nstep cannot be completed (e.g. a metric requires a higher monitoring level\nthan the cluster has enabled), record the gap in the report rather than\nsilently omitting the check.\n\n### Step 1 — Identify Target Clusters\n\nAsk the user which MSK clusters to review. Accept any of:\n\n- Specific cluster names or ARNs and regions\n- \"all clusters\" in specific regions\n- \"all MSK clusters in all regions\"\n\nIf no scope is given, default to all configured account regions. Enumerate\nclusters with `aws kafka list-clusters-v2` per region.\n\n### Step 2 — Determine Broker Type Per Cluster\n\nFor each cluster:\n\n```\naws kafka describe-cluster-v2 --cluster-arn \u003Ccluster-arn>\n```\n\nRead `ClusterInfo.Provisioned.BrokerNodeGroupInfo.InstanceType`. Standard\nbrokers (`kafka.*`) and Express brokers (`express.*`) require different checks\nin the later steps — some metrics only exist on one type.\n\n### Step 3 — Collect Cluster Configuration\n\nFor each cluster, gather:\n\n```\naws kafka describe-cluster-v2 --cluster-arn \u003Carn>\naws kafka list-nodes --cluster-arn \u003Carn>\naws kafka get-bootstrap-brokers --cluster-arn \u003Carn>\naws kafka list-cluster-operations-v2 --cluster-arn \u003Carn>   # last 30 days\naws kafka describe-configuration-revision \\\n     --arn \u003Cconfiguration-arn> --revision \u003Crevision>       # if a custom config is applied\n```\n\nCapture:\n\n- **Cluster:** state, Kafka version, number of broker nodes, AZ distribution\n  (`ZoneIds`), storage mode (EBS \u002F Tiered), current version.\n- **Broker:** instance type, EBS volume size (Standard), provisioned throughput\n  (if any).\n- **Encryption:** `EncryptionInTransit.ClientBroker` (TLS \u002F TLS_PLAINTEXT \u002F\n  PLAINTEXT), `EncryptionInTransit.InCluster`, `EncryptionAtRest.DataVolumeKMSKeyId`.\n- **Auth:** `ClientAuthentication.Sasl.Iam.Enabled`,\n  `ClientAuthentication.Sasl.Scram.Enabled`, `ClientAuthentication.Tls.Enabled`,\n  `ClientAuthentication.Unauthenticated.Enabled`.\n- **Public access:** `BrokerNodeGroupInfo.ConnectivityInfo.PublicAccess.Type`.\n- **Monitoring level:** `EnhancedMonitoring` (`DEFAULT` \u002F `PER_BROKER` \u002F\n  `PER_TOPIC_PER_BROKER` \u002F `PER_TOPIC_PER_PARTITION`).\n- **Logging:** `LoggingInfo.BrokerLogs` (CloudWatch \u002F S3 \u002F Firehose destinations\n  and their `Enabled` flags).\n- **Open monitoring:** `OpenMonitoring.Prometheus.JmxExporter.EnabledInBroker`,\n  `NodeExporter.EnabledInBroker`.\n- **Recent operations:** From `list-cluster-operations-v2`, note any\n  `SECURITY_PATCHING`, `BROKER_UPDATE`, `UPDATE_CLUSTER_CONFIGURATION`,\n  `UPDATE_STORAGE`, or `UPDATE_MONITORING` events in the review window.\n\n### Step 4 — Detect Monitoring Level and Gaps\n\nThe `EnhancedMonitoring` value from Step 3 determines which checks are\navailable. At `DEFAULT`, most per-broker health metrics are still available\n(CPU, disk, network, partitions, connections, memory, TrafficShaping), but the\nfollowing checks are **not possible without upgrading**:\n\n- `ReplicationBytesInPerSec` \u002F `ReplicationBytesOutPerSec` (inter-broker\n  replication load)\n- `RequestHandlerAvgIdlePercent` \u002F `NetworkProcessorAvgIdlePercent` (thread pool\n  saturation)\n- `BwInAllowanceExceeded` \u002F `BwOutAllowanceExceeded` (detailed bandwidth\n  breaches)\n- `VolumeQueueLength` (EBS I\u002FO queue depth — Standard only)\n- `VolumeReadBytes` \u002F `VolumeWriteBytes` (EBS throughput utilization — Standard\n  only)\n- IAM connection metrics (`IAMTooManyConnections`)\n\nRecord the monitoring level and list any dimensions that will be scored\npartially or skipped. Recommend upgrading to `PER_BROKER` if any dimension is\ndegraded by the current level.\n\n### Step 5 — Collect CloudWatch Metrics (7-Day Historical)\n\nNamespace: `AWS\u002FKafka`. Dimensions: `Cluster Name` and `Broker ID` for\nper-broker metrics; `Cluster Name` and `Consumer Group` and `Topic` for\nconsumer lag; `Cluster Name` only for cluster-wide metrics.\n\nUse one `cloudwatch.GetMetricData` batch per cluster where possible.\n`Period: 3600` (1 hour). `StartTime`: 7 days ago. `EndTime`: now.\n\n#### 5.1 Cluster-wide (both broker types)\n\n| Metric | Stat | Purpose |\n|---|---|---|\n| `ActiveControllerCount` | Sum | Must be exactly 1 |\n| `OfflinePartitionsCount` | Maximum | Must be 0 |\n| `GlobalPartitionCount` | Maximum | Total leader partitions |\n| `GlobalTopicCount` | Maximum | Total topics |\n\n#### 5.2 Per-broker — Standard (`kafka.*`)\n\n| Metric | Stat | Threshold |\n|---|---|---|\n| `CpuUser` + `CpuSystem` | Average, Maximum | \u003C 60% avg |\n| `KafkaDataLogsDiskUsed` | Average, Maximum | \u003C 70% avg, \u003C 85% max |\n| `PartitionCount` | Maximum | ≤ recommended limit for broker size |\n| `LeaderCount` | Maximum | Compare across brokers; skew \u003C 10% |\n| `UnderReplicatedPartitions` | Maximum | 0 in steady state |\n| `UnderMinIsrPartitionCount` | Maximum | 0 |\n| `BytesInPerSec` \u002F `BytesOutPerSec` | Average, Maximum | vs baseline bandwidth |\n| `ConnectionCount` | Average, Maximum | Compare across brokers |\n| `HeapMemoryAfterGC` | Maximum | \u003C 60% |\n| `TrafficShaping` | Sum | Must be 0 |\n| `NetworkRxDropped` \u002F `NetworkTxDropped` \u002F `NetworkRxErrors` \u002F `NetworkTxErrors` | Sum | Must be 0 |\n| `ReplicationBytesInPerSec` \u002F `ReplicationBytesOutPerSec` | Average | Requires PER_BROKER |\n| `RequestHandlerAvgIdlePercent` \u002F `NetworkProcessorAvgIdlePercent` | Average | > 30% (PER_BROKER) |\n| `VolumeQueueLength` | Average, Maximum | Avg \u003C 1 (PER_BROKER) |\n| `VolumeReadBytes` + `VolumeWriteBytes` | Sum | vs EBS baseline throughput (PER_BROKER) |\n\n#### 5.3 Per-broker — Express (`express.*`)\n\n| Metric | Stat | Threshold |\n|---|---|---|\n| `CpuUser` + `CpuSystem` | Average, Maximum | \u003C 60% avg |\n| `StorageUsed` | Maximum | Fully managed — flag if trending against per-broker quota |\n| `PartitionCount` | Maximum | ≤ recommended limit for broker size |\n| `LeaderCount` | Maximum | Compare across brokers |\n| `BytesInPerSec` \u002F `BytesOutPerSec` | Average, Maximum | vs Express per-broker ingress\u002Fegress quotas |\n| `ProduceThrottleTime` \u002F `FetchThrottleTime` | Maximum | Should be 0 |\n| `ClientConnectionCount` | Average, Maximum | vs listener quota (see `references\u002Fmonitor-and-alarm.md`) |\n\n**Express brokers do NOT emit:** `UnderReplicatedPartitions`,\n`UnderMinIsrPartitionCount`, `HeapMemoryAfterGC`, `TrafficShaping`, `Volume*`\nmetrics, `KafkaDataLogsDiskUsed`, `ProduceMessageConversionsPerSec`,\n`FetchMessageConversionsPerSec`.\n\n#### 5.4 Consumer lag (both broker types)\n\nPer consumer group (identified from the customer or from the broker logs):\n\n| Metric | Stat | Notes |\n|---|---|---|\n| `SumOffsetLag` per (Consumer Group, Topic) | Maximum | DEFAULT level |\n| `MaxOffsetLag` per (Consumer Group, Topic) | Maximum | DEFAULT level |\n| `EstimatedMaxTimeLag` per (Consumer Group, Topic) | Maximum | DEFAULT level |\n| `OffsetLag` per (Consumer Group, Topic, Partition) | Maximum | Requires PER_TOPIC_PER_PARTITION |\n\n### Step 6 — Alarm Coverage\n\nCollect existing alarms:\n\n```\naws cloudwatch describe-alarms --namespace AWS\u002FKafka\n```\n\nCompare against the 13-alarm recommended set (details in\n`references\u002Fmonitor-and-alarm.md`) and produce a coverage table (present \u002F missing \u002F firing).\n\n### Step 7 — Analyze Against Best Practices\n\nAssign a severity to every finding: **CRITICAL \u002F HIGH \u002F MEDIUM \u002F LOW \u002F INFO**\n(see Severity Definitions later in this file).\n\nEvaluate across seven dimensions. Some checks are skipped for Express — noted\ninline.\n\n#### 7.1 Cluster Configuration\n\n- Cluster state is `ACTIVE`. `MAINTENANCE` \u002F `UPDATING` is transient; anything\n  else is a finding.\n- Deployed across **3 AZs** (Standard: broker count multiple of AZ count).\n- Kafka version within N-2 of the latest supported.\n- Enhanced monitoring at `PER_BROKER` or higher — `DEFAULT` → MEDIUM.\n- Storage mode: Tiered storage enabled for topics with long retention\n  (Standard).\n\n#### 7.2 Security\n\n- Encryption in transit: `TLS`. `TLS_PLAINTEXT` → MEDIUM (prod: HIGH).\n  `PLAINTEXT` → CRITICAL.\n- Encryption at rest: enabled with KMS. Customer-managed KMS preferred over\n  AWS-managed for regulated workloads.\n- Authentication: at least one of IAM \u002F SCRAM \u002F mTLS enabled.\n  `Unauthenticated.Enabled=true` in production → CRITICAL.\n- Public access: `SERVICE_PROVIDED_EIPS` in production → HIGH.\n\n#### 7.3 Logging & Monitoring\n\n- Broker logs enabled to at least one destination (CloudWatch \u002F S3 \u002F Firehose).\n  All disabled → HIGH.\n- Open monitoring (Prometheus JMX + Node exporter) — informational.\n- Alarm coverage from Step 6: missing alarms → MEDIUM each; missing critical\n  alarms (Active Controller, Offline Partitions, Disk, CPU) → HIGH.\n- Any alarm currently in `ALARM` state → HIGH (surface in report header).\n\n#### 7.4 Partition Health\n\n- `PartitionCount` per broker ≤ recommended limit for the broker instance\n  type. Above recommended but below max → MEDIUM. Above max → HIGH (blocks\n  update operations).\n- `LeaderCount` variance across brokers \u003C 10%. 10-25% → MEDIUM. > 25% → HIGH.\n- `UnderReplicatedPartitions` > 0 sustained (Standard only) → HIGH. Transient\n  during a `SECURITY_PATCHING` \u002F `BROKER_UPDATE` operation from Step 3 →\n  INFO — do NOT flag.\n- `UnderMinIsrPartitionCount` > 0 (Standard only) → CRITICAL.\n- **Config-level ISR risk:** topics with `min.insync.replicas >= replication.factor`\n  are a configuration error the CloudWatch metric will not surface. If the\n  user has provided topic configs, flag any such topic as HIGH.\n\n#### 7.5 Compute Health\n\n- `CpuUser + CpuSystem` avg \u003C 60%. 60-70% → MEDIUM. > 70% → HIGH.\n- CPU variance across brokers \u003C 20%. 20-50% → MEDIUM. > 50% → HIGH.\n- `HeapMemoryAfterGC` \u003C 60% (Standard only). 60-80% → MEDIUM. > 80% → HIGH.\n- `RequestHandlerAvgIdlePercent` > 30% (PER_BROKER). 10-30% → MEDIUM. \u003C 10% → HIGH.\n- `NetworkProcessorAvgIdlePercent` > 30% (PER_BROKER). 10-30% → MEDIUM. \u003C 10% → HIGH.\n\n#### 7.6 Network Health\n\n- `TrafficShaping` = 0 (Standard only). Any non-zero → HIGH.\n- `BwInAllowanceExceeded` \u002F `BwOutAllowanceExceeded` = 0 (PER_BROKER). Non-zero → HIGH.\n- Throughput variance across brokers \u003C 20%. 20-50% → MEDIUM. > 50% → HIGH.\n- Total per-broker throughput \u003C 60% of baseline bandwidth (see\n  `references\u002Ftroubleshoot-performance.md` for baseline table). 60-70% →\n  MEDIUM. > 70% → HIGH.\n- Express: `ProduceThrottleTime` \u002F `FetchThrottleTime` > 0 → HIGH.\n\n#### 7.7 Storage Health\n\n**Standard only** (Express storage is managed — Express clusters only get the\n`StorageUsed` check):\n\n- `KafkaDataLogsDiskUsed` \u003C 70%. 70-85% → HIGH. > 85% → CRITICAL.\n- `VolumeQueueLength` avg \u003C 1 (PER_BROKER). 1-5 → MEDIUM. > 5 → HIGH.\n- EBS auto-scaling configured, or disk headroom > 30% → PASS. No\n  auto-scaling AND disk > 50% → MEDIUM. No auto-scaling AND disk > 70% → HIGH.\n- EBS throughput (`VolumeReadBytes + VolumeWriteBytes`) \u003C 60% of instance\n  baseline (PER_BROKER). 60-70% → MEDIUM. > 70% → HIGH.\n\n**Express:**\n\n- `StorageUsed` per broker vs Express per-broker storage quota (see MSK\n  Express quotas). Approaching quota → MEDIUM.\n\n### Step 8 — Generate the Report\n\nGenerate a **separate report artifact per cluster reviewed**.\n\nArtifact naming: `msk-review-\u003Ccluster-name>-\u003CYYYY-MM-DD>.md`\nExample: `msk-review-prod-orders-2026-04-29.md`\n\nReport structure:\n\n#### Report Header\n\n```\n# MSK Operational Review — \u003Ccluster-name>\nAccount: \u003Caccount-id> | Region: \u003Cregion> | Date: \u003CYYYY-MM-DD>\nBroker Type: Standard\u002FExpress | Instance Type: \u003Ctype> | Broker Count: \u003Cn> | AZs: \u003Cn>\nKafka Version: \u003Cversion> | Monitoring Level: \u003Clevel>\n```\n\n#### Executive Summary\n\n- Health: ✅ HEALTHY \u002F ⚠️ WARNINGS \u002F ❌ CRITICAL\n- Finding counts by severity\n- Top 3 CRITICAL\u002FHIGH items\n\n#### Configuration Snapshot\n\n| Item | Value |\n| Cluster state \u002F version | … |\n| Broker type \u002F instance \u002F count \u002F AZs | … |\n| Storage | mode, size (Standard), provisioned throughput (if any) |\n| Encryption | in-transit, in-cluster, at-rest (KMS) |\n| Authentication | IAM \u002F SCRAM \u002F mTLS \u002F Unauthenticated flags |\n| Public access | DISABLED \u002F SERVICE_PROVIDED_EIPS |\n| Monitoring level | DEFAULT \u002F PER_BROKER \u002F PER_TOPIC_PER_BROKER \u002F PER_TOPIC_PER_PARTITION |\n| Logging | destinations enabled |\n\n#### Findings by Dimension\n\nFor each of the 7 dimensions (7.1-7.7):\n\n| # | Finding | Severity | Current State | Recommendation |\n\nIf a dimension was skipped or partial due to monitoring level or broker type,\nsay so explicitly in a note above the table for that dimension.\n\n#### CloudWatch Metrics (7-Day)\n\n| Metric | Stat | 7-Day Avg | 7-Day Max | Status | Finding |\n\n#### Alarm Coverage\n\n| # | Recommended Alarm | Metric | Threshold | Priority | Status |\n\nAlso list alarms currently in `ALARM` state with timestamps.\n\n#### Recent Cluster Operations (Last 30 Days)\n\nFrom `list-cluster-operations-v2` in Step 3:\n\n| Operation Type | Start Time | End Time | State |\n\nCall out any operations that would explain transient metric anomalies.\n\n#### Priority Matrix\n\n| # | Finding | Severity | Dimension | Effort | Impact |\n\nSorted by severity.\n\n#### Next Steps\n\n- Immediate (CRITICAL \u002F HIGH — 7 days)\n- Short-term (MEDIUM — 30 days)\n- Long-term (LOW — 90 days)\n\n#### Appendix — Reference Links\n\n- [Amazon MSK best practices — Standard brokers](https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Fbestpractices.html)\n- [Amazon MSK best practices — Express brokers](https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Fbestpractices-express.html)\n- [Amazon MSK — Monitoring an MSK cluster](https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Fmonitoring.html)\n- [Amazon MSK — CloudWatch metrics for Provisioned clusters](https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Fmetrics-details.html)\n- [Amazon MSK — Right-size your cluster](https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Fbestpractices.html#bestpractices-right-size-cluster)\n- [Amazon MSK — Service quotas](https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Flimits.html)\n\n## Common CLI Recipes\n\n**Describe cluster:**\n\n```\naws kafka describe-cluster-v2 --cluster-arn \u003Ccluster-arn>\n```\n\n**List brokers:**\n\n```\naws kafka list-nodes --cluster-arn \u003Ccluster-arn>\n```\n\n**Get bootstrap brokers:**\n\n```\naws kafka get-bootstrap-brokers --cluster-arn \u003Ccluster-arn>\n```\n\n**List recent cluster operations (patching, config updates, storage changes):**\n\n```\naws kafka list-cluster-operations-v2 --cluster-arn \u003Ccluster-arn>\n```\n\n**Expand Standard broker storage** — *Operator-run (recommend, do not execute):*\n\n```\naws kafka update-broker-storage \\\n  --cluster-arn \u003Ccluster-arn> \\\n  --current-version \u003Ccluster-version> \\\n  --target-broker-ebs-volume-info '[{\"KafkaBrokerNodeId\": \"All\", \"VolumeSizeGB\": \u003Ctarget-size>}]'\n```\n\n**Get a CloudWatch metric (example: `CpuUser` per broker):**\n\n```\naws cloudwatch get-metric-statistics \\\n  --namespace AWS\u002FKafka \\\n  --metric-name CpuUser \\\n  --dimensions Name=\"Cluster Name\",Value=\"\u003Ccluster-name>\" Name=\"Broker ID\",Value=\"\u003Cbroker-id>\" \\\n  --start-time \u003Cstart> --end-time \u003Cend> --period 300 --statistics Average\n```\n\n**Create a cluster configuration (`server.properties`)** — *Operator-run (recommend, do not execute):*\n\nThe `--server-properties` argument MUST be a real Kafka properties file with\none `key=value` per line, separated by actual newline characters — NOT the\nliteral two-character escape sequence `\\n`. The MSK API accepts the bytes as-is;\nif you pass `\"k1=v1\\nk2=v2\"` as a single string with escaped newlines, MSK\nstores ONE invalid property line and the cluster will fail to apply it.\n\nRecommended pattern: write the properties to a local file with real newlines,\nthen pass it via `fileb:\u002F\u002F` so the CLI uploads the raw bytes verbatim. Verify by\nreading the revision back with `describe-configuration-revision` and\nbase64-decoding `ServerProperties` — you should see one property per line.\n\n```\ncat > server.properties \u003C\u003C'EOF'\nauto.create.topics.enable=false\ndefault.replication.factor=3\nmin.insync.replicas=2\nunclean.leader.election.enable=false\nnum.io.threads=32\nnum.network.threads=16\nlog.retention.hours=168\nEOF\n\naws kafka create-configuration \\\n  --name \u003Cconfig-name> \\\n  --kafka-versions \"3.6.0\" \\\n  --server-properties fileb:\u002F\u002Fserver.properties\n```\n\n## Common Error Reference\n\n| Error | Cause | Fix |\n|---|---|---|\n| `aws kafka update-broker-storage` returns \"storage is optimizing\" | Previous storage expansion still in cool-down (minimum 6 hours) | Wait for optimization to complete. Check cluster state with `describe-cluster-v2`. |\n| `ClusterState` is `MAINTENANCE` | Standard brokers undergoing patching. Express brokers stay `ACTIVE` during maintenance. | Wait for cluster to return to `ACTIVE`. Do not perform update operations during `MAINTENANCE`. |\n| Consumer receives `GROUP_COORDINATOR_NOT_AVAILABLE` | Coordinator broker is temporarily unavailable during rolling restart or overloaded | Retry with backoff. Check if maintenance is in progress via `list-cluster-operations-v2`. |\n| `NotEnoughReplicasException` on produce | Fewer brokers in ISR than `min.insync.replicas` (default: 2) | Check `UnderReplicatedPartitions` (Standard only). For Express, check `ProduceThrottleTime` and broker health instead — URP is not available. If a broker is down for maintenance, this is transient. Do NOT lower `min.insync.replicas` to work around this. |\n\n## Severity Definitions (for review-style reports)\n\n| Severity | Definition | SLA |\n|---|---|---|\n| CRITICAL | Immediate risk to availability, security, or data integrity | Fix within 24–48 hours |\n| HIGH | Significant gap that could lead to incidents | Fix within 1 week |\n| MEDIUM | Notable improvement opportunity | Plan within 30 days |\n| LOW | Minor optimization or hardening | Address when convenient |\n| INFO | Observation, no action required | N\u002FA |\n\n## Additional Resources\n\n- [Amazon MSK best practices — Standard brokers](https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Fbestpractices.html)\n- [Amazon MSK best practices — Express brokers](https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Fbestpractices-express.html)\n- [Amazon MSK — Apache Kafka client best practices](https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Fbestpractices-kafka-client.html)\n- [Amazon MSK — Monitoring an MSK cluster](https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Fmonitoring.html)\n- [Amazon MSK — CloudWatch metrics for Provisioned clusters](https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Fmetrics-details.html)\n- [Amazon MSK — Service quotas](https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Flimits.html)\n- [Amazon MSK — Custom MSK configurations](https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Fmsk-configuration.html)\n",{"data":53,"body":61},{"name":4,"description":6,"metadata":54},{"author":55,"version":56,"aws-devops-agent-skills":57},"kjjanaki","1.0.2",{"agent-types":58,"aws-services":59,"technical-domains":60},"Chat tasks, Evaluation","Amazon MSK","Analytics",{"type":62,"children":63},"root",[64,73,79,86,91,130,143,149,154,166,179,242,249,274,300,306,479,485,490,675,681,686,816,832,838,850,862,868,873,891,904,910,915,923,951,957,962,971,976,1241,1247,1272,1367,1379,1385,1440,1477,1484,1597,1609,1996,2008,2194,2255,2261,2266,2377,2383,2388,2397,2409,2415,2427,2432,2438,2510,2516,2578,2584,2615,2621,2695,2701,2748,2754,2818,2824,2841,2882,2890,2903,2909,2920,2939,2944,2950,2959,2965,2983,2989,2994,3000,3005,3010,3015,3021,3026,3032,3037,3049,3055,3067,3072,3077,3083,3088,3093,3099,3117,3123,3185,3191,3199,3207,3215,3224,3232,3241,3249,3258,3274,3283,3298,3307,3327,3363,3392,3401,3407,3595,3601,3718,3724],{"type":65,"tag":66,"props":67,"children":69},"element","h1",{"id":68},"amazon-msk-operations",[70],{"type":71,"value":72},"text","Amazon MSK Operations",{"type":65,"tag":74,"props":75,"children":76},"p",{},[77],{"type":71,"value":78},"Operate, troubleshoot, and assess Amazon MSK (Managed Streaming for Apache Kafka)\nProvisioned clusters — both Standard and Express broker types. 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Express enforces a fixed replication factor of 3 and\n",{"type":65,"tag":112,"props":293,"children":295},{"className":294},[],[296],{"type":71,"value":297},"min.insync.replicas=2",{"type":71,"value":299}," — you cannot create topics with RF=1.",{"type":65,"tag":80,"props":301,"children":303},{"id":302},"critical-warnings",[304],{"type":71,"value":305},"Critical Warnings",{"type":65,"tag":92,"props":307,"children":308},{},[309,378,396,406,422,454,464],{"type":65,"tag":96,"props":310,"children":311},{},[312,317,319,325,327,333,334,340,342,348,349,355,356,362,363,369,371,376],{"type":65,"tag":136,"props":313,"children":314},{},[315],{"type":71,"value":316},"This skill is read-only.",{"type":71,"value":318}," Every command in this file and in ",{"type":65,"tag":112,"props":320,"children":322},{"className":321},[],[323],{"type":71,"value":324},"references\u002F",{"type":71,"value":326},"\nthat mutates cluster state — ",{"type":65,"tag":112,"props":328,"children":330},{"className":329},[],[331],{"type":71,"value":332},"update-broker-storage",{"type":71,"value":202},{"type":65,"tag":112,"props":335,"children":337},{"className":336},[],[338],{"type":71,"value":339},"create-configuration",{"type":71,"value":341},",\n",{"type":65,"tag":112,"props":343,"children":345},{"className":344},[],[346],{"type":71,"value":347},"update-cluster-configuration",{"type":71,"value":202},{"type":65,"tag":112,"props":350,"children":352},{"className":351},[],[353],{"type":71,"value":354},"update-monitoring",{"type":71,"value":202},{"type":65,"tag":112,"props":357,"children":359},{"className":358},[],[360],{"type":71,"value":361},"put-metric-alarm",{"type":71,"value":341},{"type":65,"tag":112,"props":364,"children":366},{"className":365},[],[367],{"type":71,"value":368},"reboot-broker",{"type":71,"value":370},", and any partition reassignment — is a ",{"type":65,"tag":136,"props":372,"children":373},{},[374],{"type":71,"value":375},"recommendation for\nthe operator to run after review",{"type":71,"value":377},". Present these as proposed remediations\nwith expected impact and preconditions; do NOT execute them, and do NOT\nimply that the agent will run them.",{"type":65,"tag":96,"props":379,"children":380},{},[381,394],{"type":65,"tag":136,"props":382,"children":383},{},[384,386,392],{"type":71,"value":385},"NEVER reboot brokers while ",{"type":65,"tag":112,"props":387,"children":389},{"className":388},[],[390],{"type":71,"value":391},"UnderReplicatedPartitions",{"type":71,"value":393}," > 0",{"type":71,"value":395}," (Standard only —\nExpress brokers do not emit URP). 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hours",{"type":65,"tag":695,"props":3647,"children":3648},{},[3649,3654,3659],{"type":65,"tag":717,"props":3650,"children":3651},{},[3652],{"type":71,"value":3653},"HIGH",{"type":65,"tag":717,"props":3655,"children":3656},{},[3657],{"type":71,"value":3658},"Significant gap that could lead to incidents",{"type":65,"tag":717,"props":3660,"children":3661},{},[3662],{"type":71,"value":3663},"Fix within 1 week",{"type":65,"tag":695,"props":3665,"children":3666},{},[3667,3672,3677],{"type":65,"tag":717,"props":3668,"children":3669},{},[3670],{"type":71,"value":3671},"MEDIUM",{"type":65,"tag":717,"props":3673,"children":3674},{},[3675],{"type":71,"value":3676},"Notable improvement opportunity",{"type":65,"tag":717,"props":3678,"children":3679},{},[3680],{"type":71,"value":3681},"Plan within 30 days",{"type":65,"tag":695,"props":3683,"children":3684},{},[3685,3690,3695],{"type":65,"tag":717,"props":3686,"children":3687},{},[3688],{"type":71,"value":3689},"LOW",{"type":65,"tag":717,"props":3691,"children":3692},{},[3693],{"type":71,"value":3694},"Minor optimization or hardening",{"type":65,"tag":717,"props":3696,"children":3697},{},[3698],{"type":71,"value":3699},"Address when convenient",{"type":65,"tag":695,"props":3701,"children":3702},{},[3703,3708,3713],{"type":65,"tag":717,"props":3704,"children":3705},{},[3706],{"type":71,"value":3707},"INFO",{"type":65,"tag":717,"props":3709,"children":3710},{},[3711],{"type":71,"value":3712},"Observation, no action required",{"type":65,"tag":717,"props":3714,"children":3715},{},[3716],{"type":71,"value":3717},"N\u002FA",{"type":65,"tag":80,"props":3719,"children":3721},{"id":3720},"additional-resources",[3722],{"type":71,"value":3723},"Additional Resources",{"type":65,"tag":92,"props":3725,"children":3726},{},[3727,3735,3743,3753,3761,3769,3777],{"type":65,"tag":96,"props":3728,"children":3729},{},[3730],{"type":65,"tag":822,"props":3731,"children":3733},{"href":3131,"rel":3732},[826],[3734],{"type":71,"value":3135},{"type":65,"tag":96,"props":3736,"children":3737},{},[3738],{"type":65,"tag":822,"props":3739,"children":3741},{"href":3141,"rel":3740},[826],[3742],{"type":71,"value":3145},{"type":65,"tag":96,"props":3744,"children":3745},{},[3746],{"type":65,"tag":822,"props":3747,"children":3750},{"href":3748,"rel":3749},"https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Fbestpractices-kafka-client.html",[826],[3751],{"type":71,"value":3752},"Amazon MSK — Apache Kafka client best practices",{"type":65,"tag":96,"props":3754,"children":3755},{},[3756],{"type":65,"tag":822,"props":3757,"children":3759},{"href":3151,"rel":3758},[826],[3760],{"type":71,"value":3155},{"type":65,"tag":96,"props":3762,"children":3763},{},[3764],{"type":65,"tag":822,"props":3765,"children":3767},{"href":3161,"rel":3766},[826],[3768],{"type":71,"value":3165},{"type":65,"tag":96,"props":3770,"children":3771},{},[3772],{"type":65,"tag":822,"props":3773,"children":3775},{"href":3180,"rel":3774},[826],[3776],{"type":71,"value":3184},{"type":65,"tag":96,"props":3778,"children":3779},{},[3780],{"type":65,"tag":822,"props":3781,"children":3784},{"href":3782,"rel":3783},"https:\u002F\u002Fdocs.aws.amazon.com\u002Fmsk\u002Flatest\u002Fdeveloperguide\u002Fmsk-configuration.html",[826],[3785],{"type":71,"value":3786},"Amazon MSK — Custom MSK configurations",{"items":3788,"total":3893},[3789,3801,3816,3830,3846,3862,3877],{"slug":3790,"name":3790,"fn":3791,"description":3792,"org":3793,"tags":3794,"stars":24,"repoUrl":25,"updatedAt":3800},"aws-health-events","analyze AWS Health events for incidents","ALWAYS use this skill in the beginning of any incident investigation, root cause analysis, or operational troubleshooting. This skill retrieves and analyzes AWS Health events (service issues, scheduled changes, and account notifications) to identify AWS-side events that may explain or correlate with observed operational issues. Activate this skill when investigating an issue and you observe service degradation, elevated error rates, latency spikes, connection failures, throttling, capacity issues, deployment-related failures, alarms, or any operational event or issue. This skill searches AWS Health events by service, time window, region, and status to surface active or recent service disruptions, scheduled maintenance, and account-specific notifications that inform the current investigation. Also activate when a user requests a health event summary or report for their account over a specified time period.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3795,3796,3797,3799],{"name":20,"slug":8,"type":15},{"name":22,"slug":23,"type":15},{"name":3798,"slug":41,"type":15},"Incident Response",{"name":17,"slug":18,"type":15},"2026-08-20T03:53:41.178955",{"slug":3802,"name":3802,"fn":3803,"description":3804,"org":3805,"tags":3806,"stars":24,"repoUrl":25,"updatedAt":3815},"aws-vpc-dns-investigation","investigate VPC DNS resolution issues","Use this skill when a name is not resolving as expected inside a VPC, or before applying a DNS control-plane change. Activate on symptoms such as NXDOMAIN or SERVFAIL from an EC2 instance, a hostname resolving to a public address when a private endpoint was expected, an AWS service endpoint that stopped resolving after a VPC endpoint or Route 53 change, an application reaching the wrong IP, resolution that works from one instance but not another, IPv6 or dualstack resolution differences, a suspected on-premises forwarding or hybrid DNS problem, or a request to check whether enabling private DNS, adding a Resolver rule, associating a private hosted zone, attaching DNS Firewall, or associating a Route 53 Profile would break anything. It drives the aws-vpc-dns-diagnostics MCP server to observe live resolution from inside the subnet and to simulate a proposed change before it is applied.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3807,3808,3809,3812],{"name":20,"slug":8,"type":15},{"name":22,"slug":23,"type":15},{"name":3810,"slug":3811,"type":15},"DNS","dns",{"name":3813,"slug":3814,"type":15},"Networking","networking","2026-08-20T03:53:46.027593",{"slug":3817,"name":3817,"fn":3818,"description":3819,"org":3820,"tags":3821,"stars":24,"repoUrl":25,"updatedAt":3829},"crm-production-investigation-guidelines","investigate CRM production incidents","Guidelines for investigating production incidents in the CRM application. Use when triaging any alert or incident involving the CRM REST API, SQS queues, Lambda functions, or Aurora DSQL database in this AWS account. Ensures thorough root cause analysis using AWS-native observability tools.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3822,3823,3826,3827,3828],{"name":20,"slug":8,"type":15},{"name":3824,"slug":3825,"type":15},"CRM","crm",{"name":22,"slug":23,"type":15},{"name":3798,"slug":41,"type":15},{"name":13,"slug":14,"type":15},"2026-08-20T03:53:23.532781",{"slug":3831,"name":3831,"fn":3832,"description":3833,"org":3834,"tags":3835,"stars":24,"repoUrl":25,"updatedAt":3845},"database-migration-service-expertise","troubleshoot AWS Database Migration Service","AWS Database Migration Service (DMS) operational review and troubleshooting skill. Conducts best practices validation, health assessments, performance diagnostics, cost optimization reviews, and migration cutover guidance. Triggers on requests like \"DMS review\", \"DMS health check\", \"DMS troubleshooting\", \"migration assessment\", \"DMS best practices audit\", \"DMS cost optimization\", \"replication instance review\", \"CDC latency issue\", or \"DMS task failure\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3836,3837,3840,3841,3844],{"name":20,"slug":8,"type":15},{"name":3838,"slug":3839,"type":15},"Database","database",{"name":22,"slug":23,"type":15},{"name":3842,"slug":3843,"type":15},"Migration","migration",{"name":13,"slug":14,"type":15},"2026-08-20T03:53:23.927999",{"slug":3847,"name":3847,"fn":3848,"description":3849,"org":3850,"tags":3851,"stars":24,"repoUrl":25,"updatedAt":3861},"database-rds-devops","diagnose Aurora MySQL and PostgreSQL databases","Database-level data-plane diagnostics for Aurora MySQL and Aurora PostgreSQL. Executes predefined read-only health check queries via RDS Data API to analyze buffer pool, connections, locks, replication, storage, performance, and index efficiency. Requires the rds-aidba MCP server for database-internal access beyond what CloudWatch and RDS APIs provide.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3852,3853,3854,3855,3858],{"name":20,"slug":8,"type":15},{"name":3838,"slug":3839,"type":15},{"name":22,"slug":23,"type":15},{"name":3856,"slug":3857,"type":15},"MySQL","mysql",{"name":3859,"slug":3860,"type":15},"PostgreSQL","postgresql","2026-08-20T03:53:41.560344",{"slug":3863,"name":3863,"fn":3864,"description":3865,"org":3866,"tags":3867,"stars":24,"repoUrl":25,"updatedAt":3876},"eks-operation-review","audit Amazon EKS cluster operations","Comprehensive Amazon EKS operational review aligned with the AWS EKS Best Practices Guide. Use this skill when a user asks to review, audit, or assess EKS clusters for best practices compliance, operational readiness, security posture, cost optimization, reliability, networking, scalability, or upgrade readiness. Triggers on requests like \"EKS review\", \"EKS best practices audit\", \"EKS operational assessment\", \"review my EKS cluster\", or \"EKS health check\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3868,3871,3872,3875],{"name":3869,"slug":3870,"type":15},"Audit","audit",{"name":20,"slug":8,"type":15},{"name":3873,"slug":3874,"type":15},"Kubernetes","kubernetes",{"name":13,"slug":14,"type":15},"2026-08-20T03:53:20.524374",{"slug":3878,"name":3878,"fn":3879,"description":3880,"org":3881,"tags":3882,"stars":24,"repoUrl":25,"updatedAt":3892},"enrich-with-aws-security-agent","investigate security root causes in AWS","Automatically load this skill when investigating application outages, service degradation, or errors that could have security-related root causes — including unexplained downtime, authentication or authorization failures, injection attacks, data exposure, or suspicious application behavior. Query AWS Security Agent CloudWatch logs to retrieve detailed code review findings with actionable, low-level details (file, line number, vulnerability type) that customers can directly fix.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3883,3886,3887,3888,3889],{"name":3884,"slug":3885,"type":15},"Auth","auth",{"name":20,"slug":8,"type":15},{"name":22,"slug":23,"type":15},{"name":3798,"slug":41,"type":15},{"name":3890,"slug":3891,"type":15},"Security","security","2026-08-20T03:53:23.097965",15,{"items":3895,"total":4060},[3896,3914,3929,3942,3957,3967,3980,3996,4010,4023,4034,4046],{"slug":3897,"name":3897,"fn":3898,"description":3899,"org":3900,"tags":3901,"stars":3911,"repoUrl":3912,"updatedAt":3913},"agents-build","add capabilities to existing agent projects","Use to extend an existing agent project with memory, app integration, VPC, multi-agent, migration, model, browser, code interpreter, payments, or resource removal. Triggers: \"add memory\", \"remember across sessions\", \"call agent from app\", \"invoke agent from code\", \"agent auth\", \"streaming\", \"VPC\", \"VPC connectivity\", \"can't reach from VPC\", \"multi-agent\", \"A2A\", \"A2A auth\", \"orchestrator not delegating\", \"specialist not called\", \"migrate Bedrock Agent\", \"migration issue\", \"change model\", \"browser tool\", \"code interpreter\", \"delete agent\", \"tear down\", \"agentcore remove\", \"cross-account memory\", \"add payments capability to my agent\", \"wire payments plugin\", \"integrate x402 payments with the agent I'm building\", \"add MPP payments\", \"Machine Payments Protocol\". External APIs via Gateway: use agents-connect. New project: use agents-get-started. CLI\u002Fdev-server errors: use agents-debug. Runtime x402\u002FMPP payments: use agents-pay. Migration-specific Strands vs LangGraph routes here.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3902,3904,3907,3908],{"name":3903,"slug":32,"type":15},"Agents",{"name":3905,"slug":3906,"type":15},"Automation","automation",{"name":20,"slug":8,"type":15},{"name":3909,"slug":3910,"type":15},"Engineering","engineering",1822,"https:\u002F\u002Fgithub.com\u002Faws\u002Fagent-toolkit-for-aws","2026-08-20T03:27:06.137661",{"slug":3915,"name":3915,"fn":3916,"description":3917,"org":3918,"tags":3919,"stars":3911,"repoUrl":3912,"updatedAt":3928},"agents-connect","connect agents to external services","Use when connecting your agent to external APIs, tools, or services via Gateway, or restricting tool access with Cedar policies. Handles gateway setup, target types, outbound auth (OAuth, API key, IAM), credentials, and Cedar policy authoring. Triggers on: \"connect to API\", \"add gateway\", \"connect to MCP server\", \"Lambda tools\", \"OpenAPI\", \"gateway target\", \"Cedar policy\", \"restrict tools\", \"policy engine\", \"gateway auth error\", \"store API key\", \"outbound credential\", \"env var API key\", \"API key None after deploy\", \"credential not available after deploy\", \"should this be a gateway target\", \"give my agent tools\", \"add tools to agent\". Not for inbound auth (who can call your agent) — use agents-harden. Not for debugging agent behavior — use agents-debug. Not for VPC networking errors (agent can't reach APIs due to VPC) — use agents-build. Not for creating or hosting a new MCP server project — use agents-get-started.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3920,3921,3924,3927],{"name":3903,"slug":32,"type":15},{"name":3922,"slug":3923,"type":15},"API Development","api-development",{"name":3925,"slug":3926,"type":15},"Authentication","authentication",{"name":20,"slug":8,"type":15},"2026-07-16T06:00:38.866147",{"slug":3930,"name":3930,"fn":3931,"description":3932,"org":3933,"tags":3934,"stars":3911,"repoUrl":3912,"updatedAt":3941},"agents-debug","debug agent and environment issues","Use when your agent or environment is broken — wrong answers, errors, timeouts, tool failures, or CLI issues. Reads traces and logs to diagnose root causes. Also checks prerequisites when the CLI itself isn't working. Triggers on: \"agent not working\", \"wrong answer\", \"agent error\", \"tool call failing\", \"debug agent\", \"check logs\", \"read traces\", \"broken\", \"500 error\", \"424 error\", \"model access denied\", \"command not found\", \"stuck in DELETING\", \"maxVms exceeded\", \"cold start diagnosis\", \"cold start slow\", \"agentcore create error\", \"create failed\", \"exit code 7\", \"connection refused local dev\". Not for deploy failures — use agents-deploy. Not for performance tuning without errors — use agents-optimize. Not for VPC configuration — use agents-build. Not for observability setup or missing logs — use agents-optimize.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3935,3936,3937,3938],{"name":3903,"slug":32,"type":15},{"name":20,"slug":8,"type":15},{"name":22,"slug":23,"type":15},{"name":3939,"slug":3940,"type":15},"Observability","observability","2026-07-16T06:00:44.679093",{"slug":3943,"name":3943,"fn":3944,"description":3945,"org":3946,"tags":3947,"stars":3911,"repoUrl":3912,"updatedAt":3956},"agents-deploy","deploy AI agents to AWS","Use when deploying your agent to AWS, or when a deploy has failed. Handles pre-flight validation, CDK\u002FIAM\u002Fquota error diagnosis, version management, rollback, and canary deployments. Triggers on: \"deploy my agent\", \"agentcore deploy\", \"deploy failed\", \"CDK error\", \"rollback\", \"canary deploy\", \"pin version\", \"redeploy\", \"deploy stuck\". Not for production hardening — use agents-harden. Not for adding capabilities before deploy — use agents-build or agents-connect. Not for VPC configuration errors — use agents-build.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3948,3949,3950,3953],{"name":3903,"slug":32,"type":15},{"name":20,"slug":8,"type":15},{"name":3951,"slug":3952,"type":15},"CI\u002FCD","ci-cd",{"name":3954,"slug":3955,"type":15},"Deployment","deployment","2026-07-12T08:42:55.059577",{"slug":3958,"name":3958,"fn":3959,"description":3960,"org":3961,"tags":3962,"stars":3911,"repoUrl":3912,"updatedAt":3966},"agents-get-started","scaffold and deploy new agent projects","Use when a developer wants to create a new agent project or get started with AgentCore. Handles framework selection, project scaffolding, first deploy, and first invocation. Triggers on: \"build an agent\", \"create an agent\", \"get started\", \"new project\", \"agentcore create\", \"which framework\", \"Strands vs LangGraph\", \"hello world agent\", \"first agent\", \"create MCP server\", \"host MCP server\", \"agentcore dev\", \"dev server\", \"what port\", \"local development\". Not for adding capabilities to existing projects — use agents-build or agents-connect. Strands vs LangGraph in a migration context routes to agents-build, not here. Connecting to an existing MCP server routes to agents-connect, not here.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3963,3964,3965],{"name":3903,"slug":32,"type":15},{"name":20,"slug":8,"type":15},{"name":3954,"slug":3955,"type":15},"2026-07-12T08:42:51.963247",{"slug":3968,"name":3968,"fn":3969,"description":3970,"org":3971,"tags":3972,"stars":3911,"repoUrl":3912,"updatedAt":3979},"agents-harden","harden agents for production","Use when preparing your agent for production — IAM scoping, inbound auth (JWT, SigV4), secrets management, cold start optimization, session lifecycle, rate limiting, input validation, and quota guidance. Triggers on: \"production checklist\", \"harden agent\", \"production ready\", \"secure agent\", \"inbound auth\", \"going live\", \"cold start optimization\", \"session lifecycle\", \"StopRuntimeSession\", \"quota\", \"throttling\", \"maxVms\", \"rate limit\", \"security audit of outbound API calls\", \"gateway target audit for production\", \"restrict who can call\", \"lock down endpoint\", \"only our app can call\". Not for Cedar tool-restriction policies — use agents-connect. Not for quality measurement — use agents-optimize. Not for outbound credential storage or API key wiring — use agents-connect. Not for A2A agent-to-agent auth — use agents-build. Cold start observation and diagnosis (not optimization) routes to agents-debug.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3973,3974,3975,3978],{"name":3903,"slug":32,"type":15},{"name":20,"slug":8,"type":15},{"name":3976,"slug":3977,"type":15},"Best Practices","best-practices",{"name":3890,"slug":3891,"type":15},"2026-07-16T06:00:42.174705",{"slug":3981,"name":3981,"fn":3982,"description":3983,"org":3984,"tags":3985,"stars":3911,"repoUrl":3912,"updatedAt":3995},"agents-optimize","optimize agent quality and performance","Use when measuring or improving agent quality and performance — set up evaluators, online monitoring, CI\u002FCD quality gates, observability, or cost optimization. Triggers on: \"evaluate my agent\", \"add evaluator\", \"measure quality\", \"quality gate\", \"run evals\", \"agent too slow\", \"why is it slow\", \"reduce latency\", \"set up observability\", \"CloudWatch dashboard\", \"how much does my agent cost\", \"cost optimization\", \"logs not showing up\", \"logs missing\", \"spans not found\", \"eval failing\", \"eval error\", \"dev traces\", \"local traces\", \"agentcore dev traces\", \"traces to CloudWatch\". Not for debugging errors or crashes — use agents-debug. Slow but correct routes here; broken routes to debug.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3986,3987,3988,3991,3992],{"name":3903,"slug":32,"type":15},{"name":20,"slug":8,"type":15},{"name":3989,"slug":3990,"type":15},"Evals","evals",{"name":3939,"slug":3940,"type":15},{"name":3993,"slug":3994,"type":15},"Performance","performance","2026-07-12T08:42:56.488105",{"slug":3997,"name":3997,"fn":3998,"description":3999,"org":4000,"tags":4001,"stars":3911,"repoUrl":3912,"updatedAt":4009},"agents-pay","handle x402 payments for agent tasks","Use when THIS agent needs to pay for x402-protected content at runtime: hitting a paywall mid-task, settling it via AgentCore Payments, and applying operator-defined spend limits. Covers payment setup, policy, session budgets, and troubleshooting. Triggers on: \"my agent hit a 402 while calling an API\", \"a tool call returned 402 Payment Required\", \"my agent needs to pay for x402-protected content\", \"let the agent pay for content, capped at $5 per session\", \"set a spend limit for the agent\", \"ProcessPayment failed\", or \"why did my agent refuse to pay\". Not for BUILDING payment capability for end users, including wallets and framework middleware; use agents-build and references\u002Fpayments.md. For non-paid APIs via Gateway use agents-connect. For inbound auth use agents-harden. For project scaffolding use agents-get-started.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4002,4003,4004,4007],{"name":3903,"slug":32,"type":15},{"name":3905,"slug":3906,"type":15},{"name":4005,"slug":4006,"type":15},"Payments","payments",{"name":4008,"slug":4008,"type":15},"x402","2026-08-10T04:16:31.844309",{"slug":4011,"name":4011,"fn":4012,"description":4013,"org":4014,"tags":4015,"stars":3911,"repoUrl":3912,"updatedAt":4022},"amazon-aurora-mysql","manage Amazon Aurora MySQL clusters","Amazon Aurora MySQL — creates, modifies, and advises on Aurora MySQL clusters specifically (MySQL-compatible engine, Aurora serverless, parallel query). Trigger for Aurora MySQL cluster operations, ACU sizing, I\u002FO-Optimized storage, commitment pricing, or MySQL upgrade planning. Aurora MySQL uses full (VPC-based) configuration — express configuration is PostgreSQL-only. For Aurora PostgreSQL, use amazon-aurora-postgresql instead. Contains safety guardrails and response templates that override defaults.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4016,4017,4018,4019],{"name":20,"slug":8,"type":15},{"name":3838,"slug":3839,"type":15},{"name":3856,"slug":3857,"type":15},{"name":4020,"slug":4021,"type":15},"Serverless","serverless","2026-07-12T08:43:13.27939",{"slug":4024,"name":4024,"fn":4025,"description":4026,"org":4027,"tags":4028,"stars":3911,"repoUrl":3912,"updatedAt":4033},"amazon-aurora-postgresql","configure Amazon Aurora PostgreSQL clusters","Amazon Aurora PostgreSQL — creates, modifies, and advises on Aurora PostgreSQL clusters specifically (PostgreSQL-compatible engine, Aurora serverless, express configuration, pgvector, Babelfish). Trigger for Aurora PostgreSQL cluster operations, express-configuration quick-start, ACU sizing, I\u002FO-Optimized storage, commitment pricing, or PostgreSQL upgrade planning. For Aurora MySQL, use amazon-aurora-mysql instead. Contains safety guardrails, express-first routing, and response templates that override defaults.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4029,4030,4031,4032],{"name":20,"slug":8,"type":15},{"name":3838,"slug":3839,"type":15},{"name":3859,"slug":3860,"type":15},{"name":4020,"slug":4021,"type":15},"2026-07-16T06:00:34.789624",{"slug":4035,"name":4035,"fn":4036,"description":4037,"org":4038,"tags":4039,"stars":3911,"repoUrl":3912,"updatedAt":4045},"amazon-bedrock","build generative AI apps with Amazon Bedrock","Builds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore (including the Harness managed agent loop). Use when invoking models, setting up Knowledge Bases, creating agents, applying guardrails, deploying to AgentCore, migrating\u002Fporting\u002Fconverting a Bedrock Agent (including inline agents) to an AgentCore Harness, troubleshooting Bedrock errors (ThrottlingException, AccessDeniedException), or choosing models (Claude, Llama, Nova, Titan). ALSO USE for prompt caching, quota health checks and throttling diagnosis, cost attribution, migrating between Claude model generations, chunking strategies, API selection (Converse vs InvokeModel), and model selection. Also covers AgentCore Payments setup (x402, microtransactions, Payment Manager, Coinbase CDP, Stripe Privy, 402 Payment Required, paid endpoint). NOT for custom model training, Rekognition, or Comprehend.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4040,4041,4042],{"name":3903,"slug":32,"type":15},{"name":20,"slug":8,"type":15},{"name":4043,"slug":4044,"type":15},"LLM","llm","2026-08-07T04:38:13.03499",{"slug":4047,"name":4047,"fn":4048,"description":4049,"org":4050,"tags":4051,"stars":3911,"repoUrl":3912,"updatedAt":4059},"amazon-braket","run quantum computing workflows on AWS","Runs quantum computing workflows on AWS through Amazon Braket — discovering devices (QPUs and simulators) and their availability, building gate-model circuits and analog Hamiltonian programs, submitting quantum tasks, program sets and hybrid jobs, looking up prices, and capping spend with spending limits. Applies to any request about quantum computing, quantum hardware, quantum simulation, AHS, OpenQASM, or running a quantum algorithm on AWS.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4052,4053,4056],{"name":20,"slug":8,"type":15},{"name":4054,"slug":4055,"type":15},"Quantum Computing","quantum-computing",{"name":4057,"slug":4058,"type":15},"Simulation","simulation","2026-08-20T03:53:19.377174",139]