Cloudflare GraphQL Analytics for zone traffic, firewall events, Workers metrics, and schema exploration. Use when querying Cloudflare analytics data or exploring the GraphQL API.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Aws Elasticache Deep — aWS ElastiCache deep analysis for Redis and Memcached clusters, replication health, failover analysis, and performance metrics. Covers node-level metrics, memory utilization, cache hit rates, eviction tracking, connection analysis, and engine-specific diagnostics.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Deep analysis of AWS ElastiCache Redis and Memcached clusters with parallel execution and anti-hallucination guardrails.
Relationship to other AWS skills:
aws-elasticache-deep/ → ElastiCache-specific deep analysis (replication, failover, engine metrics)aws/ → "How to execute" (parallel patterns, throttling, output format)ALL independent operations MUST run in parallel using background jobs (&) and wait.
#!/bin/bash
export AWS_PAGER=""
for cluster in $clusters; do
get_cluster_metrics "$cluster" &
done
wait
#!/bin/bash
export AWS_PAGER=""
# List replication groups (Redis)
list_replication_groups() {
aws elasticache describe-replication-groups \
--output text \
--query 'ReplicationGroups[].[ReplicationGroupId,Status,ClusterEnabled,AutomaticFailover,MultiAZ,NodeGroups[0].NodeGroupMembers[0].CacheNodeId]'
}
# List cache clusters
list_cache_clusters() {
aws elasticache describe-cache-clusters --show-cache-node-info \
--output text \
--query 'CacheClusters[].[CacheClusterId,Engine,EngineVersion,CacheNodeType,NumCacheNodes,CacheClusterStatus,ReplicationGroupId]'
}
# Get cluster metrics
get_cluster_metrics() {
local cluster_id=$1 days=${2:-1}
local end_time start_time
end_time=$(date -u +"%Y-%m-%dT%H:%M:%S")
start_time=$(date -u -d "$days days ago" +"%Y-%m-%dT%H:%M:%S" 2>/dev/null || date -u -v-${days}d +"%Y-%m-%dT%H:%M:%S")
aws cloudwatch get-metric-statistics \
--namespace AWS/ElastiCache --metric-name CPUUtilization \
--dimensions Name=CacheClusterId,Value="$cluster_id" \
--start-time "$start_time" --end-time "$end_time" \
--period $((days * 86400)) --statistics Average Maximum \
--output text --query "Datapoints[0].[\"$cluster_id\",\"CPU\",Average,Maximum]" &
aws cloudwatch get-metric-statistics \
--namespace AWS/ElastiCache --metric-name DatabaseMemoryUsagePercentage \
--dimensions Name=CacheClusterId,Value="$cluster_id" \
--start-time "$start_time" --end-time "$end_time" \
--period $((days * 86400)) --statistics Average Maximum \
--output text --query "Datapoints[0].[\"$cluster_id\",\"Memory\",Average,Maximum]" &
aws cloudwatch get-metric-statistics \
--namespace AWS/ElastiCache --metric-name CacheHitRate \
--dimensions Name=CacheClusterId,Value="$cluster_id" \
--start-time "$start_time" --end-time "$end_time" \
--period $((days * 86400)) --statistics Average \
--output text --query "Datapoints[0].[\"$cluster_id\",\"HitRate\",Average]" &
aws cloudwatch get-metric-statistics \
--namespace AWS/ElastiCache --metric-name Evictions \
--dimensions Name=CacheClusterId,Value="$cluster_id" \
--start-time "$start_time" --end-time "$end_time" \
--period $((days * 86400)) --statistics Sum \
--output text --query "Datapoints[0].[\"$cluster_id\",\"Evictions\",Sum]" &
wait
}
# Get replication lag (Redis)
get_replication_lag() {
local cluster_id=$1
local end_time start_time
end_time=$(date -u +"%Y-%m-%dT%H:%M:%S")
start_time=$(date -u -d "1 hour ago" +"%Y-%m-%dT%H:%M:%S" 2>/dev/null || date -u -v-1H +"%Y-%m-%dT%H:%M:%S")
aws cloudwatch get-metric-statistics \
--namespace AWS/ElastiCache --metric-name ReplicationLag \
--dimensions Name=CacheClusterId,Value="$cluster_id" \
--start-time "$start_time" --end-time "$end_time" \
--period 300 --statistics Average Maximum \
--output text --query 'Datapoints[*].[Timestamp,Average,Maximum]' | sort -k1 | tail -5
}
#!/bin/bash
export AWS_PAGER=""
aws elasticache describe-cache-clusters --show-cache-node-info \
--output text \
--query 'CacheClusters[].[CacheClusterId,Engine,EngineVersion,CacheNodeType,NumCacheNodes,CacheClusterStatus,PreferredMaintenanceWindow]' | sort -k2
#!/bin/bash
export AWS_PAGER=""
aws elasticache describe-replication-groups \
--output text \
--query 'ReplicationGroups[].[ReplicationGroupId,Status,ClusterEnabled,AutomaticFailover,MultiAZ,MemberClusters[]]'
# Check replication lag for all replica nodes
REPLICAS=$(aws elasticache describe-cache-clusters --output text \
--query 'CacheClusters[?Engine==`redis`].CacheClusterId')
END=$(date -u +"%Y-%m-%dT%H:%M:%S")
START=$(date -u -d "1 hour ago" +"%Y-%m-%dT%H:%M:%S" 2>/dev/null || date -u -v-1H +"%Y-%m-%dT%H:%M:%S")
for replica in $REPLICAS; do
aws cloudwatch get-metric-statistics \
--namespace AWS/ElastiCache --metric-name ReplicationLag \
--dimensions Name=CacheClusterId,Value="$replica" \
--start-time "$START" --end-time "$END" \
--period 300 --statistics Average Maximum \
--output text --query "Datapoints[-1].[\"$replica\",Average,Maximum]" &
done
wait
#!/bin/bash
export AWS_PAGER=""
END=$(date -u +"%Y-%m-%dT%H:%M:%S")
START=$(date -u -d "1 day ago" +"%Y-%m-%dT%H:%M:%S" 2>/dev/null || date -u -v-1d +"%Y-%m-%dT%H:%M:%S")
CLUSTERS=$(aws elasticache describe-cache-clusters --output text --query 'CacheClusters[].CacheClusterId')
for cluster in $CLUSTERS; do
{
mem=$(aws cloudwatch get-metric-statistics \
--namespace AWS/ElastiCache --metric-name DatabaseMemoryUsagePercentage \
--dimensions Name=CacheClusterId,Value="$cluster" \
--start-time "$START" --end-time "$END" \
--period 86400 --statistics Average Maximum \
--output text --query 'Datapoints[0].[Average,Maximum]')
evictions=$(aws cloudwatch get-metric-statistics \
--namespace AWS/ElastiCache --metric-name Evictions \
--dimensions Name=CacheClusterId,Value="$cluster" \
--start-time "$START" --end-time "$END" \
--period 86400 --statistics Sum \
--output text --query 'Datapoints[0].Sum')
printf "%s\tMem:%s\tEvictions:%s\n" "$cluster" "$mem" "${evictions:-0}"
} &
done
wait
#!/bin/bash
export AWS_PAGER=""
END=$(date -u +"%Y-%m-%dT%H:%M:%S")
START=$(date -u -d "7 days ago" +"%Y-%m-%dT%H:%M:%S" 2>/dev/null || date -u -v-7d +"%Y-%m-%dT%H:%M:%S")
CLUSTERS=$(aws elasticache describe-cache-clusters --output text --query 'CacheClusters[].CacheClusterId')
for cluster in $CLUSTERS; do
{
hits=$(aws cloudwatch get-metric-statistics \
--namespace AWS/ElastiCache --metric-name CacheHits \
--dimensions Name=CacheClusterId,Value="$cluster" \
--start-time "$START" --end-time "$END" \
--period 604800 --statistics Sum \
--output text --query 'Datapoints[0].Sum')
misses=$(aws cloudwatch get-metric-statistics \
--namespace AWS/ElastiCache --metric-name CacheMisses \
--dimensions Name=CacheClusterId,Value="$cluster" \
--start-time "$START" --end-time "$END" \
--period 604800 --statistics Sum \
--output text --query 'Datapoints[0].Sum')
printf "%s\tHits:%s\tMisses:%s\n" "$cluster" "${hits:-0}" "${misses:-0}"
} &
done
wait
#!/bin/bash
export AWS_PAGER=""
END=$(date -u +"%Y-%m-%dT%H:%M:%S")
START=$(date -u -d "1 day ago" +"%Y-%m-%dT%H:%M:%S" 2>/dev/null || date -u -v-1d +"%Y-%m-%dT%H:%M:%S")
CLUSTERS=$(aws elasticache describe-cache-clusters --output text --query 'CacheClusters[].CacheClusterId')
for cluster in $CLUSTERS; do
aws cloudwatch get-metric-statistics \
--namespace AWS/ElastiCache --metric-name CurrConnections \
--dimensions Name=CacheClusterId,Value="$cluster" \
--start-time "$START" --end-time "$END" \
--period 3600 --statistics Average Maximum \
--output text --query "Datapoints[-1].[\"$cluster\",Average,Maximum]" &
done
wait
EngineCPUUtilization for the Redis process CPU. CPUUtilization includes OS overhead. For Memcached with multiple cores, CPUUtilization may underreport per-core usage.BytesUsedForCacheItems divided by maxmemory.NodeGroups with multiple shards. Non-cluster mode has one shard with primary/replicas.AutomaticFailover and MultiAZ fields.Present results as a structured report:
Aws Elasticache Deep Report
═══════════════════════════
Resources discovered: [count]
Resource Status Key Metric Issues
──────────────────────────────────────────────
[name] [ok/warn] [value] [findings]
Summary: [total] resources | [ok] healthy | [warn] warnings | [crit] critical
Action Items: [list of prioritized findings]
Target ≤50 lines of output. Use tables for multi-resource comparisons.
| Shortcut | Counter | Why |
|---|---|---|
| "I'll skip discovery and check known resources" | Always run Phase 1 discovery first | Resource names change, new resources appear — assumed names cause errors |
| "The user only asked for a quick check" | Follow the full discovery → analysis flow | Quick checks miss critical issues; structured analysis catches silent failures |
| "Default configuration is probably fine" | Audit configuration explicitly | Defaults often leave logging, security, and optimization features disabled |
| "Metrics aren't needed for this" | Always check relevant metrics when available | API/CLI responses show current state; metrics reveal trends and intermittent issues |
| "I don't have access to that" | Try the command and report the actual error | Assumed permission failures prevent useful investigation; actual errors are informative |
cache. prefix (e.g., cache.r6g.large), not the EC2 naming convention.describe-reserved-cache-nodes.PreferredMaintenanceWindow.--statistics Average Maximum.SnapshotRetentionLimit.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Cloudflare GraphQL Analytics for zone traffic, firewall events, Workers metrics, and schema exploration. Use when querying Cloudflare analytics data or exploring the GraphQL API.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Alloydb — google AlloyDB instance analysis, query insights, columnar engine optimization, maintenance windows, and cluster health.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Aqua — aqua Security platform analysis. Covers container runtime protection, image assurance policies, compliance frameworks, vulnerability management, workload protection, and registry scanning. Use when analyzing container security posture, reviewing image compliance, investigating runtime alerts, or auditing security policies.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Bigquery — google BigQuery job analysis, slot utilization, cost analysis, dataset management, and query optimization.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Cassandra — apache Cassandra keyspace analysis, compaction strategies, repair status, nodetool operations, and cluster health monitoring.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Checkov — checkov infrastructure-as-code security scanning. Covers Terraform, CloudFormation, Kubernetes, and Dockerfile scanning, policy management, custom checks, compliance frameworks, and suppression management. Use when scanning IaC for security misconfigurations, evaluating compliance, managing custom policies, or reviewing scan results.
日本語の概要は準備中です。原文の説明を表示しています。