Cloudflare GraphQL Analytics for zone traffic, firewall events, Workers metrics, and schema exploration. Use when querying Cloudflare analytics data or exploring the GraphQL API.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Aws Rds Deep — aWS RDS deep analysis covering Performance Insights, event subscriptions, proxy management, and global database status. Covers PI counter metrics, wait event analysis, top SQL queries, read replica lag, storage autoscaling, and Aurora-specific diagnostics.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Deep analysis of AWS RDS instances with parallel execution and anti-hallucination guardrails.
Relationship to other AWS skills:
aws-rds-deep/ → RDS deep-dive analysis (Performance Insights, proxies, global DBs)aws/ → "How to execute" (parallel patterns, throttling, output format)aws-rightsizing/ → RDS rightsizing recommendationsALL independent operations MUST run in parallel using background jobs (&) and wait.
#!/bin/bash
export AWS_PAGER=""
for db in $databases; do
get_db_performance "$db" &
done
wait
#!/bin/bash
export AWS_PAGER=""
# List RDS instances with Performance Insights status
list_rds_instances() {
aws rds describe-db-instances \
--output text \
--query 'DBInstances[].[DBInstanceIdentifier,Engine,EngineVersion,DBInstanceClass,DBInstanceStatus,PerformanceInsightsEnabled,MultiAZ,StorageType,AllocatedStorage]'
}
# Get Performance Insights resource metrics
get_pi_metrics() {
local resource_arn=$1 hours=${2:-1}
local end_time start_time
end_time=$(date +%s)
start_time=$((end_time - hours * 3600))
aws pi get-resource-metrics \
--service-type RDS \
--identifier "$resource_arn" \
--metric-queries '[{"Metric":"db.load.avg"}]' \
--start-time "$start_time" --end-time "$end_time" \
--period-in-seconds 300 \
--output text \
--query 'MetricList[0].DataPoints[*].[Timestamp,Value]' | tail -10
}
# Get top wait events from PI
get_pi_wait_events() {
local resource_arn=$1 hours=${2:-1}
local end_time start_time
end_time=$(date +%s)
start_time=$((end_time - hours * 3600))
aws pi get-resource-metrics \
--service-type RDS \
--identifier "$resource_arn" \
--metric-queries '[{"Metric":"db.load.avg","GroupBy":{"Group":"db.wait_event","Limit":10}}]' \
--start-time "$start_time" --end-time "$end_time" \
--period-in-seconds $((hours * 3600)) \
--output text \
--query 'MetricList[0].DataPoints[0].Value'
}
# List RDS event subscriptions
list_event_subscriptions() {
aws rds describe-event-subscriptions \
--output text \
--query 'EventSubscriptionsList[].[CustSubscriptionId,Status,SnsTopicArn,SourceType,Enabled]'
}
# List RDS proxies
list_proxies() {
aws rds describe-db-proxies \
--output text \
--query 'DBProxies[].[DBProxyName,Status,EngineFamily,VpcId,IdleClientTimeout,RequireTLS]' 2>/dev/null
}
# Get read replica lag
get_replica_lag() {
local instance_id=$1
local end_time start_time
end_time=$(date -u +"%Y-%m-%dT%H:%M:%S")
start_time=$(date -u -d "1 hour ago" +"%Y-%m-%dT%H:%M:%S" 2>/dev/null || date -u -v-1H +"%Y-%m-%dT%H:%M:%S")
aws cloudwatch get-metric-statistics \
--namespace AWS/RDS --metric-name ReplicaLag \
--dimensions Name=DBInstanceIdentifier,Value="$instance_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 rds describe-db-instances \
--output text \
--query 'DBInstances[].[DBInstanceIdentifier,Engine,DBInstanceClass,DBInstanceStatus,PerformanceInsightsEnabled,MultiAZ,ReadReplicaDBInstanceIdentifiers[0]]' | sort -k2
#!/bin/bash
export AWS_PAGER=""
PI_INSTANCES=$(aws rds describe-db-instances \
--output text \
--query 'DBInstances[?PerformanceInsightsEnabled==`true`].[DbiResourceId,DBInstanceIdentifier]')
END=$(date +%s)
START=$((END - 3600))
echo "$PI_INSTANCES" | while read resource_id db_name; do
{
load=$(aws pi get-resource-metrics \
--service-type RDS --identifier "db-$resource_id" \
--metric-queries '[{"Metric":"db.load.avg"}]' \
--start-time "$START" --end-time "$END" \
--period-in-seconds 3600 \
--output text \
--query 'MetricList[0].DataPoints[0].Value')
printf "%s\tDBLoad:%s\n" "$db_name" "${load:-N/A}"
} &
done
wait
#!/bin/bash
export AWS_PAGER=""
REPLICAS=$(aws rds describe-db-instances \
--output text \
--query 'DBInstances[?ReadReplicaSourceDBInstanceIdentifier!=null].DBInstanceIdentifier')
END=$(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 $REPLICAS; do
aws cloudwatch get-metric-statistics \
--namespace AWS/RDS --metric-name ReplicaLag \
--dimensions Name=DBInstanceIdentifier,Value="$replica" \
--start-time "$START" --end-time "$END" \
--period 300 --statistics Average Maximum \
--output text --query "Datapoints[-1].[\"$replica\",Average,Maximum]" &
done
wait
#!/bin/bash
export AWS_PAGER=""
PROXIES=$(aws rds describe-db-proxies --output text --query 'DBProxies[].DBProxyName' 2>/dev/null)
for proxy in $PROXIES; do
{
info=$(aws rds describe-db-proxies --db-proxy-name "$proxy" \
--output text --query 'DBProxies[].[DBProxyName,Status,EngineFamily,IdleClientTimeout,RequireTLS]')
targets=$(aws rds describe-db-proxy-targets --db-proxy-name "$proxy" \
--output text --query 'Targets[].[RdsResourceId,TargetHealth.State,TargetHealth.Description,Type]' 2>/dev/null)
printf "%s\nTargets:\n%s\n" "$info" "$targets"
} &
done
wait
#!/bin/bash
export AWS_PAGER=""
aws rds describe-event-subscriptions \
--output text \
--query 'EventSubscriptionsList[].[CustSubscriptionId,Status,SourceType,Enabled]' &
aws rds describe-events --duration 1440 \
--output text \
--query 'Events[].[Date,SourceIdentifier,SourceType,Message]' | tail -20 &
wait
db-ABCDEFGHIJKLMN), NOT DBInstanceIdentifier. Get it from describe-db-instances.PerformanceInsightsEnabled before querying PI APIs.MaxAllocatedStorage being set does not mean autoscaling is active. Check if MaxAllocatedStorage > AllocatedStorage.describe-db-instances but are managed differently. Aurora uses clusters (describe-db-clusters), reader/writer endpoints, and shared storage.Present results as a structured report:
Aws Rds 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 |
describe-global-clusters.MaxConnectionsPercent and MaxIdleConnectionsPercent.--statistics Average Maximum.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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Cloudflare GraphQL Analytics for zone traffic, firewall events, Workers metrics, and schema exploration. Use when querying Cloudflare analytics data or exploring the GraphQL API.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Alloydb — google AlloyDB instance analysis, query insights, columnar engine optimization, maintenance windows, and cluster health.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Bigquery — google BigQuery job analysis, slot utilization, cost analysis, dataset management, and query optimization.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Cassandra — apache Cassandra keyspace analysis, compaction strategies, repair status, nodetool operations, and cluster health monitoring.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.