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 API Gateway — analyzing REST or HTTP APIs, debugging latency or 5xx errors, auditing throttling and stage configuration, reviewing usage plans, or checking authorization setup. Covers API inventory, CloudWatch metrics, stage audits, and integration health for both REST (v1) and HTTP (v2) APIs.
インストール方法を見る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。
Analyze AWS API Gateway REST and HTTP APIs with parallel execution and anti-hallucination guardrails.
| Need | Use | Why |
|---|---|---|
| Usage plans / API keys | REST API | HTTP APIs don't support usage plans |
| Request validation / WAF | REST API | Not available in HTTP API |
| Execution logging / X-Ray | REST API | HTTP API only supports access logging |
| Lowest cost | HTTP API | $1/M vs $3.50/M requests |
| WebSocket support | HTTP API (v2) | Only v2 supports WebSocket protocol |
| Auto-deploy | HTTP API | REST requires explicit deployment |
| Simple proxy to Lambda | HTTP API | Simpler, cheaper, auto-deploy |
CRITICAL: Discover both REST and HTTP APIs in parallel. NEVER assume API names or IDs.
#!/bin/bash
export AWS_PAGER=""
echo "=== REST APIs (apigateway) ==="
aws apigateway get-rest-apis \
--output text \
--query 'items[].[id,name,endpointConfiguration.types[0]]' &
echo "=== HTTP APIs (apigatewayv2) ==="
aws apigatewayv2 get-apis \
--output text \
--query 'Items[].[ApiId,Name,ProtocolType]' &
wait
Run ALL independent operations in parallel using & and wait.
#!/bin/bash
export AWS_PAGER=""
END=$(date -u +"%Y-%m-%dT%H:%M:%S")
START=$(date -u -d "7 days ago" +"%Y-%m-%dT%H:%M:%S" 2>/dev/null || date -u -v-7d +"%Y-%m-%dT%H:%M:%S")
# REST APIs: use ApiName dimension
APIS=$(aws apigateway get-rest-apis --output text --query 'items[].[name]')
for api in $APIS; do
{
latency=$(aws cloudwatch get-metric-statistics \
--namespace AWS/ApiGateway --metric-name Latency \
--dimensions Name=ApiName,Value="$api" \
--start-time "$START" --end-time "$END" \
--period 604800 --statistics Average Maximum \
--output text --query 'Datapoints[0].[Average,Maximum]')
errors=$(aws cloudwatch get-metric-statistics \
--namespace AWS/ApiGateway --metric-name 5XXError \
--dimensions Name=ApiName,Value="$api" \
--start-time "$START" --end-time "$END" \
--period 604800 --statistics Sum \
--output text --query 'Datapoints[0].Sum')
printf "REST\t%s\tLatency:%s\t5xx:%s\n" "$api" "$latency" "${errors:-0}"
} &
done
# HTTP APIs: use ApiId dimension and lowercase metric names
HTTP_APIS=$(aws apigatewayv2 get-apis --output text --query 'Items[].[ApiId,Name]')
echo "$HTTP_APIS" | while read api_id api_name; do
{
latency=$(aws cloudwatch get-metric-statistics \
--namespace AWS/ApiGateway --metric-name Latency \
--dimensions Name=ApiId,Value="$api_id" \
--start-time "$START" --end-time "$END" \
--period 604800 --statistics Average Maximum \
--output text --query 'Datapoints[0].[Average,Maximum]')
errors=$(aws cloudwatch get-metric-statistics \
--namespace AWS/ApiGateway --metric-name 5xx \
--dimensions Name=ApiId,Value="$api_id" \
--start-time "$START" --end-time "$END" \
--period 604800 --statistics Sum \
--output text --query 'Datapoints[0].Sum')
printf "HTTP\t%s(%s)\tLatency:%s\t5xx:%s\n" "$api_name" "$api_id" "$latency" "${errors:-0}"
} &
done
wait
#!/bin/bash
export AWS_PAGER=""
APIS=$(aws apigateway get-rest-apis --output text --query 'items[].id')
for api_id in $APIS; do
aws apigateway get-stages --rest-api-id "$api_id" \
--output text \
--query "item[].[\"$api_id\",stageName,cacheClusterEnabled,tracingEnabled,methodSettings.*.loggingLevel]" &
done
wait
#!/bin/bash
export AWS_PAGER=""
# Account-level limits
aws apigateway get-account \
--output text --query '[throttleSettings.burstLimit,throttleSettings.rateLimit]'
# Usage plans (REST only)
aws apigateway get-usage-plans \
--output text \
--query 'items[].[id,name,throttle.burstLimit,throttle.rateLimit,quota.limit,quota.period]'
| Rule | Detail |
|---|---|
| REST vs HTTP CLI | apigateway (REST/v1) vs apigatewayv2 (HTTP/WebSocket). NEVER mix. |
| CloudWatch dimensions | REST uses ApiName; HTTP uses ApiId. Wrong dimension = empty results. |
| Metric name casing | REST: 5XXError; HTTP: 5xx. Check API type before querying. |
| Usage plans | REST API only. HTTP APIs use route-level throttling. |
| Latency metrics | Latency = total (including APIGW overhead). IntegrationLatency = backend only. |
| Stage requirement | Metrics require Stage dimension for per-stage accuracy. |
| Deployment | REST: changes require new deployment. HTTP: auto-deploy by default. |
| Shortcut | Counter | Why |
|---|---|---|
| "I'll just check REST APIs" | Always discover both REST and HTTP APIs | HTTP APIs are increasingly common; missing them gives incomplete picture |
| "Metrics aren't needed for health check" | Always check CloudWatch metrics | APIs can return 200 while silently failing on a subset of requests |
| "Default stage config is fine" | Audit stage config explicitly | Defaults leave execution logging, tracing, and caching disabled |
| "Usage plans aren't relevant" | Review if REST API has external consumers | Unthrottled APIs cause cascading failures under load |
| "The API is responding, so it's healthy" | Check error rates AND latency percentiles | p50 may be fine while p99 is unacceptable |
API Gateway Health Report
═══════════════════════════
REST APIs: [count] | HTTP APIs: [count]
API Type Stage Latency(avg/max) 5xx(7d) Cache Logging Tracing
─────────────────────────────────────────────────────────────────────────────
my-api REST prod 45ms/230ms 12 ON ERROR ON
payment-api HTTP $def 22ms/89ms 0 N/A ACCESS N/A
Throttling: Account [burst/rate] | Plans: [count]
Issues: [list of findings with severity]
--statistics Average Maximum.apigatewayv2 with ProtocolType=WEBSOCKET. Different metric dimensions.-v-7d, Linux uses -d "7 days ago". Scripts handle both.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。