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 Kinesis — aWS Kinesis stream management, shard analysis, consumer lag monitoring, enhanced fan-out configuration, and throughput analysis.
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 and manage Kinesis streams with safe, read-only operations.
You MUST follow this two-phase pattern. Skipping Phase 1 causes hallucinated stream/consumer names.
#!/bin/bash
# 1. List streams
aws kinesis list-streams --output json | jq -r '.StreamNames[]'
# 2. Describe stream
aws kinesis describe-stream-summary --stream-name "$STREAM_NAME" --output json
# 3. List shards
aws kinesis list-shards --stream-name "$STREAM_NAME" --output json | jq '.Shards[] | {ShardId, HashKeyRange, SequenceNumberRange}'
# 4. List stream consumers (enhanced fan-out)
aws kinesis list-stream-consumers --stream-arn "$STREAM_ARN" --output json
# 5. Describe stream consumer
aws kinesis describe-stream-consumer --stream-arn "$STREAM_ARN" --consumer-name "$CONSUMER_NAME" --output json 2>/dev/null
Phase 1 outputs:
Only reference stream names, shard IDs, and consumer names confirmed in Phase 1.
#!/bin/bash
# Core Kinesis helper — always use this
kinesis_cmd() {
aws kinesis "$@" --output json
}
# CloudWatch metric for Kinesis
kinesis_metric() {
local stream="$1" metric="$2" stat="${3:-Sum}" period="${4:-300}"
aws cloudwatch get-metric-statistics \
--namespace AWS/Kinesis \
--metric-name "$metric" \
--dimensions Name=StreamName,Value="$stream" \
--start-time "$(date -u -v-1H +%Y-%m-%dT%H:%M:%S 2>/dev/null || date -u -d '1 hour ago' +%Y-%m-%dT%H:%M:%S)" \
--end-time "$(date -u +%Y-%m-%dT%H:%M:%S)" \
--period "$period" \
--statistics "$stat" \
--output json
}
list-streamslist-shards#!/bin/bash
echo "=== Kinesis Streams ==="
for STREAM in $(aws kinesis list-streams --output json | jq -r '.StreamNames[]'); do
SUMMARY=$(kinesis_cmd describe-stream-summary --stream-name "$STREAM" | jq '.StreamDescriptionSummary')
echo "$STREAM:"
echo " Status: $(echo $SUMMARY | jq -r '.StreamStatus')"
echo " Shards: $(echo $SUMMARY | jq -r '.OpenShardCount')"
echo " Mode: $(echo $SUMMARY | jq -r '.StreamModeDetails.StreamMode')"
echo " Consumers: $(echo $SUMMARY | jq -r '.ConsumerCount')"
echo " Retention: $(echo $SUMMARY | jq -r '.RetentionPeriodHours')h"
done
#!/bin/bash
STREAM="${1:-my-stream}"
echo "=== Shards ==="
kinesis_cmd list-shards --stream-name "$STREAM" | jq '.Shards[] | {ShardId, ParentShardId: .ParentShardId, HashKeyRange: "\(.HashKeyRange.StartingHashKey[0:10])...\(.HashKeyRange.EndingHashKey[0:10])"}'
echo ""
echo "=== Write Throughput per Shard ==="
kinesis_metric "$STREAM" "IncomingRecords" "Sum" 60 | jq -r '.Datapoints | sort_by(.Timestamp) | .[-5:][] | "\(.Timestamp)\t\(.Sum) records"'
echo ""
echo "=== Read Throughput ==="
kinesis_metric "$STREAM" "GetRecords.Records" "Sum" 60 | jq -r '.Datapoints | sort_by(.Timestamp) | .[-5:][] | "\(.Timestamp)\t\(.Sum) records"'
#!/bin/bash
STREAM="${1:-my-stream}"
echo "=== Iterator Age (lag) ==="
kinesis_metric "$STREAM" "GetRecords.IteratorAgeMilliseconds" "Maximum" 60 | jq -r '.Datapoints | sort_by(.Timestamp) | .[-5:][] | "\(.Timestamp)\t\(.Maximum)ms"'
echo ""
echo "=== Read Provisioned Throughput Exceeded ==="
kinesis_metric "$STREAM" "ReadProvisionedThroughputExceeded" "Sum" 300 | jq -r '.Datapoints | sort_by(.Timestamp) | .[] | select(.Sum > 0) | "\(.Timestamp)\t\(.Sum)"'
echo ""
echo "=== Write Provisioned Throughput Exceeded ==="
kinesis_metric "$STREAM" "WriteProvisionedThroughputExceeded" "Sum" 300 | jq -r '.Datapoints | sort_by(.Timestamp) | .[] | select(.Sum > 0) | "\(.Timestamp)\t\(.Sum)"'
echo ""
echo "=== Enhanced Fan-out Consumers ==="
STREAM_ARN=$(kinesis_cmd describe-stream-summary --stream-name "$STREAM" | jq -r '.StreamDescriptionSummary.StreamARN')
kinesis_cmd list-stream-consumers --stream-arn "$STREAM_ARN" | jq '.Consumers[] | {ConsumerName, ConsumerStatus, ConsumerCreationTimestamp}'
#!/bin/bash
STREAM="${1:-my-stream}"
echo "=== Incoming Bytes ==="
kinesis_metric "$STREAM" "IncomingBytes" "Sum" 60 | jq -r '.Datapoints | sort_by(.Timestamp) | .[-5:][] | "\(.Timestamp)\t\(.Sum / 1024 | round)KB"'
echo ""
echo "=== Outgoing Bytes ==="
kinesis_metric "$STREAM" "GetRecords.Bytes" "Sum" 60 | jq -r '.Datapoints | sort_by(.Timestamp) | .[-5:][] | "\(.Timestamp)\t\(.Sum / 1024 | round)KB"'
echo ""
echo "=== Put Latency ==="
kinesis_metric "$STREAM" "PutRecord.Latency" "Average" 60 | jq -r '.Datapoints | sort_by(.Timestamp) | .[-5:][] | "\(.Timestamp)\t\(.Average)ms"'
Present results as a structured report:
Managing Aws Kinesis 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 |
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。