Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.
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。
Deploy containers on ECS and Fargate. Configure task definitions, services, and load balancing. Use when running containerized workloads on AWS.
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。
Run containerized applications on Amazon ECS with Fargate serverless compute or EC2 launch type.
ecs:*, ecr:*, elasticloadbalancing:*, logs:*, iam:PassRole# Create an ECS cluster with Container Insights enabled
aws ecs create-cluster \
--cluster-name production \
--capacity-providers FARGATE FARGATE_SPOT \
--default-capacity-provider-strategy '[
{"capacityProvider": "FARGATE", "weight": 1, "base": 2},
{"capacityProvider": "FARGATE_SPOT", "weight": 3}
]' \
--settings '[{"name": "containerInsights", "value": "enabled"}]'
# List clusters
aws ecs list-clusters
# Describe cluster details
aws ecs describe-clusters --clusters production --include STATISTICS ATTACHMENTS
# Create ECR repository
aws ecr create-repository \
--repository-name myapp \
--image-scanning-configuration scanOnPush=true \
--encryption-configuration encryptionType=KMS
# Authenticate Docker to ECR
aws ecr get-login-password --region us-east-1 | \
docker login --username AWS --password-stdin 123456789012.dkr.ecr.us-east-1.amazonaws.com
# Build, tag, and push
docker build -t myapp:latest .
docker tag myapp:latest 123456789012.dkr.ecr.us-east-1.amazonaws.com/myapp:latest
docker push 123456789012.dkr.ecr.us-east-1.amazonaws.com/myapp:latest
{
"family": "myapp",
"networkMode": "awsvpc",
"requiresCompatibilities": ["FARGATE"],
"cpu": "512",
"memory": "1024",
"executionRoleArn": "arn:aws:iam::123456789012:role/ecsTaskExecutionRole",
"taskRoleArn": "arn:aws:iam::123456789012:role/ecsTaskRole",
"containerDefinitions": [
{
"name": "myapp",
"image": "123456789012.dkr.ecr.us-east-1.amazonaws.com/myapp:latest",
"essential": true,
"portMappings": [
{
"containerPort": 8080,
"protocol": "tcp"
}
],
"environment": [
{"name": "NODE_ENV", "value": "production"},
{"name": "PORT", "value": "8080"}
],
"secrets": [
{
"name": "DB_PASSWORD",
"valueFrom": "arn:aws:secretsmanager:us-east-1:123456789012:secret:myapp/db-password"
},
{
"name": "API_KEY",
"valueFrom": "arn:aws:ssm:us-east-1:123456789012:parameter/myapp/api-key"
}
],
"healthCheck": {
"command": ["CMD-SHELL", "curl -f http://localhost:8080/health || exit 1"],
"interval": 30,
"timeout": 5,
"retries": 3,
"startPeriod": 60
},
"logConfiguration": {
"logDriver": "awslogs",
"options": {
"awslogs-group": "/ecs/myapp",
"awslogs-region": "us-east-1",
"awslogs-stream-prefix": "ecs",
"awslogs-create-group": "true"
}
},
"ulimits": [
{"name": "nofile", "softLimit": 65536, "hardLimit": 65536}
]
}
]
}
# Register the task definition
aws ecs register-task-definition --cli-input-json file://task-definition.json
# List task definition revisions
aws ecs list-task-definitions --family-prefix myapp
# Deregister an old revision
aws ecs deregister-task-definition --task-definition myapp:1
# Create the CloudWatch log group first
aws logs create-log-group --log-group-name /ecs/myapp
aws logs put-retention-policy --log-group-name /ecs/myapp --retention-in-days 30
# Create ECS service with load balancer
aws ecs create-service \
--cluster production \
--service-name myapp \
--task-definition myapp:2 \
--desired-count 3 \
--launch-type FARGATE \
--platform-version LATEST \
--deployment-configuration '{
"deploymentCircuitBreaker": {"enable": true, "rollback": true},
"maximumPercent": 200,
"minimumHealthyPercent": 100
}' \
--network-configuration '{
"awsvpcConfiguration": {
"subnets": ["subnet-private-a", "subnet-private-b"],
"securityGroups": ["sg-app"],
"assignPublicIp": "DISABLED"
}
}' \
--load-balancers '[{
"targetGroupArn": "arn:aws:elasticloadbalancing:us-east-1:123456789012:targetgroup/myapp-tg/abc123",
"containerName": "myapp",
"containerPort": 8080
}]' \
--service-registries '[{
"registryArn": "arn:aws:servicediscovery:us-east-1:123456789012:service/srv-abc123"
}]' \
--enable-execute-command \
--propagate-tags SERVICE
# Rolling update - update task definition and force new deployment
aws ecs update-service \
--cluster production \
--service myapp \
--task-definition myapp:3 \
--force-new-deployment
# Watch deployment progress
aws ecs describe-services \
--cluster production \
--services myapp \
--query "services[0].deployments[].{Status:status,Running:runningCount,Desired:desiredCount,TaskDef:taskDefinition}" \
--output table
# Wait for service to stabilize
aws ecs wait services-stable --cluster production --services myapp
# Exec into a running container for debugging
aws ecs execute-command \
--cluster production \
--task arn:aws:ecs:us-east-1:123456789012:task/production/abc123 \
--container myapp \
--interactive \
--command "/bin/sh"
# Register ECS service as a scalable target
aws application-autoscaling register-scalable-target \
--service-namespace ecs \
--resource-id service/production/myapp \
--scalable-dimension ecs:service:DesiredCount \
--min-capacity 2 \
--max-capacity 20
# Target tracking policy - scale on CPU utilization
aws application-autoscaling put-scaling-policy \
--service-namespace ecs \
--resource-id service/production/myapp \
--scalable-dimension ecs:service:DesiredCount \
--policy-name cpu-target-tracking \
--policy-type TargetTrackingScaling \
--target-tracking-scaling-policy-configuration '{
"PredefinedMetricSpecification": {
"PredefinedMetricType": "ECSServiceAverageCPUUtilization"
},
"TargetValue": 70.0,
"ScaleInCooldown": 300,
"ScaleOutCooldown": 60
}'
# Scale on request count per target (ALB)
aws application-autoscaling put-scaling-policy \
--service-namespace ecs \
--resource-id service/production/myapp \
--scalable-dimension ecs:service:DesiredCount \
--policy-name request-count-tracking \
--policy-type TargetTrackingScaling \
--target-tracking-scaling-policy-configuration '{
"PredefinedMetricSpecification": {
"PredefinedMetricType": "ALBRequestCountPerTarget",
"ResourceLabel": "app/my-alb/abc123/targetgroup/myapp-tg/def456"
},
"TargetValue": 1000.0,
"ScaleInCooldown": 300,
"ScaleOutCooldown": 60
}'
resource "aws_ecs_cluster" "main" {
name = "production"
setting {
name = "containerInsights"
value = "enabled"
}
}
resource "aws_ecs_task_definition" "myapp" {
family = "myapp"
network_mode = "awsvpc"
requires_compatibilities = ["FARGATE"]
cpu = 512
memory = 1024
execution_role_arn = aws_iam_role.ecs_execution.arn
task_role_arn = aws_iam_role.ecs_task.arn
container_definitions = jsonencode([{
name = "myapp"
image = "${aws_ecr_repository.myapp.repository_url}:latest"
essential = true
portMappings = [{
containerPort = 8080
protocol = "tcp"
}]
logConfiguration = {
logDriver = "awslogs"
options = {
awslogs-group = aws_cloudwatch_log_group.myapp.name
awslogs-region = "us-east-1"
awslogs-stream-prefix = "ecs"
}
}
healthCheck = {
command = ["CMD-SHELL", "curl -f http://localhost:8080/health || exit 1"]
interval = 30
timeout = 5
retries = 3
startPeriod = 60
}
}])
}
resource "aws_ecs_service" "myapp" {
name = "myapp"
cluster = aws_ecs_cluster.main.id
task_definition = aws_ecs_task_definition.myapp.arn
desired_count = 3
launch_type = "FARGATE"
deployment_circuit_breaker {
enable = true
rollback = true
}
network_configuration {
subnets = aws_subnet.private[*].id
security_groups = [aws_security_group.app.id]
assign_public_ip = false
}
load_balancer {
target_group_arn = aws_lb_target_group.myapp.arn
container_name = "myapp"
container_port = 8080
}
enable_execute_command = true
propagate_tags = "SERVICE"
}
# Tail logs from CloudWatch
aws logs tail /ecs/myapp --follow --since 1h
# Get logs for a specific task
aws logs get-log-events \
--log-group-name /ecs/myapp \
--log-stream-name "ecs/myapp/abc123def456" \
--start-from-head
# Filter logs for errors
aws logs filter-log-events \
--log-group-name /ecs/myapp \
--filter-pattern "ERROR" \
--start-time $(date -d '1 hour ago' +%s000)
| Problem | Cause | Fix |
|---|---|---|
| Task stuck in PROVISIONING | No available capacity in subnets | Check subnet availability and capacity provider |
| Task fails immediately | Container crashes on startup | Check CloudWatch logs; run image locally first |
| Health check failing | App not ready within startPeriod | Increase startPeriod; verify health endpoint |
| Cannot pull ECR image | Execution role missing ECR permissions | Attach AmazonECSTaskExecutionRolePolicy |
| Service stuck at 0 running | Security group blocks ALB health check | Allow ALB SG to reach container port |
| Exec command fails | SSM agent not initialized | Ensure enableExecuteCommand is true; check task role |
| High Fargate costs | Not using Fargate Spot for tolerant workloads | Add FARGATE_SPOT capacity provider |
| Container OOM killed | Memory limit too low | Increase memory in task definition; check for leaks |
| Slow deployments | minimumHealthyPercent too high | Set to 50% for faster rolling updates |
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
Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.
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。
Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates. Use when shipping agent features, validating prompt changes, or gating deployments on quality.
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。
Instrument AI agents with tracing, token metrics, latency, and cost visibility. Use for reliability and debugging.
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。
Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls. Use when building, deploying, or hardening agentic AI systems that invoke tools, access data, or interact with production infrastructure.
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。
Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.
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 service mesh patterns for AI inference traffic management, mTLS, canary releases, policy enforcement, and cross-cluster resilience.
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。