agents-deploy
Use when deploying your agent to AWS, or when a deploy has failed. Handles pre-flight validation, CDK/IAM/quota error diagnosis, version management, rollback, and canary deployments. Triggers on: "deploy my agent", "agentcore deploy", "deploy failed", "CDK error", "rollback", "canary deploy", "pin version", "redeploy", "deploy stuck". Not for production hardening — use agents-harden. Not for adding capabilities before deploy — use agents-build or agents-connect. Not for VPC configuration errors — use agents-build.
Overview
deploy
Deploy your AgentCore agent to AWS, or diagnose why a deploy failed.
When to use
- You're ready to deploy and want to validate config first
agentcore deployfailed with an error- You want to preview what deploy will create without actually deploying
- You want to deploy to a specific target (staging, production)
- You need to roll back to a previous version, pin to a specific version, or set up canary deployments
Input
$ARGUMENTS is optional:
/agents-deploy # interactive — pre-flight check or diagnose failure
/agents-deploy preflight # validate config and IAM before deploying
/agents-deploy diagnose # diagnose a failed deploy (paste error or read logs)
/agents-deploy preview # show what deploy will create without deploying
/agents-deploy rollback # roll back to a previous versionProcess
Step 0: Verify CLI version
Run agentcore --version. This skill requires v0.9.0 or later. If the version is older, tell the developer to run agentcore update before proceeding.
Step 1: Determine the situation
Read agentcore/agentcore.json and agentcore/aws-targets.json if they exist.
Ask (or infer from context):
"Are you:
- About to deploy and want to check everything first
- Dealing with a failed deploy — what error did you see?
- Needing to roll back or pin a specific version?"
If the developer needs versioning, rollback, or canary deployment, load references/versioning.md and follow its instructions.
Path A: Pre-flight validation
Run these checks before agentcore deploy:
Check 1: Validate config files
Show the developer this command to run:
agentcore validateThis catches malformed agentcore.json before CDK even starts.
Check 2: Verify region alignment
The most common deploy failure is a region mismatch. Show the developer these commands to verify:
# Your configured AWS region
aws configure get region
# The region in your deployment target
cat agentcore/aws-targets.json
# The account you're actually authenticated as
aws sts get-caller-identityThe region in aws-targets.json must match your aws configure default region. The account must match the account ID from sts get-caller-identity.
Check 3: Verify Bedrock model access
Show the developer this command to check enabled models in their region:
aws bedrock list-foundation-models --region $(aws configure get region) \
--query 'modelSummaries[?modelLifecycle.status==`ACTIVE`].modelId' \
--output tableCross-region inference profile IDs use a geographic prefix (us., eu., apac.) or global. to control where inference runs. The CLI scaffolds global. by default (e.g., global.anthropic.claude-sonnet-4-5-20250929-v1:0), which routes to any commercial region. Geographic prefixes keep inference within that geography (e.g., eu. stays in EU regions). All prefixes require model access enabled in every destination region the profile covers. Check the Bedrock docs for which regions are included in each profile prefix.
Check 4: Preview what will be deployed
agentcore deploy --dry-run
agentcore deploy --diff--dry-run shows what resources will be created. --diff shows the CDK diff against what's currently deployed.
Check 5: Verify IAM permissions
Show the developer the permissions needed and this verification command:
aws iam simulate-principal-policy \
--policy-source-arn $(aws sts get-caller-identity --query Arn --output text) \
--action-names iam:CreateRole \
--resource-arns "arn:aws:iam::*:role/*BedrockAgentCore*"Run the deploy
agentcore deploy -y # auto-confirm (alias: agentcore dp -y)
agentcore deploy -y -v # verbose — shows resource-level events
agentcore deploy --target staging -y # deploy to a specific targetMemory provisioning note: If your project includes memory, deploy takes 2–5 minutes longer while the memory resource becomes ACTIVE. This is normal — not an error. Check status:
agentcore status --type memoryPath B: Diagnose a failed deploy
Step B1: Read the error
If the developer pasted an error, diagnose it directly. If not, read the deploy logs:
# View recent deploy logs
ls -lt agentcore/.cli/logs/
cat agentcore/.cli/logs/deploy-*.log 2>/dev/null | tail -100Step B2: Match to known failure patterns
IAM permission error:
User: arn:aws:iam::123456789012:user/dev is not authorized to perform: iam:CreateRoleFix: Attach the required IAM permissions (see Check 5 above). The deploying identity needs IAM write access scoped to *BedrockAgentCore* roles.
CDK bootstrap not run:
This stack uses assets, so the toolkit stack must be deployed to the environmentFix:
npx cdk bootstrap aws://<YOUR_ACCOUNT_ID>/<REGION>ECR authorization error:
no basic auth credentials
Error response from daemon: Head "https://<YOUR_ACCOUNT_ID>.dkr.ecr.<REGION>.amazonaws.com/..."Fix:
aws ecr get-login-password --region <REGION> | \
docker login --username AWS --password-stdin <YOUR_ACCOUNT_ID>.dkr.ecr.<REGION>.amazonaws.comModel access denied during deploy:
ValidationException: The provided model identifier is invalidFix: Enable the model in the Bedrock console → Model access. Ensure the model ID in agentcore.json matches an enabled model in your target region.
Region mismatch:
Stack ... is in region us-east-1 but the target is us-west-2Fix: Update agentcore/aws-targets.json to match your aws configure default region, or run aws configure set region <REGION>.
Memory stuck in CREATING:
Memory resource is in CREATING state after 10 minutesThis is unusual — normal provisioning takes 2–5 minutes. Check:
agentcore status --type memory --jsonIf stuck, try removing and re-adding the memory resource.
Service quota exceeded:
LimitExceededException: Account limit for AgentCore runtimes exceededFix: Request a quota increase in the AWS console → Service Quotas → Amazon Bedrock AgentCore.
Step B3: After fixing, re-run
agentcore deploy -yIf the same error recurs, check agentcore status to see the current state of all resources:
agentcore status
agentcore status --state pending-removal # resources marked for deletionDeploying to multiple targets
Define targets in agentcore/aws-targets.json:
[
{
"name": "staging",
"description": "Staging environment",
"account": "123456789012",
"region": "us-east-1"
},
{
"name": "production",
"description": "Production environment",
"account": "987654321098",
"region": "us-west-2"
}
]Deploy to a specific target:
agentcore deploy --target staging -y
agentcore deploy --target production -yOutput
- Pre-flight check results with specific fixes for any issues found
- Diagnosis of deploy failure with the specific fix
- Deploy command to run after fixes are applied
Files 2 files
Install it by hand
Deska runs this for you, for every agent you pick. To run it yourself in a terminal:
npx skills add aws/agent-toolkit-for-aws --skill agents-deployMore from aws
- aws-iamawsProvides verified corrections for IAM behaviors that AI agents frequently get wrong — policy evaluation edge cases, trust policy gotchas, STS session limits, Organizations quirks, and SAML/MFA specifics. Also provides structured workflows for IAM role management and baseline policy generation from application source code or a Terraform plan JSON. Covers condition operator safety (ForAnyValue/ForAllValues with Null checks), bucket policy deny patterns (VPC endpoint restrictions, org paths), confused deputy protection, and service role creation for AWS services (Glue, CloudTrail, Lambda, ECS, etc.) with aws:SourceAccount/aws:SourceArn trust conditions. Applies when creating IAM roles, writing IAM or bucket policies, generating policies from application source code or a Terraform plan JSON, working with STS, Organizations, or condition operators, or any task needing a service or execution role. Does not cover non-IAM authorization like Cognito user-pool policies or app-level RBAC.9,200 installs on skills.sh0
- aws-serverlessawsBuilds, deploys, manages, debugs, configures, and optimizes serverless applications on AWS using Lambda, API Gateway, Step Functions, EventBridge, and SAM/CDK. Covers cold starts, CORS debugging, event source mappings, troubleshooting, concurrency, SnapStart, Powertools, function URLs, EventBridge Scheduler, Lambda layers, and production readiness. Triggers on mentions of Lambda, API Gateway, Step Functions, SAM templates, CDK serverless stacks, DynamoDB stream triggers, SQS event sources, cold starts, timeouts, 502/504 errors, throttling, concurrency, CORS, Powertools, or any event-driven architecture on AWS, even without the word "serverless." Does not apply to EC2, ECS/Fargate containers, or Amplify hosting.9,000 installs on skills.sh0
- aws-observabilityawsBuilds, configures, debugs, and optimizes AWS observability - operator-symptom questions and detecting Omni vs classic CloudWatch. CloudWatch on an already-reporting service: Log Insights, metric/composite/anomaly alarms, custom metrics/EMF, dashboards, X-Ray/ADOT tracing, canaries, CloudTrail, Dynamic Instrumentation (live breakpoints/snapshots), the Application Signals service map, and fleet health views. CloudWatch Omni on an existing Space: SQL over logs and traces, PromQL over metrics, Omni dashboards, Omni alerts, context graph for root cause, programmatic/IaC access (API/SDK/CLI/CloudFormation), driving Omni from a coding agent or skills, and evaluating AI agent quality from traces - on-demand and online scoring of live traffic, readback, custom evaluators. For first-time setup - creating an Omni Space, granting access, ingestion, or ADOT instrumentation for Application Signals (ServiceEvents, CI/CD metadata) or Omni - use setting-up-cloudwatch-observability. Not for app logging or threat detection.8,900 installs on skills.sh0
- aws-cdkawsAuthors, deploys, and troubleshoots AWS infrastructure using CDK with TypeScript or Python. Covers best practices, stack architecture, and construct patterns. Applies when writing CDK constructs, bootstrapping environments, running cdk deploy/synth/diff, fixing CDK or CloudFormation errors, planning stack structure, importing existing resources, resolving drift, or refactoring stacks without resource replacement.8,400 installs on skills.sh0
- aws-containersawsBuilds and deploys containerized workloads on Elastic Kubernetes Service (EKS), Elastic Container Service (ECS), Fargate, and ECR (Elastic Container Registry). Covers general EKS knowledge, Karpenter, AWS Load Balancer Controller and leveraging various open source Kubernetes projects with EKS. Covers general ECS knowledge, task definitions, Fargate services, ECS Exec, ECS Express Mode and ECS Managed Instances. Covers general Elastic Beanstalk knowledge, Elastic Beanstalk configuration and platforms supported by Elastic Beanstalk. Covers general ECR knowledge, ECR repository setup and lifecycle policies. Includes recommending, enabling, and reading Amazon ECS Action Logs to troubleshoot control-plane failures (deployment rollback/circuit-breaker, task placement, scaling, task replacement). Applies when deploying, debugging, or optimizing containers on AWS. Should be used instead of relying on internal knowledge for these services.8,300 installs on skills.sh0