Moving an existing project to a new command-line interface is not simply a matter of installing the latest version. A CLI upgrade can affect project configuration, authentication, deployment commands, environment variables, and automation scripts. If these changes are not checked carefully, a project that worked locally may fail in a CI/CD pipeline or deployment environment.
The Amazon Bedrock AgentCore CLI helps developers work with agent-based applications built around Amazon Bedrock AgentCore. When moving an existing project to version 1.0, the goal should be to preserve the application's behavior while updating its development and deployment workflow.
The exact migration steps depend on the CLI version currently installed, the project's framework, and the commands supported by the target release. Before changing an existing project, verify the official version-specific documentation and release notes for the CLI distribution you use.
This article explains a practical migration approach, including environment checks, configuration reviews, testing, and common mistakes.
What to Check Before Migrating
Before changing the CLI, identify how the current project uses it.
An existing project might use the CLI to initialize an agent, configure its runtime, run it locally, prepare deployment artifacts, or deploy it to AWS. Some projects may also call CLI commands from shell scripts or automated workflows.
Start by recording the current environment.
aws --version
aws sts get-caller-identity
The first command displays the installed AWS CLI version. The second verifies the identity associated with the current AWS credentials.
These commands do not identify the AgentCore CLI version itself. Use the version command supported by your installed AgentCore CLI distribution to record that information.
Also record the following details:
The current AgentCore CLI version and installation method.
The language and framework used by the application.
The AWS account and region used for development.
The runtime configuration and environment variables.
The commands used for local testing and deployment.
The CI/CD workflows that invoke the CLI.
This information provides a baseline for identifying migration-related changes.
Step 1: Review the Existing Project Structure
Start by examining the repository rather than immediately upgrading the CLI.
A typical agent project might contain application code, dependency definitions, configuration files, tests, and deployment scripts.
For example:
customer-support-agent/
├── src/
│ └── agent.py
├── tests/
│ └── test_agent.py
├── requirements.txt
├── .env.example
├── README.md
└── deploy.sh
This is an illustrative structure, not a required AgentCore project layout.
Identify which files are generated by the CLI and which are maintained manually. This distinction matters because a newer CLI may generate a different configuration structure or introduce new defaults.
Check the repository's current state before running initialization or migration commands.
git status
git log -5 --oneline
If the working tree contains uncommitted changes, commit or safely preserve them before continuing.
Do not assume that running an initialization command against an existing project is harmless. Depending on the CLI implementation, initialization may create files, modify configuration, or report that the project already exists.
Step 2: Install and Verify CLI Version 1.0
Use the installation method documented for the specific AgentCore CLI distribution. Avoid copying installation commands from an unrelated AWS tool or an older tutorial.
If the CLI is distributed through a Python package, for example, an isolated environment can help prevent dependency conflicts.
python -m venv .venv
Activate the environment using the appropriate command for your operating system.
On Linux or macOS:
source .venv/bin/activate
On Windows PowerShell:
.\.venv\Scripts\Activate.ps1
Install the CLI using the package name and version specified in its current installation documentation. The following is only a placeholder pattern, not a verified installation command:
python -m pip install <documented-package-name>==1.0.0
Do not use this pattern until you have confirmed the actual package name and release version. A product version of 1.0 does not necessarily mean its package is published as version 1.0.0.
After installation, run the documented version command and confirm that the expected executable is being used.
If the command still reports an older version, check whether another installation exists earlier in the system's executable search path.
Step 3: Compare Commands and Configuration
One of the most important migration tasks is comparing the commands used by the old CLI with those supported by the new version.
Do not assume that command names, arguments, configuration fields, or defaults remain unchanged.
Create a migration checklist covering the operations your project actually uses.
Area | What to verify | Why it matters |
|---|
Initialization | Project creation and configuration commands | Prevent accidental file changes |
Local execution | Commands and required arguments | Keep the development workflow working |
Runtime settings | Environment variables and runtime configuration | Preserve application behavior |
Authentication | AWS credential and role configuration | Avoid access failures |
Deployment | Artifact preparation and deployment commands | Prevent failed releases |
Automation | Shell scripts and CI/CD steps | Keep automated workflows compatible |
Diagnostics | Logging and error-reporting options | Make failures easier to investigate |
Use the version-specific help output to inspect supported commands and arguments.
For example, if the CLI supports a standard help option, run its top-level help command and then inspect the relevant subcommands.
Do not mechanically replace old command names with new ones. A command that appears similar may have different defaults or requirements.
Step 4: Review AWS Credentials and Permissions
A CLI upgrade does not automatically guarantee that the project has the correct AWS permissions.
Check which identity the application or deployment workflow uses. For local development, the following command can help verify the active AWS identity:
aws sts get-caller-identity
Review the IAM permissions required for the project's actual operations. These may include permissions for the relevant AgentCore resources, IAM role operations, logging, or other AWS services used by the application.
The required permissions depend on the features enabled in the project. Do not grant broad administrative access merely to make a migration error disappear.
For production deployments, prefer an appropriate IAM role and temporary credentials over long-lived access keys stored in source code.
Also check whether the application and deployment process use the intended AWS region. A successful authentication check does not prove that the required resources exist in that region.
Step 5: Update Configuration and Environment Variables
Compare the existing project configuration with the schema supported by the new CLI.
Look for renamed fields, changed defaults, newly required settings, and obsolete options. Confirm each change against the documentation for the target version.
Keep application secrets outside source control.
For example, an environment file template might contain:
AWS_REGION=your-region
AGENT_ENVIRONMENT=development
These are illustrative application settings, not guaranteed AgentCore CLI variables.
The actual names must match the application and the CLI configuration supported by your project.
Commit a template containing non-sensitive settings, but do not commit real access keys, passwords, or tokens. If a secret was previously committed, removing it from the latest file is not sufficient by itself; the exposed credential should be rotated.
After updating configuration, test the application using the same environment variables and runtime settings that will be used during deployment.
Step 6: Validate the Migration Locally
Once the CLI and configuration have been updated, verify the application before deploying it.
Start with the project's existing automated tests.
python -m pytest
This example applies to a Python project that uses pytest. Use the appropriate test command for projects written in other languages.
Next, run the documented AgentCore CLI command for local execution or validation, if supported by your CLI version.
Check the following:
The application starts without configuration errors.
Required environment variables are available.
The agent can access the services it needs.
Existing tests continue to pass.
Error messages and logs remain useful.
The application handles expected failure conditions.
A successful startup does not prove that every integration works. Include tests for important external dependencies and failure cases where practical.
Step 7: Update CI/CD Workflows
After local validation, update the automation that builds and deploys the application.
A pipeline should use a known CLI version rather than silently installing whichever version happens to be latest.
For example, a simplified shell-based workflow could follow this pattern:
set -e
# Install the CLI using the documented, pinned version.
# Run the project's automated tests.
# Execute the documented CLI validation command.
# Deploy only after validation succeeds.
The comments are placeholders for the actual commands supported by your project.
In a real pipeline, pin the CLI and relevant application dependencies. Use the CI platform's supported secret-management mechanism for credentials, and prefer short-lived authentication where available.
Test the updated workflow in a development environment before using it for production deployments.
Common Migration Mistakes
Assuming version 1.0 is backward-compatible
A major release may introduce behavior changes, but the version number alone does not establish which changes exist. Review the actual release notes and migration documentation.
Reinitializing an existing project without checking its files
Initialization may change configuration or create new files. Inspect the changes with version control before accepting them.
Updating the local CLI but not the pipeline
A developer's machine may use version 1.0 while the CI/CD runner still installs an older version. Pin and verify the version in both environments.
Fixing permission errors with excessive IAM access
Broad permissions can hide the actual problem and create unnecessary security risk. Identify the denied operation and grant only the permissions required for the intended task.
Skipping deployment validation
A project that passes unit tests may still fail because of missing runtime permissions, incorrect environment variables, or deployment configuration differences. Include an integration or staging test before production rollout.
Troubleshooting Common Problems
Problem | Possible cause | What to check |
|---|
The CLI reports an unexpected version | Multiple installations or an incorrect environment | Inspect the executable path and active environment |
A command is no longer recognized | The command or syntax differs in the target version | Review the new CLI help and migration notes |
AWS reports an access-denied error | Missing permissions or an incorrect identity | Verify the active identity and the denied operation |
Local execution fails | Missing dependencies or environment settings | Compare the local environment with the project configuration |
CI/CD fails while local execution succeeds | Different CLI versions, credentials, or environment variables | Compare runner setup with the validated local setup |
Deployment succeeds but the agent fails at runtime | Runtime permissions or application configuration may be incorrect | Inspect runtime logs and service-specific settings |
Treat error messages as evidence rather than immediately changing several settings at once. Change one relevant item, rerun the failing operation, and record the result. This makes the cause easier to identify.
Best Practices for a Safe Migration
A reliable migration process should be repeatable and easy to review.
Commit the existing project before making changes.
Read the release notes and migration instructions for the exact CLI distribution.
Pin the CLI version in local development documentation and CI/CD workflows.
Compare configuration files before accepting generated changes.
Keep credentials and sensitive environment variables out of source control.
Use least-privilege IAM permissions.
Run unit tests and relevant integration tests before deployment.
Validate the updated project in a development or staging environment.
Keep a rollback plan for the deployment and configuration changes.
Document the new commands so that other developers can reproduce the setup.
Where practical, automate the version check and basic validation steps. This reduces the chance that different developers or build agents use inconsistent tooling.
Advantages and Disadvantages of Migrating
The main advantage of moving to a newer CLI is access to the capabilities, fixes, and supported workflows provided by that release. It can also provide an opportunity to remove outdated scripts and standardize project setup.
However, migration requires time for compatibility checks, testing, and documentation updates. If a project depends on undocumented behavior or an older configuration format, the work may be more involved than a simple installation change.
The decision should be based on the target release's documented changes and the project's actual dependencies, not on the version number alone.
Summary
Moving an existing project to Amazon Bedrock AgentCore CLI 1.0 should begin with an inventory of the current project, its configuration, and the commands used in development and deployment.
Install the documented target version, compare the supported commands and configuration, verify AWS credentials and permissions, and update automation scripts where necessary. Run tests locally, validate the deployment in a safe environment, and confirm that the production runtime still behaves as expected.
The most important principle is to make the migration controlled and verifiable. When each change is reviewed and tested independently, developers can identify compatibility problems earlier and reduce the risk of disrupting an existing agent application.
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