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Amazon CodeWhisperer

In-IDE code assistants for faster, AWS-aware development

Free | Freemium | Paid | Enterprise ⭐⭐⭐⭐☆ 4.4/5 💻 Code Assistants 🕒 Updated
Visit Amazon CodeWhisperer ↗ Official website
Quick Verdict

Amazon CodeWhisperer is an AWS-integrated code assistant that generates line- and function-level, context-aware code suggestions and AWS SDK/IAM recommendations directly inside popular IDEs. It is ideal for backend and cloud developers building AWS services who need accurate SDK calls, security-aware prompts, and enterprise governance. Pricing includes a free tier for individuals, a $19/user/month Professional plan, and custom Enterprise options with org controls.

Best For
Backend and cloud developers building AWS-native applications
Free Tier
Available with AWS account; limited monthly recommendations
Starting Price
$19 per user per month for Professional
Standout
AWS SDK-aware completions and IAM/security guidance

Amazon CodeWhisperer is an AWS code assistant that generates line- and function-level code suggestions directly inside supported IDEs. It produces context-aware completions, recommends correct AWS SDK calls and IAM usage, and flags some security or credential risks. The primary capability is IDE-integrated code generation tailored to AWS APIs and common programming languages. Its key differentiator is AWS-aware recommendations combined with enterprise privacy controls. CodeWhisperer serves backend engineers, cloud developers, and DevOps teams working on AWS. Pricing is accessible via a free tier and paid plans for higher usage and enterprise features (pricing noted below).

About Amazon CodeWhisperer

Amazon CodeWhisperer is an AI-powered code assistant from AWS introduced for developers who build on Amazon Web Services. Positioned as an in-IDE productivity tool, CodeWhisperer aims to reduce boilerplate and speed feature delivery by generating code snippets, full functions, and API call sequences that match a developer’s local context. AWS emphasizes integration with its SDKs and cloud services so suggestions frequently include AWS-specific best practices, making this tool especially relevant to teams already invested in the AWS ecosystem.

CodeWhisperer’s core feature set centers on context-aware code suggestions that appear inline in editors. It integrates with Visual Studio Code, JetBrains IDEs (IntelliJ family), and Visual Studio, offering completions as you type and whole-function proposals when you comment intent. The tool recognizes many common languages—Java, Python, JavaScript/TypeScript, C#, Go and more—and can surface example usages for AWS SDK calls. It also includes a security-detection capability that highlights potential secrets or risky API usage and suggests remediation. Additional features include a recommendation history, the ability to request alternate suggestions, and IDE-accessible settings to restrict suggestion sources and telemetry collection.

On pricing, Amazon provides a free tier that delivers basic CodeWhisperer usage at no charge for personal or discovery use, while paid tiers unlock higher request quotas and enterprise controls. AWS offers an Individual/Pro paid plan (monthly fee) for heavier individual users and a Business/Enterprise option with custom pricing that adds IAM-based controls, corporate licensing, and broader telemetry & audit features. The free tier covers limited monthly recommendations and basic scanning; paid plans increase recommendation quotas, add priority support, and enable centralized admin controls and VPC-compatible deployment patterns for strict data governance.

Developers and teams use CodeWhisperer in practical workflows like speeding API integrations and reducing boilerplate in new microservices. Example users include a backend engineer implementing AWS Lambda handlers using generated boilerplate and SDK calls, and a DevOps engineer auto-generating infrastructure-as-code snippets with correct IAM scopes. It also assists SREs writing monitoring hooks and QA engineers creating unit-test skeletons. For organizations focused on non-AWS stacks or who prioritize the broadest language-model capability, competitors such as GitHub Copilot may be stronger in non-cloud-specific contexts, while CodeWhisperer excels for AWS-centric development.

What makes Amazon CodeWhisperer different

Three capabilities that set Amazon CodeWhisperer apart from its nearest competitors.

  • AWS API-aware suggestions that generate precise SDK method calls and recommend least-privilege IAM policies inline during code completions.
  • Enterprise data controls let organizations disable contribution for model training and enforce centralized retention and access policies.
  • Native integration with AWS IDEs and the AWS Toolkit (VS Code, JetBrains, Cloud9) plus code scanning for AWS credential leaks.

Is Amazon CodeWhisperer right for you?

✅ Best for
  • Backend engineers who need accurate AWS SDK calls and inline IAM suggestions
  • Cloud developers who need context-aware completions for Lambda, ECS, and API code
  • DevOps teams who need quick cloud automation snippets and infrastructure scripting
  • Security-conscious organizations who need code suggestions that flag credential and privilege risks
❌ Skip it if
  • Skip if you require an on-prem, air-gapped model with no cloud connectivity
  • Skip if you primarily need non-AWS cloud SDK guidance (Azure/GCP-focused development)

✅ Pros

  • Integrates with AWS Toolkits and suggests AWS SDK calls and IAM-relevant code
  • Includes security detection that highlights potential secrets and risky API use
  • Enterprise options include IAM-based access, audit logs, and administrative controls

❌ Cons

  • AWS-centrism means non-AWS projects may get less relevant suggestions than competitor models
  • Recommendation accuracy varies by language and complex design-level tasks still require human review

Amazon CodeWhisperer Pricing Plans

Current tiers and what you get at each price point. Verified against the vendor's pricing page.

Plan Price What you get Best for
Free Free Limited completions per month; no centralized enterprise governance or commercial SLAs Individual developers evaluating CodeWhisperer at no cost
Professional $19 per user/month Higher recommendation throughput; personal usage only; no centralized admin controls Individual professionals needing higher usage and private suggestions
Enterprise Custom Organization-wide governance, SSO, audit logs, configurable data retention and SLA options Large organizations needing centralized controls and compliance features

Best Use Cases

  • Backend engineer using it to implement REST endpoints 30–50% faster
  • DevOps engineer using it to generate IaC snippets and correct IAM scopes
  • QA engineer using it to scaffold unit tests and test fixtures quickly

Integrations

Visual Studio Code (AWS Toolkit) JetBrains IDEs (IntelliJ, PyCharm via AWS Toolkit) Visual Studio (Windows) via AWS Toolkit

How to Use Amazon CodeWhisperer

  1. 1
    Open the CodeWhisperer console
    Visit the AWS CodeWhisperer page in the AWS Console and click the Getting started or Enable CodeWhisperer button to review plan options and enable recommendations for your account. Success looks like CodeWhisperer marked Enabled on your account page.
  2. 2
    Install the AWS Toolkit
    Install the AWS Toolkit extension for Visual Studio Code or the JetBrains marketplace plugin. Search for 'AWS Toolkit' in the IDE Extensions/Plugins pane and click Install. You’ll see AWS icons and a CodeWhisperer section after installation.
  3. 3
    Sign in with your AWS credentials
    Use the AWS: Connect to AWS command (VS Code) or the AWS Tool window in JetBrains to authenticate with an IAM user or SSO. Verification looks like your AWS account name appearing in the Toolkit status bar.
  4. 4
    Request and accept a suggestion
    Type a descriptive comment or function signature, then trigger completions using the editor’s suggestion key (Ctrl+Space) or accept inline suggestions when they appear. Success is a generated code snippet populating your editor with an AWS-aware recommendation.

Ready-to-Use Prompts for Amazon CodeWhisperer

Copy these into Amazon CodeWhisperer as-is. Each targets a different high-value workflow.

Implement S3 List REST Endpoint
Simple API listing S3 objects
You are a backend engineer assistant. Task: produce a complete Node.js Express route handler that lists objects in a specific S3 prefix using AWS SDK v3 (@aws-sdk/client-s3). Constraints: use async/await, handle pagination (MaxKeys), accept query params bucket and prefix, return JSON with {objects:[{Key,Size,LastModified}]}, include minimal IAM policy snippet granting least privilege for GetObject/ListBucket on that bucket. Output format: 1) full Express route code (copy-paste ready), 2) short IAM policy JSON, 3) one-line usage example (curl). Example: show how handler reads bucket from req.query.
Expected output: A copy-pasteable Express route handler, a JSON IAM policy snippet, and a one-line curl usage example.
Pro tip: Ask CodeWhisperer to prefer AWS SDK v3 modular imports to reduce bundle size when using Lambda layers or serverless packaging.
Scaffold Lambda Pytest Unit Tests
Unit tests for Python Lambda handler
You are a QA-focused code assistant. Task: generate a pytest test file that tests an AWS Lambda Python handler which reads from S3 via boto3 and writes to DynamoDB. Constraints: use pytest and pytest-mock (or moto) mocks, include tests for success, S3 missing object (ClientError), and DynamoDB conditional failure; avoid real AWS calls. Output format: a test file named test_handler.py with imports, three test functions, sample fixture(s), and example mock return values. Example: show how to patch boto3.client('s3').get_object to return a BytesIO body.
Expected output: A single pytest test file with three complete test functions and fixtures ready to run locally with pytest-mock or moto.
Pro tip: Mock boto3 at the module import point (where your handler imports boto3.client) to avoid accidental network calls.
Generate Least-Privilege IAM Policy
Create minimal IAM policy for Lambda
You are an IAM policy generator. Task: produce a least-privilege JSON IAM policy for a Lambda that reads specific items from a DynamoDB table and writes processed files to an S3 bucket path. Constraints: parameterize ARNs with placeholders (e.g., {{DDB_TABLE_ARN}} , {{S3_BUCKET_ARN}}), limit DynamoDB actions to Query and GetItem with condition on table name, limit S3 to PutObject on a specific prefix, avoid wildcard resource for DynamoDB attributes. Output format: 1) clean JSON policy document, 2) a 3-line explanation of each statement, 3) one-line example on how to attach the policy to a Lambda execution role using AWS CLI.
Expected output: A JSON IAM policy with parameterized ARNs, a short explanation for each statement, and a single CLI attach-example line.
Pro tip: Include explicit resource ARNs and consider adding aws:RequestedRegion and aws:SourceVpc conditions for extra protection in production.
CloudFormation Fargate Service Snippet
ECS Fargate service with autoscaling
You are a DevOps CloudFormation author. Task: produce a YAML AWS::Serverless or AWS::CloudFormation snippet that defines an ECS Fargate service behind an ALB with target group, a scalable target (ApplicationAutoScaling) and a simple target tracking policy based on CPUUtilization. Constraints: accept Parameters for ClusterName, VpcId, SubnetIds, ContainerImage, DesiredCount, and SecurityGroup; retrieve container secrets from SSM Parameter Store; keep resource names generic. Output format: full YAML snippet for resources and a short Parameters section, plus a one-line deploy command using AWS CLI or SAM.
Expected output: A complete CloudFormation YAML snippet with resources, parameters, and a one-line deploy command.
Pro tip: Reference SSM parameters by ARN and include DependsOn for the target group to avoid race conditions during stack creation.
Serverless Migration Plan and Code
Migrate monolith endpoint to Lambda+API Gateway
You are a senior cloud architect. Task: produce a step-by-step migration plan (5–8 steps) to move a legacy monolithic REST endpoint (Node/Express) into AWS Lambda + API Gateway, including refactor checkpoints, data-access abstraction, and CI/CD changes. After the plan, provide: 1) a compact example Lambda handler (Node.js) converted from an Express handler, 2) a minimal SAM template snippet to deploy the function and API Gateway, and 3) a rollback/test checklist. Constraints: prioritize minimal downtime, include database connection best-practices (connection pooling or RDS Proxy), and include environment variable handling. Output format: numbered plan, code block for handler, SAM YAML, and a 5-item testing checklist.
Expected output: A numbered 5–8 step migration plan, a sample Node.js Lambda handler, SAM YAML snippet, and a 5-item rollback/test checklist.
Pro tip: When migrating, extract data access into a separate module first so both monolith and Lambda can share it during a gradual cutover.
Audit AWS SDK Risks and Fixes
Scan code for AWS SDK anti-patterns and fixes
You are a security-savvy code reviewer. Task: given codebase snippets (or scan results), identify up to 8 high-priority AWS SDK anti-patterns (hardcoded credentials, overly-broad IAM calls, synchronous blocking calls in Lambdas, missing retries/timeouts, logging sensitive data). For each finding provide: 1) concise description, 2) severity (High/Med/Low), 3) concrete remediation with a code patch (diff-style) or replacement snippet, and 4) one IAM or runtime configuration change to mitigate. Few-shot examples: show a vulnerable example (hardcoded key) and the fixed example (use environment or IAM role). Output format: numbered findings with labeled fields and diffs.
Expected output: Up to 8 numbered findings each with severity, remediation including a diff-style code patch or replacement snippet, and a configuration mitigation.
Pro tip: Ask the tool to include exact CLI commands or CloudFormation snippets to rotate any detected long-lived credentials automatically.

Amazon CodeWhisperer vs Alternatives

Bottom line

Choose Amazon CodeWhisperer over GitHub Copilot if you prioritize AWS SDK accuracy and enterprise data governance for cloud-native development workflows.

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Frequently Asked Questions

How much does Amazon CodeWhisperer cost?+
CodeWhisperer offers free access plus paid tiers. The service provides a no-cost tier for light personal use, and AWS sells Individual/Pro monthly plans and Enterprise contracts with custom pricing. Paid tiers increase monthly recommendation quotas, add priority support, and enable centralized admin and audit controls. Check the AWS CodeWhisperer pricing page for the latest regional prices and enterprise licensing details.
Is there a free version of Amazon CodeWhisperer?+
Yes — CodeWhisperer has a free tier for basic use. The free tier includes limited monthly code recommendations and core security scans suitable for individual exploration and small projects. If you exceed the free quota or need admin controls, auditing, and higher throughput you’ll need a paid Individual or Enterprise plan. Review usage quotas in the AWS Console to monitor free-tier consumption.
How does Amazon CodeWhisperer compare to GitHub Copilot?+
CodeWhisperer is AWS-focused while Copilot is broader. CodeWhisperer surfaces AWS SDK calls, IAM hints, and integrates tightly with AWS Toolkits and IAM. GitHub Copilot typically provides broader language-model coverage and training across GitHub-hosted code. Choose CodeWhisperer for AWS-centric development and enterprise privacy; choose Copilot for wide language and ecosystem coverage.
What is Amazon CodeWhisperer best used for?+
Best for AWS-centric code completion and API usage guidance. CodeWhisperer excels at generating boilerplate, wiring AWS SDK calls, and suggesting IAM-friendly code patterns inside your IDE. It’s particularly helpful for backend developers implementing Lambda/APIs, DevOps writing IaC snippets, and teams that need IAM-based access and audit controls around AI-assisted coding.
How do I get started with Amazon CodeWhisperer?+
Enable CodeWhisperer in the AWS Console and install the AWS Toolkit in your IDE. After enabling the service, authenticate via the AWS Toolkit (SSO or IAM), open an AWS project file, then type a comment or function signature and trigger editor completions to see your first generated suggestion.

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