DVA-C03 (the current version of the Developer Associate exam, replacing DVA-C02 after 30 November 2026) is about building, securing, deploying and debugging applications on AWS from the developer's side: SDK calls, Lambda, DynamoDB, messaging, tokens and keys, CI/CD, observability and using AI tools and managed AI services. It does not ask you to design architectures or administer IAM users and servers. This outline lists what each domain expects, in plain terms. Tick topics off as you cover them. Your ticks are saved in this browser.
This outline follows the official DVA-C02 exam guide . Check it for the exact wording.
Development with AWS services 32% Writing application code against AWS services (including AI-assisted development and managed AI services), writing Lambda functions, and choosing and using data stores. The largest domain (30%).
Application architecture patterns Fault-tolerant code SDKs, CLI and APIs API Gateway REST, HTTP and WebSocket APIs, and when to pick each Lambda proxy, custom, HTTP, AWS service and mock integrations Request and response transformation with mapping templates, request validation, overriding status codes Throttling, usage plans, caching, CORS and common error codes (400, 403, 429, 502, 504) AppSync for GraphQL Serialization and event-driven code Messaging and orchestration SQS standard versus FIFO, visibility timeout, long polling, delay, batching, message size SNS topics, fanout to SQS, FIFO topics and delivery retries EventBridge buses, rules, schedules and pipes Step Functions Standard versus Express, Retry and Catch, service integration patterns Data streaming Lambda configuration and behaviour Memory, timeout, runtime, handler, ephemeral storage, environment variables, layers, extensions Execution environment lifecycle, cold starts, provisioned concurrency and SnapStart Reserved concurrency, account concurrency and throttling Versions, aliases and weighted traffic Function URLs and package size limits Lambda events and errors DynamoDB Partition and sort keys, high-cardinality keys, hot partitions CRUD, Query versus Scan, filter and projection expressions, batch and transaction calls Local and global secondary indexes Eventually consistent versus strongly consistent reads and capacity unit calculations Conditional writes, atomic counters, TTL, Streams, global tables, DAX Serializing and deserializing items Other data stores and storage Caching AI-assisted development and managed AI services
Security 26% Authentication and authorization, encryption and sensitive data, and the security risks of using AI services (26%).
Authorization with IAM Roles, STS and programmatic access Federation and tokens Presigned URLs, signed URLs and MFA Amazon Cognito Encryption and KMS Certificates and keys Sensitive data in code Securing AI services
Deployment 24% Packaging artifacts, testing and automating tests (including with AI tools), and shipping code with AWS CI/CD services (22%, called Testing and Deployment in DVA-C03).
Packaging artifacts Container images and orchestration Configuration data Version control Testing in development environments Automated and AI-assisted testing Infrastructure as code Environment management CI/CD services Deployment strategies and rollback
Troubleshooting and optimization 18% Finding the cause of problems (with AI help), applying logging, monitoring and health-check practices, and tuning applications (22%).
Logging, monitoring and observability CloudWatch metrics and alarms CloudWatch Logs Distributed tracing with X-Ray Root cause analysis Health checks and workload health AI tools for troubleshooting and optimization Optimization Concurrency, pooling and bottlenecks