June 2026 Summaries

LocalStack for AWS 2026.06.0 introduces several key features and improvements, including S3 Replication emulation, enhanced Service Control Policy enforcement within the IAM policy engine, and a new SQLite-backed v2 implementation of CloudWatch Logs. This release supports Bottlerocket self-managed nodes for EKS, Lambda runtime init error reporting, and Kubernetes pod configuration controls. It also expands AWS Replicator coverage and introduces initial support for the Aurora DSQL control plane. Enhancements have been made across various AWS services such as Lambda, SQS, ECS, CloudFormation, S3, and more, aiming to close AWS parity gaps and improve compatibility with Terraform and CloudFormation. The release also marks the removal of legacy CloudFormation v1 and Glue job execution paths, and encourages users to upgrade to benefit from the latest features and provide feedback for future updates.

AWS Glue and Snowflake can be effectively combined for ETL workloads, with Glue managing orchestration and Spark execution, and Snowflake serving as the data warehouse. The typical process involves deploying Glue jobs to AWS and debugging them through CloudWatch while incurring Snowflake compute costs. However, using LocalStack's Snowflake emulator allows for running Glue jobs locally by providing a Snowflake-compatible endpoint, eliminating the need for cloud infrastructure and credentials. The tutorial explained how to build a Glue ETL pipeline that reads from a Snowflake table using the Snowflake Spark connector, with AWS resources provisioned via Terraform and the Snowflake table seeded with an init script. The setup includes AWS Glue for Spark-based ETL jobs, the Snowflake Spark connector for JDBC-based data reading, and LocalStack's emulator for a local Snowflake endpoint. By running tasks locally, developers can iterate on Glue-Snowflake jobs without waiting for cloud infrastructure, test schema changes, and validate connection parameters, thus saving time and cost.

AWS CDK's integration testing framework, often overlooked by teams, includes the integ-runner CLI and @aws-cdk/integ-tests-alpha construct library, which allow for testing real infrastructure by deploying stacks, running assertions, and tearing down resources. However, deploying to real AWS accounts incurs costs and delays feedback. The framework can be configured to use LocalStack, an AWS service emulator, enabling tests to run locally without AWS credentials or expenses. An example application, a friend request microservice leveraging AWS CDK services such as Lambda, API Gateway, DynamoDB Streams, and SQS, demonstrates the integration tests. These tests differ from unit tests as they deploy infrastructure and verify end-to-end behavior. By setting specific environment variables, the integ-runner can redirect to LocalStack, allowing developers to test complex event-driven pipelines with faster feedback. This setup involves deploying stacks to LocalStack, executing assertions on emulated services, and inspecting resources post-test. The framework ensures comprehensive testing of asynchronous state changes that unit tests may miss, providing an efficient and cost-effective solution for AWS CDK application testing.

AI agents can significantly enhance development workflows by automating tasks, but they necessitate careful validation to avoid costly mistakes, particularly when interacting with cloud services. LocalStack provides a useful local testing environment for these agents, allowing developers to verify code without incurring cloud expenses. A dedicated entry point for AI agents has been created at blog.localstack.cloud/ai, which offers a step-by-step setup flow in a plain-text Markdown format, designed for agent comprehension. This process includes installing LocalStack's CLI tool, creating an account, and configuring the MCP server. Once setup is complete, agents gain access to a comprehensive suite of LocalStack tools, enabling them to manage container lifecycles, deploy infrastructure, analyze logs, and more. The document also highlights the importance of dedicated workflows and skills available on GitHub, which further streamline processes like state management and IAM policy analysis. This setup empowers agents to operate LocalStack efficiently, providing developers with a robust framework for testing and deploying AWS applications locally.

AWS Lambda extensions enhance the Lambda execution environment by allowing users to run additional code alongside the function handler, providing functionalities such as telemetry capture, security policy enforcement, and integration with observability tools. This tutorial demonstrates how to build an audit-log extension using LocalStack, a tool that shortens the development cycle by quickly shutting down the execution environment and allowing immediate inspection of resources like S3 and CloudWatch Logs. The tutorial outlines the creation of an external extension that registers for INVOKE and SHUTDOWN events through the Extensions API, records metadata for each Lambda invocation, and writes an audit report to S3 upon shutdown. The extension is packaged as a Lambda layer, which is deployed to LocalStack, enabling rapid testing and iteration. Additionally, the tutorial highlights the integration of AWS Lambda function with the extension and offers step-by-step guidance on deploying, invoking, and observing the extension's operations within a simulated AWS environment, emphasizing the efficiency and flexibility of using LocalStack for local development.

CloudBurn is an open-source AWS cost policy engine designed to provide developers greater visibility into cloud deployment costs by performing static analysis on infrastructure-as-code (IaC) files and live AWS resources to identify cost-related issues. It operates in two modes: "scan," which evaluates Terraform and CloudFormation files without requiring AWS credentials, and "discover," which scans live AWS resources to identify waste in already deployed infrastructure. CloudBurn integrates into CI pipelines to prevent costly infrastructure from being merged without acknowledgment and can be used locally with LocalStack to test IaC changes in a simulated AWS environment. The tool features a library of 80 rules across 22 AWS services, each highlighting specific cost anti-patterns and providing actionable insights. Developers can incorporate CloudBurn scans into their workflows to catch potential cost issues before code reaches the pipeline, and a bash script can be used to enforce checks via pre-commit hooks, identifying new cost violations introduced by IaC changes. While CloudBurn and LocalStack offer valuable insights, effective cloud cost management still requires a holistic approach beyond just technical tools.