Category: AWS Lambda

A single cold start can push your Java Lambda function’s response time from milliseconds to seconds, enough to violate your p99 SLA, timeout a downstream service, and page your on-call. The Java Virtual Machine (JVM) performs best in long-running processes. Its Just-In-Time (JIT) compiler progressively optimizes code over thousands of invocations. Standard serverless execution environments […]

We recently announced the launch of AWS Lambda MicroVMs, a new serverless compute primitive that provides VM-level isolation, near-instant startup performance, and state retention. You can now give each user or job their own execution environment to securely run just-in-time code – either user or AI generated – without managing virtualization infrastructure or choosing between […]

Development teams building serverless applications with AI coding agents face the question of how to let those agents generate and execute code without losing control over governance. Agent-generated code needs a secure environment to execute, isolated from production systems and the developer’s local environment. Addressing this requires three things working together: a secure execution sandbox, […]

Agentic AI workflows coordinate multiple agents that reason, plan, and act across multi-step processes. Each step is expensive, non-deterministic, and unpredictable in latency. Human review gates can pause execution for days. Transient failures are expected, and restarting a half-finished workflow wastes time and money. Duplicate actions, like charging a payment twice or sending the same […]

Contact centers handle millions of voice interactions monthly, but transforming raw call recordings into actionable insights remains a manual and fragile process. With voice analytics workflows, you can decrease the average handle time of a voice call from minutes to seconds and increase the efficiency and productivity of your support agents. Today, these workflows often […]

Learn how Amazon S3 Files simplifies Lambda functions by eliminating transfer code and /tmp constraints. See three modernization patterns with code examples for image processing, ETL pipelines, and multi-agent AI workloads. AWS Lambda functions that interact with Amazon Simple Storage Service (Amazon S3) typically follow a familiar pattern: download an object to /tmp, process it […]

When you create an AWS Lambda function, you choose the runtime that Lambda will use to run your code. This includes the base language version and supporting libraries. Lambda runtimes follow a published deprecation schedule. This means that you must periodically upgrade your function’s runtime. Running on a deprecated runtime means potential security exposure, loss […]

Building event-driven multi-tenant SaaS applications typically requires compute isolation between tenants to prevent data leakage, maintain security boundaries, and ensure compliance. Traditionally, you had to choose between two approaches: sharing execution environments across tenants (risking cross-tenant contamination of in-memory state) or managing separate Lambda functions per tenant (which introduces operational overhead, increasing costs, and complicating […]

Multi-Region Event-Driven Failover Architecture with Amazon EventBridge and Route 53 Event-driven architectures enable applications to respond to events in real-time, providing scalability and loose coupling between components. However, ensuring high availability across multiple AWS regions requires careful design of failover mechanisms. This post demonstrates how to build a resilient multi-region event-driven architecture using Amazon EventBridge, […]

Stay current with the latest serverless innovations that can improve your applications. In this 32nd quarterly recap, discover the most impactful AWS serverless launches, features, and resources from Q1 2026 that you might have missed. In case you missed our last ICYMI, check out what happened in Q4 2025. 2026 Q1 calendar Serverless with Mama […]