There is a growing ecosystem of vendors that are helping AWS customers gain better observability into their serverless applications. All of them have been facing the same struggle: how to collect telemetry data about AWS Lambda functions in a way that’s both performant and cost-efficient. To address this need, Amazon is announcing today the release of AWS Lambda Extensions.

We are excited to announce a new integration to help developers add partner solutions to their serverless applications. AWS recently released Lambda Extensions to allow Lambda to augment the Function invocation lifecycle. Extensions from AWS, AWS Lambda Ready partners, and open source projects are useful for a wide range of use cases. For example, Extensions simplify a development workflow by automatically instrumenting Lambda functions or deploying operational tools without needing code changes.

We are excited to announce the preview of the Splunk extension for AWS Lambda, a new way to integrate monitoring and observability in Lambda environments. Splunk is already the pioneer in providing real-time observability into serverless environments. With the Splunk extension, capturing and ingesting observability data become seamless without the need to instrument function code.

Welcome to the final installment of our Complete AWS Lambda Handbook series! Given Lambda is often the central point for many serverless applications, we wanted to make sure we didn’t skip or breeze past any part. In this episode, we’re looking at some limitations and difficulties using AWS Lambda and how to overcome them, and the importance of monitoring for performance and failure remediation.

Software development has greatly evolved over the years. Serverless is an emerging software architecture that could resolve issues when it comes to developing software solutions. As software developers, you’re tasked with server setup, installing the software, operating systems requirements, server management and maintenance, designing an application with high fault tolerance and availability, as well as managing load balance and more.

Troubleshooting production issues in Lambda environments is often challenging. CloudWatch requires developers to comb through logs, search for relevant terms that they may not always know of and has hard-to-consume stack traces. For obvious reasons, we recommend using Sentry to instrument your Lambda Functions code in order to report error stack traces and associated debugging context. Here’s a walk through on how to instrument a Node function.

AWS DynamoDB changed the database game in Serverless and continues to do so, as its design repeatedly proves its huge value. This guide takes you through everything there is to know about DynamoDB so you can rest assured you’re using the service in its best way and reaping all of the benefits.

Deploying a stack into AWS is at the core of what Stackery helps you do. So much so that Stackery users deployed over 10,000 times last month! For the most part, this has been a manually executed process in our Web UI or command-line client. As teams grow and take on more work, fast and consistent deployments are key to scaling effectively. That’s why we’ve been working this year on continuous integration and deployment (CI/CD) features, tailor-built for serverless applications.

Now that you’ve chosen to go the serverless route, which vendor option should you go for? That’s one of the major questions that anybody asks themselves when they make the switch. Should you choose Amazon Web Services (AWS), which is a mature service that will serve you well, or should you go with e Google’s younger Firebase? Before the comparison of AWS vs Firebase, we should understand what serverless really means. This one server can be responsible for several different functions.