An ever increasing number of developers and architects are using AWS Lambda to deploy serverless functions to control costs and reduce the burden of server management. Due to the unpredictable nature of end-user demand in today’s digital-first world, Lambda functions can help resolve unplanned scaling issues.

Serverless architectures such as AWS Lambda have created new challenges in debugging code. Without a solid logging framework in place, you could waste hours, or even days, tracking down simple defects in your functions. A strategic logging framework can be a powerful way to track down and resolve bugs. Let’s walk through how to get the most out of logging Lambda functions.

This is the first of a two-part blog series. In this post we’ll use Stackery to configure and deploy a serverless data processing architecture that utilizes AWS Step Functions to coordinate multiple steps within a workflow. In the next post we’ll expand this architecture with additional workflow logic to highlight techniques for increasing resiliency and reliability.

The way we build software products changes all the time. Serverless architecture opens up new opportunities to create awesome products faster. Not only that, serverless applications are more scalable, secure and maintainable – all with much less code. Serverless is the future of development and you should get ready for it. But what does it mean to be a serverless developer? What do you need to understand before jumping into the serverless pool?

We’re very pleased to announce the official launch of our new Java tracer for AWS Lambda. This release extends Lumigo’s real-time monitoring and observability tools to all JVM-based AWS Lambda applications, with support for Apache Groovy, Scala and Kotlin among others.

If you’ve built a serverless application or two, you’re probably familiar with the benefits of serverless architecture. You take advantage of already built, managed cloud services to handle standard application requirements like authentication, storage, compute, API gateways, and a long list of other infrastructure needs. You can spin up these resources in a matter of minutes and add your own specific business logic (usually as AWS Lambda function code).

Deploying a basic Serverless application has been made easy with the abundance of frameworks out there. If you’re part of a small team or working on a relatively simple project, setting up a basic serverless CICD process is also pretty straightforward, since there is plenty of information on the subject. But when a Serverless application grows it can get very complex very fast.

With Serverless, it’s not the technology that’s hard, it’s understanding the language of a new culture and operational model. Serverless architecture has coined some new terms and, more confusingly, re-used a few older terms with new meanings. This glossary will clarify some of them.

One of the basic ingredients of any software is that before you deliver it to the end user you want to make sure that it works properly. The question is how we need to adapt our approach to testing to take account of the cloud-based, highly distributed nature of serverless architecture.

Like many startups, Stackery is a small team. For this reason, employees often need to go beyond their official job title to ensure everything gets done. As the Stackery product matures and gains more exposure, we’ve seen an increase in customer support inquiries and decided to further refine our customer support process through the creation of a customer support rotation that rotates amongst the software engineers on a weekly basis.