AWS Lambda supports nearly any programming language by enabling developers to run serverless functions with either supported or custom runtimes. Once a runtime is deprecated, however, AWS will set dates for when you can no longer create or update functions using that runtime. You will then need to decide what course of action to take to ensure your Lambda functions continue running as expected.

Azure, Microsoft’s cloud platform, has become an essential part of modern businesses, offering a vast array of services and resources. However, effective cost management in Azure is crucial to avoid unexpected expenses and optimize spending. While Azure provides its native tools for cost management, several third-party solutions offer advanced features and capabilities to help you make the most of your Azure resources. This blog will explore the top 24 Azure cost management tools.

As of 2024, the global serverless computing market is projected to reach a value of USD 21.9 billion, with expectations to grow to USD 44.7 billion by 2029. Around 70% of organizations using AWS have adopted at least one serverless solution. The adoption rates for Google Cloud and Azure are 60% and 49%, respectively. These numbers affirm that serverless is here to stay, and the demand for platforms to create and run applications is higher than ever. AWS Lambda is the most popular serverless platform.

Serverless platforms make it incredibly easy to deploy applications. You can take raw code, push it up to a service like AWS Lambda, and have a running application in just a few seconds. The serverless platform provider assumes responsibility for hosting and operating the platform, freeing you up to focus on your application. Naturally, this raises a question: if something goes wrong, who’s responsible?

Serverless is an incredible paradigm, but performance tuning sometimes feels like a black box. You have no control over the infrastructure, but that doesn’t mean you can’t optimize. In this post, let’s look at five ways to take serverless performance to the next level.

Building applications using serverless technology on AWS—like AWS Lambda and Amazon API Gateway—can be incredibly powerful. You get to scale effortlessly and focus on writing code without worrying about managing servers. But as your application grows and spreads across hundreds or even thousands of cloud resources, keeping track of errors and fixing issues quickly becomes a big challenge.

AWS enables customers to retry or redrive Step Functions executions to continue any failed executions of Standard Workflows from their points of failure while maintaining all inputs. For example, if you find broken downstream logic in your code or experience unexpected errors upon execution, you can remediate those errors by fully re-running an execution or use redrive to continue this execution.