A Closer Look at Serverless Monitoring Tools
Serverless computing, like that found in platforms such as AWS Lambda, actually represent a new paradigm in computing. Through a technical process involving the virtualizing of hardware servers, serverless computing systems remove the host server from the computing equation. Because of the major differences between traditional and serverless computing, the user is forced to rethink several important pieces of the puzzle, including their use of monitoring functions. Such changes are particularly applicable to Lambda functions, but may also apply to just about any serverless computing environment.
When you are working in a traditional computing environment, there are numerous performance metrics to monitor, particularly the performance of the server and the network. When you work in a serverless platform, like Lambda, these traditional metrics no longer matter. It is the application vendor who will manage the underlying infrastructure like the server and network performance, and you will be left to manage your application code.
You may be wondering what advantage this gives you? Serverless computing systems allow you to execute and monitor your code without having to concentrate on your computing power and servers. To ensure that you always have enough computing power to execute your code, AWS Lambda always scales the available computing capacity to your needs.
In AWS Lambda, all of these monitoring functions are actually hidden from you and handled automatically by the platform. As user, the thing you control in this system is the application code, which you begin by uploading into Lambda as a function and is then implemented in AWS as code. The primary application used by AWS to monitor the performance of Lambda is called CloudWatch, which monitors Lambda to ensure it is running error free. In Lambda, AWS also allows you to monitor application performance by using an application called X-Ray. Whenever it is necessary to address errors in Lambda, you can consult the CloudWatch logs, in which all applicable error information is stored and from which you can derive valuable insights for correcting problems and errors in code.
As you begin to work in a serverless environment like Lambda, there will be a lot to get used to. Monitoring in Lambda is much different than monitoring in traditional applications. Therefore, you will need to leverage the already built in monitoring features in AWS like X-Ray, CloudWatch, and custom metrics that are available to you.
Those who would like to find out more about all of the serverless monitoring solutions available for Lambda and AWS systems should begin by visiting the website of a software development firm that offers serverless monitoring systems. To begin, simply search the Internet for AWS calculators, Lambda functions, and python error handling.