A General Overview of Serverless Monitoring Tools
Serverless computing represents a new paradigm and is best represent by emergent platforms like AWS Lambda. In serverless computing, the host server is virtualized, meaning that the host computing hardware is removed from the computing situation entirely. 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. These changes are particularly important in AWS Lambda, but also apply in any other serverless computing environment.
Traditional computing environments force you to monitor the performance of the network as well as the servers. Whenever you are working in a new, serverless environment like AWS Lambda, these metrics will no longer be of importance to you. 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.
At first, you may wonder why this would be so important for you? This kind of serverless computing system allows you to implement and execute your application code without the problem of regulating and monitoring your server’s computing power. Serverless computing platforms like Lambda always scale the available computing power to ensure that you have enough power to always execute your code.
In the Lambda platform, all of these consideration are hidden from you and handled automatically. 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. AWS primarily uses an application called CloudWatch to automatically monitor the performance of Lambda in the error free implementing of code and running of applications. If you want to further monitor application performance on Lambda, you can do so by using an application called X-Ray. Valuable insights for troubleshooting AWS Lambda errors and for correcting errors in code are stored in the Cloudwatch logs which can be consulted whenever you need to address errors.
There is a lot to get used to when you begin working in an environment like Lambda. Monitoring in Lambda is much different than monitoring in traditional applications. This means that you should take advantage of the AWS built in monitoring services, such as CloudWatch, X-Ray and a variety of customized metrics.
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.