editortamvan / September 7, 2018
5 Takeaways That I Learned About Computer
A General Overview of Serverless Monitoring Tools
Serverless computing, like that found in platforms such as AWS Lambda, actually represent a new paradigm in computing. 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. 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.
There are many out there who may be wondering why this is such an important point? When you use a serverless platform, you will be free to execute your code without having to think about the computing power of your underlying servers. Serverless computing platforms like Lambda always scale the available computing power to ensure that you have enough power to always execute your code.
In AWS Lambda, all of these monitoring functions are actually hidden from you and handled automatically by the platform. The thing that you control in this platform is the application code, which you upload to Lambda as a function, and which is implemented and executed automatically in AWS as code. An application called CloudWatch is the default program for monitoring Lambda for errors in running code. AWS also provides monitoring on Lambda for application performance 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. When you are monitoring in Lambda, it can be quite a bit different from monitoring in more traditional environments. 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.
If you would like to find out more about serverless monitoring tools in Lambda and AWS, the best thing you can do is is take a moment to visit the website of a software developer who offers these tools online. To begin, simply search the Internet for AWS calculators, Lambda functions, and python error handling.