AWS Automation Case Study

What is Automatic Remediation in AWS? -- Auto-remediation in AWS refers to the process of automatically fixing problems that occur within an environment, without the need for human intervention. Auto-remediation can help reduce downtime and ensure that critical systems and applications are always available. In AWS, we can use services like AWS CloudWatch and AWS Lambda to set up auto-remediation processes that can detect and fix issues in real-time, enabling you to maintain optimal performance and availability for our critical workloads. -- Amazon CloudWatch is a monitoring service provided by Amazon Web Services (AWS) that enables us to monitor our AWS resources, applications, and services in real-time. CloudWatch provides metrics, logs, and alarms to monitor and troubleshoot your AWS environment. We can use CloudWatch to collect and track metrics, collect and monitor log files, and set alarms. -- With CloudWatch, we can monitor and visualize metrics such as CPU usage, network traffic

What is AWS Lambda? -- AWS Lambda is a serverless computing service that allows developers to run code without having to worry about server management. With AWS Lambda, developers can build and deploy applications quickly and easily, while only paying for the compute time that they use. We can say while exploring AWS Lambda functions it also provides an example of how to create a Python-based Lambda function also. Functionalities of AWS Lambda -- Lambda functions are small pieces of code that can be triggered by events such as changes in data or user activity. The functions are stored in the cloud and run on demand, which means that developers don't have to worry about provisioning or managing servers. AWS Lambda supports several programming languages, including Python, Java etc. Case study : To get description  of an EC2 instance ( example Configuration ) -- Here's an example Python AWS Lambda function that retrieves the description of an EC2 instance using the Boto3 library: