HOW AWS LAMBDA WORKS INTERNALLY TAMIL | What is AWS Lambda Explain ? | InterviewDOT

Click here - https://www.youtube.com/channel/UCd0U_xlQxdZynq09knDszXA?sub_confirmation=1 to get notifications. How AWS lambda works internally ?

AWS Lambda is a compute service that lets you run code without provisioning or managing servers.
AWS Lambda executes your code only when needed and scales automatically.
You pay only for the compute time you consume - there is no charge when your code is not running.
With AWS Lambda, you can run code for virtually any type of application or backend service - all with zero administration.
AWS Lambda supports currently Node.js, Java, C#, Go and Python

Benefits :

1. Focus on business logic.
2. Scalable application with less effort.
3. Reduced cost of execution.
4. Multiple languages support.

Cons :

1. Complex call pattern.
2. Less control over the environment.
3. Design decisions are challenging.
SERVERLESS FRAMEWORK

AWS Lambda Execution Context
When AWS Lambda executes your Lambda function, it provisions and manages the resources needed to run your Lambda function. When you create a Lambda function, you specify configuration information, such as the amount of memory and maximum execution time that you want to allow for your Lambda function. When a Lambda function is invoked, AWS Lambda launches an execution context based on the configuration settings you provide. The execution context is a temporary runtime environment that initializes any external dependencies of your Lambda function code, such as database connections or HTTP endpoints. This affords subsequent invocations better performance because there is no need to "cold-start" or initialize those external dependencies, as explained below.

It takes time to set up an execution context and do the necessary "bootstrapping", which adds some latency each time the Lambda function is invoked. You typically see this latency when a Lambda function is invoked for the first time or after it has been updated because AWS Lambda tries to reuse the execution context for subsequent invocations of the Lambda function.

After a Lambda function is executed, AWS Lambda maintains the execution context for some time in anticipation of another Lambda function invocation. In effect, the service freezes the execution context after a Lambda function completes, and thaws the context for reuse, if AWS Lambda chooses to reuse the context when the Lambda function is invoked again. This execution context reuse approach has the following implications:

Objects declared outside of the function's handler method remain initialized, providing additional optimization when the function is invoked again. For example, if your Lambda function establishes a database connection, instead of reestablishing the connection, the original connection is used in subsequent invocations. We suggest adding logic in your code to check if a connection exists before creating one.

Each execution context provides 512 MB of additional disk space in the /tmp directory. The directory content remains when the execution context is frozen, providing transient cache that can be used for multiple invocations. You can add extra code to check if the cache has the data that you stored. For information on deployment limits, see AWS Lambda Limits.

Background processes or callbacks initiated by your Lambda function that did not complete when the function ended resume if AWS Lambda chooses to reuse the execution context. You should make sure any background processes or callbacks in your code are complete before the code exits.

When you write your Lambda function code, do not assume that AWS Lambda automatically reuses the execution context for subsequent function invocations. Other factors may dictate a need for AWS Lambda to create a new execution context, which can lead to unexpected results, such as database connection failures.

AWS Lambda is a serverless data processing service that runs your code as events occur and automatically manages the underlying computing resources for you. With AWS Lambda, you can extend other AWS services with custom logic, or build your own back-end services and operate at the AWS scale and with AWS performance and security. AWS Lambda can automatically execute code in response to multiple events such as HTTP requests through Amazon API Gateway , changes to objects in Amazon S3 buckets , updates to tables in Amazon DynamoDB, or state transitions in AWS Step Functions .

Lambda automatically executes your code on high-availability computing infrastructure and manages the entire administration of computing resources, including server and OS maintenance, capacity provisioning and auto scaling, code and security patch deployment, and code monitoring and logging. You just have to provide the code.

Видео HOW AWS LAMBDA WORKS INTERNALLY TAMIL | What is AWS Lambda Explain ? | InterviewDOT канала Interview DOT