What are the use cases of AWS Lambda?

Common Lambda application types and use cases

  • File processing – Suppose you have a photo sharing application.
  • Data and analytics – Suppose you are building an analytics application and storing raw data in a DynamoDB table.
  • Websites – Suppose you are creating a website and you want to host the backend logic on Lambda.

What is the benefit of Amazon AWS Lambda?

AWS Lambda lets you run code without provisioning or managing servers. You pay only for the compute time you consume – there is no charge when your code is not running. With Lambda, you can run code for virtually any type of application or backend service – all with zero administration.

What are AWS Lambda applications?

An AWS Lambda application is a combination of Lambda functions, event sources, and other resources that work together to perform tasks. You can use AWS CloudFormation and other tools to collect your application’s components into a single package that can be deployed and managed as one resource.

What AWS Lambda should not be used for?

What not to Do with AWS Lambda: Serverless Antipatterns

  • #1. Serverless Async Calls.
  • #3. Distributed Monoliths.
  • #4. Complex Processing.
  • #5. Serverless Big Data ETL Pipeline.
  • #7. Long Processing Tasks.

Who uses Lambda?

Square Enix uses AWS Lambda to run image processing for its Massively Multiplayer Online Role-Playing Game (MMORPG). With AWS Lambda, Square Enix was able to reliably handle spikes of up to 30 times normal traffic.

What is the difference between Lambda application and function?

Lambda Functions vs. Lambda Applications. A Lambda function is a piece of code (managed by AWS) that is executed whenever it is triggered by an event from an event source. A Lambda application is a cloud application that includes one ore more Lambda functions, as well as potentially other types of services.

When should I use AWS Lambda?

Use a Lambda when you need to access several services or do custom processing. As data flows through services, you use Lambdas to run custom code on that data stream. This is useful in a Kinesis Pipeline that’s receiving data from things like IoT devices.

What is the best language for AWS Lambda?

It is well known that Node and Python are the leading languages for Lambda, but it’s interesting to dig even deeper and get the exact numbers for each version used. Node 8.10 is the clear winner with 51.7 percent of functions using it.

What is the difference between Lambda function and application?

A Lambda function is a piece of code (managed by AWS) that is executed whenever it is triggered by an event from an event source. A Lambda application is a cloud application that includes one ore more Lambda functions, as well as potentially other types of services.

Why Lambda is used in python?

We use lambda functions when we require a nameless function for a short period of time. In Python, we generally use it as an argument to a higher-order function (a function that takes in other functions as arguments). Lambda functions are used along with built-in functions like filter() , map() etc.

What are limitations of Lambda functions?

AWS Lambda has the following limitations

  • The disk space (ephemeral) is limited to 512 MB.
  • The default deployment package size is 50 MB.
  • The memory range is from 128 to 3008 MB.
  • The maximum execution timeout for a function is 15 minutes*.
  • Request and response (synchronous calls) body payload size can be up to to 6 MB.

When should you avoid serverless?

Issues to Avoid When Implementing Serverless Architecture with AWS Lambda

  1. Using monolithic Lambda functions with a large code base.
  2. Using synchronous architectures.
  3. Not managing the shared code base.
  4. Choosing the wrong Lambda function memory configuration.
  5. Making Lambda functions dependent on less scalable service.