Downloaded 79 times
Uploaded byGlobalLogic Ukraine
AWS Lambda Features and Uses
The document provides an extensive overview of AWS Lambda and its serverless computing features, highlighting its advantages like flexible scaling, cost efficiency, and ease of use. It discusses Lambda's functionality, including supported services, languages, execution roles, and error handling. Additionally, it outlines pricing, deployment limits, and the pros and cons of using AWS Lambda for application development.
In this document
Powered by AI
Overview of AWS Lambda and its features, introduced by Dmytro Harbuzov, with agenda outlining the presentation.
Concept of Cloud Computing and its various applications, including Security, Databases, and Networking.
An overview of Amazon Web Services, including its global infrastructure and product categories.
Introduction to serverless computing and AWS Lambda's features: SCALE, SIMPLICITY, AVAILABILITY, COST.
Presentation of AWS services compatible with Lambda including data stores and messaging services.
Details on supported programming languages, serverless applications, synchronous/asynchronous models, and the role of the Lambda context.
Logging practices using AWS CloudWatch, error handling strategies, and integration with AWS Step Functions.
Resource limits regarding memory, execution time, and deployment package restrictions in AWS Lambda.
Overview of AWS Lambda pricing including free tier offers, request and compute time costs.
Pros and cons of AWS Lambda including scaling, operational management, execution duration, and testing challenges.
Thank you note and contact information for further queries.
More Related Content
Similar to AWS Lambda Features and Uses
AWS Lambda Features and Uses
- 1. AWS Lambda: Features andUses Dmytro Harbuzov Senior Software Engineer, Сonsultant
- 2. Agenda 1. Introduction 2. AmazonWeb Services overview 3. AWS Lambda serverless computing 4. AWS Lambda pros and cons 2
- 3.
- 4. Applications Security Databases Operating Systems Virtualization Servers Storage Networking Data Centers EnterpriseIT Infrastructure Platform Software Customer Customer Provider Customer Provider Provider 4
- 5.
- 6.
- 7.
- 8.
- 9. AWS Lambda &serverless computing 9
- 10. What is serverlesscomputing? -SCALE: flexible scale without worrying about complex and time-consuming data migrations. - SIMPLICITY: you don’t manage any servers and OS. - AVAILABILITY: managed by cloud provider - COST: you pay only for the requests served and the compute time required to run your code 10
- 11.
- 12. Supported services Amazon datastores S3 Dynamo DB Kinesis Cognito AWS: - CloudFormation - CloudTrail - CodeCommit Amazon CodeCommit Amazon Alexa Amazon API Gateway AWS lo T Amazon SES Amazon SNS Cron events Repositories End points Event/message services 12
- 13.
- 14. 14 Serverless applications Event SourceFunction Services 14
- 15. 15 Example synchronous model 15 15 CustomApp AWS Lambda Execution Role Lambda Function
- 16. 16 16 Example asynchronous model UserAWS LambdaExecution Role Lambda Function Amazon S3 Access Policy Source Bucket Notification Configuration
- 17. 17 Example stream-based model 17 CustomApp AWS LambdaExecution Role Lambda Function Amazon Kinesis Event Source Mapping Stream
- 18. Lambda permissions model -Permissions you grant to this role determine what your AWS Lambda function can do - If event source is Amazon DynamoDB or Amazon Kinesis, then add read permissions in IAM Role - Permissions you grant to your Lambda function determine which service or event source can invoke your function - Resource policies make it easy to grant cross-account permissions to invoke Lambda function IAM Role Function (resource) policy 18
- 19. Lambda Configuration - Computeresources - Maximum execution time (timeout) - IAM role (execution role) - Handler name 19
- 20. Lambda execution context EachExecution Context provides 500MB 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 Any declarations in your Lambda function code (outside the handler code) remains initialized, providing additional optimization when the function is invoked again (for example Database connections, Environment Variables) How? What? 20
- 21. Programming model - Handler.Handler is the function AWS Lambda calls to start execution of your Lambda function. - Context. AWS Lambda also passes a context object to the handler function, as the second parameter. Via this context object your code can interact with AWS Lambda. - Logging. Your Lambda function can contain logging statements. AWS Lambda writes these logs to CloudWatch Logs. - Exceptions. Your Lambda function needs to communicate the result of the function execution to AWS Lambda. 21
- 22. Lambda Function Handler -inputType: The first handler parameter is the input to the handler, which can be event data (published by an event source) or custom input that you provide such as a string or any custom data object. - outputType: If you plan to invoke the Lambda function synchronously (using the RequestResponse invocation type), you can return the output of your function using any of the supported data types. If you plan to invoke the Lambda function asynchronously (using the Event invocation type), the outputType should be void. 22
- 23. Lambda Context Object -getMemoryLimitInMB() - getFunctionName() - getFunctionVersion() - getInvokedFunctionArn() - getAwsRequestId() - getLogStreamName() - getLogGroupName() - getClientContext() - getIdentity() - getRemainingTimeInMillis() - getLogger() 23
- 24. Lambda logging - AWSLambda recommends Log4j 2 to provide a custom appender. You can use the custom Log4j appender provided by Lambda for logging from your lambda functions. - In addition, you can also use the statements “System.out()” and “System.err()” in your Lambda function code to generate log entries. AWS CloudWatch Options 24
- 25.
- 26. Lambda error handlingwith AWS Step Functions Function Example START CATCH 26 26 END
- 27. Limits per invocation 27 Memoryallocation range Ephemeral disk capacity (*/tmp* space) Number of file descriptors Number of processes and threads (combined total) Max execution duration per request Invoke request body payload size (RequestResponse/synchronous invocation) Invoke request body payload size Min 128 MB / Max 3008 MB (with 64 MB Increments) 512 MB 1,024 1,024 300 seconds 6 MB 128 KB Resource Limits
- 28. Deployment limits 28 Item DefaultLimit Lambda function deployment package size (compressed .zip/.jar file) 50 MB Total size of all the deployment packages that can be uploaded per region 75 MB Size of code/dependencies that you can zip into a deployment package (uncompressed .zip/.jar file) Note - Each Lambda function receives an additional 500 MB of non-persistent disk space in it's own /tmp directory. The /tmp directory can be used for loading additional resources like dependency libraries or data or data sets during function initialization 250 MB Total size of environment variables set 4 KB
- 29. 29 Lambda pricing 1 Mrequests per month 400,000 GB-SECONDS of compute time per month The Lambda free tier does not automatically expire at the end of your 12 month AWS Free Tier term, but is available to both existing and new AWS customers indefinitely. Free Tier 1 M requests free First 1M requests per month are free $0.20 Per 1M requests thereafter $0.0000002 per request Requests 400,000 GB-SECONDS per month free First 400,000 GB-seconds per month up to 3.2M seconds of compute time, are free $0.00001667 for every GB- second used thereafter The price depends on the amount of memory you allocate to your function Duration 29
- 30. Lambda pros andcons - Scaling - Faster Development - Operational Management - Reduction in Operational - Costs + 30
- 31. Lambda pros andcons - Scaling - Faster Development - Operational Management - Reduction in Operational - Costs - Execution Duration - Stateless - Testing - Monitoring and Debugging - Denial of Service - Tracking + - 31
- 32.