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Serverless Computing

  1. Serverless Computing & key Consideration Anand Gupta (Senior Solution Architect at Capgemini) Linked in:
  2. 01 03 04 05 07 08 09 10 What Is Serverless ? Use cases Patterns. Communication Patterns. Key Benefits of Serverless. How does Functions-as-a-service work? Key Considerations and best practices. Introduction Agenda 02 Brief of Cloud Computing 06 Serverless Application & AWS Lambda
  3. 3 Traditional way to provide the infrastructure Data Center Provides CLI or API to manage infrastructure(AWS EC2) IAAS Provides infrastructure bases on developed application (AWS Beanstalk) PAAS Provides infrastructure on demand when the FaaS provider receive the request(AWS Lambda) Serverless Brief History of Cloud computing.
  4. 4 No Server provision or manage Scale with Usage Never Pay for Idle High Availability and fault tolerance built in What is Serverless ? Serverless is new set of emerging practices that'll change the way we build the application, it brings more agility, cuts cost and enables more efficient application development. This seems like a real fundamental shift the way we are building out application.
  5. How does Functions-as-a-service Works? /users /orders /catalogue Host Instance Application FaaS Platform /users /orders /catalogue /users Traditional Computing Serverless Computing Request: Many To One Instance Instance Request: One To One
  6. 6 01 02 03 04 05 06 New Feature Product engineers can innovate rapidly as serverless architecture has alleviated the problems of system engineering. Thus, you spend less time on operational issues and can release new feature faster. Pay for Use With serverless, you only pay for what you use, there are no hardware costs and no costs when your services are not in use, and you get away not paying anything when the application is not in use. Deployment Package Simplifies deployment and packaging, which eliminates the complex build and deploy process. Resilience and Flexibility Because Serverless is stateless, it is highly resilient when under load and in sub-optimal execution conditions. Developer productivity Smaller code, agile development and enables the developers to concentrate on code and deliver quickly. No Server to provision Eliminates the need of estimating what type of, and how many, resources our application requires also the process of acquiring machine instances and setting them up ready for deployment Key Benefits of Serverless Computing
  7. 7 Serverless Application Event Source Function Service Changes in data state Changes in Resources state Request to end points Node.js Python Java C# Go Ruby Runtime API Database External endpoint
  8. 8 Anatomy of AWS Lambda Function Handler Function Event Object Context Object Function to be executed upon invocation Data sent during Lambda function invocation Method available to interact with runtime information(request ID, log group, more) exports.handler = (event, context, callback) => { // TODO implement console.log("context object details"); console.log(JSON.stringify(context)); callback(null, “test response'); };
  9. 9 Serverless Communication Patterns Synchronous (Push) API Gateway /master Asynchronous (Event) Stream (Poll Based) SQS S3 Lambda function Lambda function Events Kinesis DynamoDB changes Lambda function
  10. 10 Design Pattern : API implementation {….} https Endpoint CloudWatch Cognito(IDM) /booking IDM MDM Booking API Gateway Service Database
  11. 11 Design Pattern : Microservice Integration {….} https Endpoint Lambda API Gateway Amazon MQ RDS /payment /orders /loyalty {….} https private Endpoint {….} third party https Endpoint API Layer Source System Message Broker & Listener Target System
  12. 12 Design Pattern : Batch Job Cloud Watch Alarm (time based) Step Functions S3 /sendMail Sendgrid Lambda invoked when scheduled time occurs Scheduled Processor Internal Service
  13. 13 BACKENDS • Apps & services. • Mobile • IoT DATA PROCESSING • Real Time • Map Reduce • Batch VOICE ENABLED SERVICES • Powering Voice Enabled Apps. • Alexa Skill Kit IT AUTOMATIONS • Policy Engines • Extending AWS Services. • Infrastructure Management WEB APPLICATIONS • Static Web sites. • API development • API Integration CHAT BOTS • Powering chat bots. Use cases
  14. 14 1. Mono Repo 2. Repo per function 3. Repo per Group /users /orders 1. Key Consideration : Repository Structure One Group of repo should not have more then 25 to 30 function No Repo per function and pipeline Group the application in function close to functionality. No mono repo. 1 2 3 4
  15. 15 Download code and dependency Create, setup and start new container Runtime Bootstrapped Code execution 2.a Key Consideration : Cold Start The Request Life Cycle AWS Provider Optimization Dev team Optimization Cold Start Time Warm Start Time Request Execution time
  16. 16 Memory size If you increase the memory, you will also get more CPU, this memory balancing approach will help to faster the start up time. Runtime Scripting languages (Python, Java script) perform a lot better in startup time in comparison to compiled runtimes (Java, .NET, C#). Code package size The larger the size, the more time it takes to spin up a new container, avoid unnecessary third-party libraries Application initialization If application is performing any task at startup, it will add to cold start, try to load the resources lazily. 2.b Key Consideration : Cold Start Improve Startup Latency
  17. 17 • Minimize your package size. • There is a hard limit of 50MB for compressed deployment package. Application Package Size • Put your dependency(e.g. jar files) in a separate directory. • An uncompressed(Layer) AWS Lambda hard limit of 250MB. Lambda Layer • Stop reaching for 3rd party dependencies and rather build your own serverless library. 3rd party dependencies 3. Key Consideration : Application Package and Dependency management
  18. 18 API Gateway should have mapping of error code to avoid CORS error. API Gateway Error Mapping Follow the proper HTTP error code. Http Error Code AWS API Gateway has a 29 second hard limit of timeout. Use short timeout limits. set them at 3-6 seconds for API calls API Gateway Timeout Use global exception handler in your code and do not allow exception to propagate outside of Lambda handler. Global Exception Handling Request and response (synchronous calls) body payload size can be up to 6 MB. Pay Load Size Lambda time out limit is 15 minute, so do not perform long job. Lambda Timeout 4. Key Consideration : Exception Handling and timeout
  19. 19 S START UP TIME • Minimize the complexity of your dependencies. • Choose interpreted languages like Node.js or Python over languages like Java and C# if cold start time is affecting user experience. M MEMORY BALANCING • Lambda costing depends on both memory allocation and execution time. If we need to reduce the Lambda execution time, one can try increasing memory (and by extension, CPU) to process it faster C CODE OPTAMIZATION • Store and reference external configurations and dependencies locally after first execution. • Avoid memory intensive or iteration of large data set. R RE-USE LAMBDA CONTAINERS • Cache reusable resources. • Limit the re-initialization of variables/objects on every invocation. Instead use static initialization/constructor, global/static variables and singletons. 5. Key Consideration : Performance
  20. 20 • Do not store secrets in application code, environment variables or in a source code. • For sensitive information, utilize a secret storage that enables both runtime access, as well as easy and routine key rotation. Manage secrets in secure storage • Offloading authentication concerns from your functions core business logic • DDOS protection, traffic throttling and rate limiting. API gateways as a security buffer • Avoid globally defined roles and resource access permissions for functions. • Minimize access rights to resources for functions using fine-grained permissions for each function Adopt Least privilege • Audit and monitor how and what functions are accessing to ensure no illegal paths are taken, and monitor security vulnerabilities in functions. • Implement central logging system to gain better observability. Monitor and log functions 6. Key Consideration : Security
  21. 21 Q/A