Going serverless with aws
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Serverless is aiming to be the future of software development, but what does it really mean running without servers? In this session we will explain how to build a serverless application on top of AWS. We will understand how AWS Lambda functions work, how to use them properly and how can we debug and monitor serverless application.
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Going serverless with aws
- 1. Going Serverless with AWS Alex Landa
- 2. Services in the Cloud • Infrastructure (IaaS) • virtualized basic computing, networking and storage resources. • EC2, VPC, EBS … • Platform (PaaS) • complete development and deployment environment in the cloud • RDS, ElastiCache, Elastic Beanstalk … • Software (SaaS) – complete application offered through the web.
- 3. Serverless - don’t think about servers • A trending execution model in which the server management and the resource management are completely hidden. • AWS offers a set of serverless services • Storage – S3 • DB – DynomoDB • Queues – SQS, Kinesis • Notifications – SNS • Monitoring – CloudWatch • Compute - Lambda
- 4. Used for • Automation – ”maintenance scripts” for the cloud • ETL – extraction and transformation layer in front of the backend services • External services • Glue code – connect between several services • Full blown applications – not the main purpose (yet)
- 5. Lambda • AWS Lambda allows you to define a function that will be executed when some event happens. • You do not need to care about the physical execution regarding resources as AWS Lambda will automatically scale and provide CPU/Network/IO and Memory for it. • A major part in a serverless architecture.
- 6. Lambda • The Lambda code you write must be in one of the following languages: • Java. • C#. • Python. • Node.js (JavaScript). • Go
- 7. How Does It Work? • The main component of the Lamda is the handler. • The point-of-entry. • When some event happens (more about it in the next slides), Lamda will create a container ands runs your function there (by invoking the handler). • The container may be retain for some time to allow consecutive executions without paying the bootstrapping price. • Note that you can’t count on it and a new container may be created.
- 8. Event Sources • AWS Lambda can connect and be activated by a large variety of events. • For example: • S3 – respond to object_created event. • SNS – respond to object published on a configured topic. • API Gateway – wire the Lambda to a REST API. • CloudWatch Events – respond to object changing state (e.g., EC2 instance state changes). • You can also invoke the Lambda directly from the CLI or your application (custom events).
- 10. The Container • Lamda creates a container to run your function. • When your function exits, the container is frozen for some time and may be thawed for consecutive execution. • You are provided with 500MB of /tmp directory which contents are maintained between invocations. • Note that you can’t count on it as a new container may be created for you. • A good use-case for /tmp is caching.
- 11. The Container • Global objects can be reused and are maintained cross freeze/thaw. • For example, static objects in Java. • In is considered a good practice to try and reuse global resources (e.g., connection pools).
- 12. What about scale? • Scale in Lambda == “Concurrent Executions” • Handled by execution pools – 1000 per account, per region • Can be changed • If not set function uses “unreserved concurrency pool” • All specified limits should reach together 900 • 100 reserved for the ”unreserved concurrency”
- 13. Throttling • Behaves differently for synchronous and asynchronous events • HTTP – synchronous • S3 trigger – asynchronous • In case of synchronous - invoking application receives a 429 error • In case of asynchronous - will automatically retry the invocation twice, with delays between retries • If DLQ is configured the failed event will be sent to SNS topic or SQS Queue
- 14. Advanced example Machine Learning HTTP Endpoint
- 15. Logging – CloudWatch • Lambda integrates with Cloud Watch for logging • Pushes the logs to /aws/lambda/<function name> • Common errors: • permissions denied – modify IAM permission • timeout exceeded – increase timeout • memory exceeded - increase memory • Exception stack trace - go and handle :)
- 16. Monitoring – Cloud Watch • Provides you a full view on the execution metrics • Number of executions • Duration • Failures • Concurrent executions • .. • You should set alarms on those metrics to be notified in case of unexpected behavior
- 17. Serverless != Effortless • How do we manage all of this? • Manually – Good for demo and job security, bad for everything else.. • Automatically – using Terraform / CloudFormation + scripts • Good but requires a lot of knowledge • Doesn’t solve the debugging • We want a framework to manage it for us!
- 18. Serverless Framework • Open source CLI for building serverless applications • Allows you to create, deploy, test , invoke and debug your serverless services • Serverless service is composed of : • Functions – mapped to AWS Lambda • Resources • Permissions
- 19. Serverless Framework • Uses serverless.yml to describe the functions of your service as well as their permissions and dependent resources • By running serverless deploy it will deploy your changes using cloud formation
- 21. Questions ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?