Keynote Gregor Hohpe - Serverless Architectures
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Serverless is much more than an abstraction over compute run-time. Serverless applications are inherently distributed, easily respond to incoming events, and change the role of cloud automation. This session reflects on how serverless influences our application delivery and takes a peek at recent trends like Event-driven Architectures and Infrastructure from Code.
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Keynote Gregor Hohpe - Serverless Architectures
- 1. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. O K , N O M O R E S E R V E R S – N O W W H A T ? Serverless Architectures Gregor Hohpe Sr. Principal Evangelist AWS
- 2. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. How modern is your cloud application? VM Container Serverless “Modern” APIs? “Traditional” Granularity? CI/CD? Progr. Languages? Managed services? Automation? Observability? State management?
- 3. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Serverless – Not just a run-time AWS Lambda AWS Fargate COMPUTE DATA STORES Amazon Aurora Serverless Amazon S3 Amazon DynamoDB AWS AppSync Amazon API Gateway Amazon SNS Amazon SQS AWS Step Functions INTEGRATION Amazon EventBridge
- 4. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Sr. Principal Evangelist, Serverless ArchitectElevator.com www.linkedin.com/in/ghohpe/ Gregor Hohpe
- 5. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Serverless Architectures: Under the Lambda covers
- 6. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS Lambda – Launched Nov 2014 • Provide your code or image; we run it as an event when things happen • Pay by the millisecond, up to 15mins • Package as .zip file (250 MB) or container image (10 GB) • Java, Go, Node.js, .NET, Python, and Ruby, or bring-your own • No provisioning or managing servers • Scale up in milliseconds in response to traffic Lambda is the compression algorithm for experience
- 7. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Lambda Architecture – High-level View Dev Tools Event Sources Async. Invocation Events Front-End Pollers Queue Synchronous Invocation Assignment Service Placement Worker Requests Front-end AWS X-Ray Amazon CloudWatch Capacity Manager Data Science Control Plane Configuration Code Lambda API
- 8. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Our experience: Implementation considerations • Placement (Assignment Service) • Fault tolerant, leader-follower model • Worker manager • Isolation levels • Firecracker micro-VMs • Tenant de-correlation • Initialization / cold starts • SnapStart • Chunks, read-ahead https://www.infoq.com/news/2023/10/aws-lambda-under-the-hood/
- 9. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Serverless Architectures: Of boxes and lines
- 10. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Serverless applications are distributed and fine-grained. Distribute responsibly!
- 11. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Friends don’t let friends use synchronous integration Customer Fraud detection service https://... Synchronous response External payment service provider https://... Synchronous response Ride booking service Resource management service Customer loyalty service Ride payment service https://... Synchronous response https://... https://... Synchronous response Synchronous response 12 3 9 6 12 3 9 6 12 3 9 6 12 3 9 6 12 3 9 6 12 3 9 6 ?
- 12. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. • Event-driven architectures • Lambda has synchronous and asynchronous invocation models • Push models, pull models, streaming • Serverless integration provides orchestration, event routing, and message queues Reduced Dependencies Failure Isolation Evolvable Architecture Independent Scalability Distributed, event-driven architecture
- 13. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Behold the lines! A B C D A B C D
- 14. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Connecting two systems. How hard can it be? A B Sync/async? Interaction model? Data format? Pub-sub or point-to-point? Conversation State? Error handling? Distributed? Partial failures? Retries? Idempotency? Back-off? Data or control flow? Polling? Systems or instances?
- 15. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Control flow vs. data flow Data Flow A B Control Flow: RPC A B Control Flow: Polling A B Control Flow: Messaging A B
- 16. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Control Flow Message Transformation Enterprise Integration Patterns Message Routing Content-based Router Message Filter Splitter Message Translator Content Enricher Claim Check Source: EnterpriseIntegrationPatterns.com ? Data (Message) Flow Puller Pusher Driver Queue Event Source Polling Source Event Target Pulling Target Active Passive Scatter Gather
- 17. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon SNS Translator API Destination Filter Amazon EventBridge Bus EventBridge with Rate Limited Target Driver Invocation Rate: 10 Control Flow Visualizing control flow: EventBridge Bus Source: EnterpriseIntegrationPatterns.com Puller Pusher Driver Queue Event Source Polling Source Event Target Pulling Target Active Passive Queue TTL: 24h Amazon SNS Translator Filter Amazon SQS Amazon EventBridge Bus EventBridge with Event Target
- 18. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Control flow is essential to understanding dynamic system behavior such as latency, scaling, batching, time-outs
- 19. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Queues invert flow control, shape traffic Arrival Rate Consumption Rate Arrival Rate Consumption Rate Queue empty Queue fills up Producer Consumer
- 20. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Queues require flow control Back Pressure: Slow down arrival rate Time-to-live (TTL): Shed old messages TTL is an SQS setting, backpressure has to be built. Even valuable messages have a meaningful time to live. Fast Producer Slow Consumer
- 21. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Queues decouple control flow but require flow control. Hard-earned experience from an integration architect
- 22. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Serverless Architectures: Coordination
- 23. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Choreography vs. Orchestration Centralized business logic in Orchestrator Transaction management across services End-to-end monitoring and error handling easier Tightly coupled Orchestrator can become single point of failure / limitation Single point of maintenance (can be good or bad) Business logic can evolve easily (add, update services) Services can scale independently Transactional consistency across services is difficult End-to-end monitoring ,handling errors, and timeout is difficult Original Design Lambda must publish events Refactored Design
- 24. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Serverless Architectures: Automation
- 25. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Cloud − Automation = Just another data center An opinionated architect
- 26. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Automation focused on infrastructure (“IaC”) Development teams Infra / Ops teams - Functionality, UX - Application architecture - Write code - Non-functional “-ilities” - Sizing, procurement - Click-Ops -> Write scripts Automation Application “Build” “Run” • Resource-oriented • Prefer simple syntax (YAML) • Strings and integers • Text editor • Object-oriented or functional • Powerful languages • Type systems • Automated testing, TDD, IDE https://architectelevator.com/cloud/iac-ifc-trends/
- 27. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. As application architecture changes, so does the role of cloud automation. Limiting cloud automation to infrastructure is no longer adequate.
- 28. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Composition with cloud automation Data change triggers workflow Type: AWS::Pipes::Pipe Properties: Description: String Name: String RoleArn: String Source: String SourceParameters: PipeSourceParameters YAML (CloudFormation) Amazon DynamoDB AWS Step Functions Source this.sourceArn = table.tableStreamArn; this.sourceParameters = { dynamoDbStreamParameters: { startingPosition: LATEST, maximumBatchingWindowInSeconds: 5, maximumRetryAttempts: 10 }, }; Object-Oriented (CDK) Target Amazon EventBridge Pipes Architecture Implementation (Services) Automation Code
- 29. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. From IaC to AaC: Architecture as Code Classic IaC (incl. CDK): Resource hierarchy Serverless Application Architecture: Data and control flow Well suited for infrastructure resources Well suited for fine-grained and loosely coupled applications Source: architectelevator.com/cloud/iac-ifc-trends/
- 30. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Coding in 202x: Fluent APIs, Pipes-and-Filters const pipeline = new PipelineBuilder<IPipelineSource, Filter, Channel, IPipelineTarget>() .fromSource(new DynamoDBStreamSource(ordersTable)) .with(new MessageSplitter('$.tickets', ['$.id', '$.userId'], 'common_')) .with(new ContentEnricher(lookupTable, { "id": "id" }, "detail")) .toTarget(new StepFunctionsTarget(…); deployPipe(this, "myPipeline", pipeline, LogLevel.ALL); Implementation with CDK (Experimental ) Amazon DynamoDB AWS Step Functions Amazon DynamoDB Message Splitter Content Enricher Architecture Automation Code Implementation Icons: EnterpriseIntegrationPatterns.com
- 31. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Program to your architecture, not cloud services Manual Translation Manual Translation Automatic Translation Direct Mapping Architecture Automation Code Implementation Traditional Model Architecture Automation Code Implementation Cloud Compiler Approach
- 32. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. as Code Actual Next-gen Serverless Automation: Application Architecture Infrastructure
- 33. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Want more? Gregor Hohpe @ghohpe www.linkedin.com/in/ghohpe ArchitectElevator.com
- 34. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Thank you! © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Please complete the session survey in the mobile app Thank you! © 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Please complete the session survey in the mobile app Gregor Hohpe @ghohpe Linkedin.com/in/ghohpe ArchitectElevator.com
Editor's Notes
- Cloud automation can do more than reduce the toil of provisioning or configuring compute infrastructure. With application-level services that orchestrate, transform, store, and route events, it can also define your application topology. By describing component granularity, dependencies, data and control flow, and degrees of coupling in executable automation code, you can redefine automation from infrastructure as code to architecture as code. This talk takes AWS CDK to the next level and provides a novel take on automation at the intersection of serverless, integration, abstraction, and design patterns, with a special emphasis on the lines, not just the boxes.
- While many customers associate serverless with Lambda, there are actually serverless services at all layers of the stack. And while Lambda offers many key advantages for our customers, it’s really when all these other components surround Lambda that we start to see much bigger benefits. Messaging, orchestration, storage and compute together are the secret sauce. But In fact, it’s really when all of these components come together that we really start to see big gains.
- So, synchronous communication blocks resources in all involved services, worst case for the time the entire processing takes. Additionally, problems in downstream services can accumulate upstream. This is why there are mitigation patterns like circuit breaker in the first place. So, particularly under load, a synchronous integration approach can jeopardize the reliability of the entire application, and it can require excessive horizontal scaling with the respective cost attached. Next step, they worked on reducing their runtime coupling, or temporary coupling, by switching from sync to async comms. <click>
- So why is connecting systems so difficult and so important? The answer quickly becomes apparent once we look at how connected systems behave
- This is from 2008 / 2015
- This is from 2008 / 2015
- This is from 2008 / 2015 Pipes with API destination is synchronous, adjusts concurrency based on the max Invocation Rate
- Note: Serverlesspresso has a backpressure function built from DynamoDB as a flag for SFN because Baristas have limited capacity
- [Sindhu] <don’t click – auto> Above is an example of ride booking app: 3 Lambda functions handle a customer booking: the booking service, payment service, and driver assignment. The coordination across these services is choreographed by passing events through EventBridge.<CLICK> Such an event-driven architecture is flexible and scalable, but it relies on each Lambda function emitting events like “Payment received”. With Lambda destinations that’s easy to do, but still the Lambda functions have to participate by returning the event data.<CLICK> Since the business flow is distributed, it difficult to maintain transactional scope, for example in case the payment service goes down or times out no event is published. To address these challenges, we can refactor this design<CLICK> We replaced the Choreography with a Step Functions Orchestrator that calls each Lambda function. Now the functions are just passive elements that are called by Step Functions and it’s easier to see the entire flow, track the status of each workflow instance. <CLICK> But architecture is always about trade-offs, so now things are a bit more tightly coupled with a single point of maintenance. That can be a good thing if you want control, but it can become a bottleneck if services come and go.
- With automation playing such a central role, you could go as far as saying that if you remove automation from the cloud, you don’t have much more left than a good-old data center. At AWS, we have very nice data centers, but I haven’t met any customer who’s looking for yet another data center. So, let’s not do that.
- Modern automation does more than just deploy an ec2 cluster. <CLICK> The most common thing that automation does is provision resources. In our trivial example, that might be two VMs, a load balancer and a gateway. But servers don’t do much on their own, so you need to deploy workloads. <CLICK> That’s one step closer but now you have disconnected pieces. To turn this into a functioning application, you need to wire it together.<CLICK> We call that composition: what is connected to what? And last, you’ll might have some slight differences in configuration. <CLICK> You might have a primary server and a secondary, or have different services connected to different databases. So you also want to do that via automation. So, this architecture diagram helps us understand the different aspects that come together when we say "automation".
- So how does serverless relate back to our architecture model of cloud automation? Well, the provisioning is all done for you and deployment can be as simple as placing a ZIP file in a bucket.<CLICK> So, the element that’s becoming most prominent for serverless applications is composition - that’s how those loosely coupled components are connected into a working application. Composition defines many essential properties of a serverless application, e.g. its granularity - how small are your pieces? It also defines the dependencies - which components send messages or events to which other components? Do they do so synchronously or asynchronously? You will likely use services like Amazon SQS, Amazon SNS and Amazon EventBridge for those connections.
- That’s what I am working on – stay tuned
- With tools such as the AWS CDK, you are not only being able to define your infrastructure as code. If you think about serverless applications, things as deployment, composition and configuration are the main drivers for leveraging automation tools. <CLICK> So you can say, this is much more than infrastructure as actual code.