O slideshow foi denunciado.
Seu SlideShare está sendo baixado. ×

The State of Serverless Computing | AWS Public Sector Summit 2017

Anúncio
Anúncio
Anúncio
Anúncio
Anúncio
Anúncio
Anúncio
Anúncio
Anúncio
Anúncio
Anúncio
Anúncio

Confira estes a seguir

1 de 69 Anúncio

The State of Serverless Computing | AWS Public Sector Summit 2017

Baixar para ler offline

oin us to learn about the state of serverless computing from Dougal Ballantyne, Principal Product Manager, Serverless. Dougal Ballantyne discusses the latest developments from AWS Lambda and the serverless computing ecosystem. He talks about how serverless computing is becoming a core component in how companies build and run their applications and services, and he also discusses how serverless computing will continue to evolve. Learn More: https://aws.amazon.com/government-education/

oin us to learn about the state of serverless computing from Dougal Ballantyne, Principal Product Manager, Serverless. Dougal Ballantyne discusses the latest developments from AWS Lambda and the serverless computing ecosystem. He talks about how serverless computing is becoming a core component in how companies build and run their applications and services, and he also discusses how serverless computing will continue to evolve. Learn More: https://aws.amazon.com/government-education/

Anúncio
Anúncio

Mais Conteúdo rRelacionado

Diapositivos para si (20)

Semelhante a The State of Serverless Computing | AWS Public Sector Summit 2017 (20)

Anúncio

Mais de Amazon Web Services (20)

Mais recentes (20)

Anúncio

The State of Serverless Computing | AWS Public Sector Summit 2017

  1. 1. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Dougal Ballantyne, Principal Product Manager, Serverless June 13, 2017 The State of Serverless Computing
  2. 2. Agenda
  3. 3. What is serverless? Build and run applications without thinking about servers
  4. 4. Let’s take a look at the evolution of computing Physical servers in data centers Virtual servers in data centers Virtual servers in the cloud
  5. 5. Each progressive step was better Physical servers data centers Virtual servers data centers • Higher utilization • Faster provisioning speed • Improved uptime • Disaster recovery • Hardware independence • Trade CAPEX for OPEX • More scale • Elastic resources • Faster speed and agility • Reduced maintenance • Better availability and fault tolerance Virtual servers in the cloud
  6. 6. But there are still limitations Physical servers data centers Virtual servers data centers • Trade CAPEX for OPEX • More scale • Elastic resources • Faster speed and agility • Reduced maintenance • Better availability and fault tolerance • Still need to administer virtual servers • Still need to manage capacity and utilization • Still need to size workloads • Still need to manage availability, fault tolerance • Still expensive to run intermittent jobs Virtual servers in the cloud
  7. 7. Evolving to serverless SERVERLESS Virtual servers in the cloud Physical servers in data centers Virtual servers in data centers
  8. 8. No server is easier to manage than no server All of these responsibilities go away Provisioning and utilization Availability and fault tolerance Scaling Operations and management
  9. 9. Serverless is a form of event-driven computing Event-driven computing Function as a Service Serverless
  10. 10. EVENT DRIVEN CONTINUOUS SCALING PAY BY USAGE Deliver on demand, never pay for idle
  11. 11. Building blocks for serverless AWS Lambda Amazon DynamoDB Amazon SNS Amazon API Gateway Amazon SQS Amazon Kinesis Amazon S3 Orchestration and State Management API Proxy Messaging and Queues Analytics Monitoring and Debugging Compute Storage Database AWS X-RayAWS Step Functions Edge Compute AWS Greengrass Lambda@Edge
  12. 12. Serverless changes how you deliver Speeds up time to market Dedicated time to innovation Increases developer productivity Eliminates operational complexity
  13. 13. Serverless today
  14. 14. Chatbots • Powering chatbot logic • Alexa Skills for Amazon Echo Common use cases Web applications • Static websites • Dynamic web apps • Packages for Flask and Express Backends • Apps & services • Mobile • IoT </></> Media & Log Processing • Real-time data • Streaming data Big Data • MapReduce • Batch
  15. 15. Big Data • MapReduce • Batch Big data Map Phase Reduce PhaseInputs Results
  16. 16. Serverless Map/Reduce with Lambda https://github.com/awslabs/lambda-refarch-mapreduce
  17. 17. PyWren: a massive data framework for Lambda • Open source MapReduce framework using Lambda • 25 TFLOPS performance • 60 GB/sec read and 50 GB/sec write to S3 https://github.com/pywren/pywren http://pywren.io/ http://ericjonas.com/
  18. 18. Academics agree: serverless + big data = <3 (Source: arXiv)
  19. 19. Now run denser workloads with Lambda Default concurrency = 100 concurrent functions200400
  20. 20. NEW Now run denser workloads with Lambda Default concurrency = 600 concurrent functions600
  21. 21. Customers innovating with serverless
  22. 22. Enterprises are achieving massive scale with Lambda • Thomson Reuters processes 4,000 requests per second • FINRA processes half a trillion validations of stock trades daily • Hearst reduced the time to ingest and process data for its analytics pipeline by 97% • Vevo can handle spikes of 80x normal traffic • Expedia triggers 1.2 billion Lambda requests each month
  23. 23. Serverless is a core component of modern apps
  24. 24. AWS serverless platform
  25. 25. Capabilities of a serverless platform
  26. 26. Cloud logic layer
  27. 27. NEW Cloud logic layer New Lambda runtimes • Node.js v6.10 announced in March • Python 3.6 now available
  28. 28. NEW Cloud logic layer Tagging for Lambda • Add metadata to Lambda functions using tags • Track and allocate costs per function
  29. 29. Cloud logic layer Other recent features… • Iterator age metric for Amazon Kinesis records • View Lambda function policies from the console
  30. 30. NEW Cloud logic layer HIPAA compliance • Amazon API Gateway is now HIPAA compliant
  31. 31. NEW Cloud logic layer API request validation • Amazon API Gateway supports request validation • Check for required request parameters in a request’s URI, query string, and headers • Verify adherence to the request model of methods • Detailed error logs stored in Amazon CloudWatch Logs
  32. 32. NEW Cloud logic layer API Gateway + ACM • API Gateway is now integrated with AWS Certificate Manager • Deploy and configure SSL/TLS certificates for custom API Gateway domains in minutes
  33. 33. Responsive data sources
  34. 34. Lambda event sources – AWS services Amazon API Gateway Amazon S3 Amazon DynamoDB Amazon Aurora Amazon Simple Notification Service Amazon Simple Email Service Amazon Cognito AWS Snowball Edge Amazon CloudWatch Amazon Kinesis Streams Amazon Kinesis Firehose AWS CodeCommit AWS CloudFormation AWS Config Amazon Lex
  35. 35. Integrations library
  36. 36. Integrations library Amazon API Gateway listings in the AWS Marketplace
  37. 37. Reliability and performance
  38. 38. Reliability and performance Dead Letter Queues • Automatically capture events after exhausting retries • Build even more reliable event processing applications • Target Amazon SQS queues or Amazon SNS topics • Available in all regions
  39. 39. Application modeling framework Monolithic application Microservices
  40. 40. But what happens when you have an entire app made up of many functions? Composing serverless applications
  41. 41. Meet SAM
  42. 42. AWS Serverless Application Model (SAM) Standard model for representing serverless applications on AWS Functions, APIs, event sources, and data stores Simplifies deployment and management for serverless applications
  43. 43. AWS Serverless Application Model (SAM) • Natively supported by AWS CloudFormation • Export any function as a SAM template • Package and deploy SAM templates using AWS CLI • Open spec under Apache 2.0 for community extensions
  44. 44. NEW AWS Serverless Application Model (SAM) New features • Support for inline Swagger • Intrinsic functions
  45. 45. CI/CD for serverless applications </> AWS CodePipeline + SAM GitHub Amazon S3 AWS CodeCommit AWS CodeBuild AWS CodeBuild Third-party tools AWS CloudFormation Commit Build Test Deploy to Prod
  46. 46. Developer ecosystem — AWS How do you debug distributed applications made of multiple functions or services? How do you gain insights into how your functions are performing or behaving?
  47. 47. AWS X-Ray • Analyze and debug distributed apps in production • Visualize service call graph of your app • Identify performance bottlenecks and errors • Pinpoint service-specific issues • Identify impact of issues on users of the app • Trace function executions (coming soon)
  48. 48. How X-Ray works Trace requests Record traces View service map Analyze issues
  49. 49. X-Ray example
  50. 50. X-Ray example
  51. 51. X-Ray example
  52. 52. X-Ray example
  53. 53. X-Ray example
  54. 54. X-Ray example
  55. 55. X-Ray example
  56. 56. Developer tools Write code Deploy to customer Build and test Receive feedback
  57. 57. Developer ecosystem — commercial MonitoringDeployment Service Delivery Program IntegrationsCode Libraries
  58. 58. Developer ecosystem — open source Chalice Framework Serverless Java Container
  59. 59. Orchestration and state management
  60. 60. NEW AWS Step Functions update New features Integration with API Gateway Error-handling for Lambda functions Send CloudWatch Events to Step Functions
  61. 61. AWS Greengrass • Extends Lambda functions to devices • Low latency, near-real time
  62. 62. AWS Snowball Edge • Petabyte-scale hybrid device with onboard compute and storage • Deploy AWS Lambda code to Snowball Edge
  63. 63. NEW Global scale Lambda available in most major regions in the AWS global infrastructure Now available in London and Mumbai regions!
  64. 64. Lambda@Edge (in preview) Lambda@Edge is available in all Amazon CloudFront edge locations • Low-latency request/response customization • Supports viewer and origin events
  65. 65. CloudFront triggers for Lambda@Edge functions Origin server End user CloudFront cache Viewer response Origin response Viewer request Origin request
  66. 66. Lambda@Edge use cases Content customization Visitor validation A/B testing
  67. 67. Serverless is a fundamental component of modern applications
  68. 68. Conclusion Lambda is a fundamental component of modern application architectures It has a place in everything from data processing to simple web apps
  69. 69. Thank you!

×