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SMC301 The State of Serverless Computing

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Join us to learn about the state of serverless computing from Dr. Tim Wagner, General Manager of AWS Lambda. Dr. Wagner 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.

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SMC301 The State of Serverless Computing

  1. 1. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Dr. Tim Wagner, General Manager, AWS Lambda and Amazon API Gateway April 18, 2017 State of Serverless Computing AWS Summit San Francisco
  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. NEW Now run denser workloads with Lambda Default concurrency = 600 concurrent functions600
  20. 20. Customers innovating with serverless
  21. 21. 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
  22. 22. © 2017 Autodesk Alan Williams Enterprise Architect AWS SF Summit 2017 Tailor - Managing AWS accounts at scale, serverlessly @alanwill alanwill
  23. 23. https://archiveofourown.org/works/1974981 Once Upon A Time…
  24. 24. Human Error Labor intensive Inconsistency Provisioning Request Turnaround (1-2 weeks) Global Configuration Changes
  25. 25. http://www.eharmony.com.au/dating-advice/dating/what-if#.WJFRCkXysnU
  26. 26.  …we could provision accounts in minutes vs weeks?  …we could make global changes to all accounts with a single API call?  …we could manage all accounts like a single account?  …we lost all care for whether we have 100 or 10000+ accounts?
  27. 27. Tailor Tailor-made + serverless AWS Account management at scale
  28. 28.  Low Ops  No OS patching  No configuration management  Minimal capacity planning  Code focus  Economical  Managed  Seamless integration  Just works Why Lambda & API Gateway? SSH
  29. 29. Current Capabilities
  30. 30. Provisioning • Lambda + API Gateway + Organizations Standards Enforcement • Lambda + API Gateway Querying • API Gateway + Lambda + DynamoDB Auditing • Config Rules + Lambda + DynamoDB
  31. 31. https://www.collegetransitions.com/top-architecture-colleges/ Architecture
  32. 32. https://99robots.com/wordpress-security-log/ Security
  33. 33.  All actions logged & auditable  IAM session name  CloudTrail  Root MFA enabled  Isolated AWS account Security Features
  34. 34. https://admissions.byu.edu/how-much-does-it-cost Economics
  35. 35. Pre-Tailor (Manual) Post-Tailor (Automated) Average # of new accounts per month 2 20 Provisioning Time 10 hours 10 minutes Tailor Infrastructure N/A $125/m Cost per account >$500 <$6 ROI
  36. 36.  ~$125 per month  $30 - Cloudwatch/DynamoDB/Config/RDS  $75 – Lambda How much does it cost to run?
  37. 37.  5-10 accounts per week  100s of accounts under management  Serving ~100 project teams / ~500 engineers / 4 business units  10 minutes provisioning time  Peak 400 Lambda invocations per sec from Kinesis Streams  1 month engineering & development time Stats
  38. 38.  Increased time to value  Reduction in human errors  Increased security posture  Reduction in provisioning time  Scalable  Reusable Benefits
  39. 39. http://www.gastro.org/about/initiatives/aga-roadmap-to-the-future-of-gi-practice ArchitectureRoadmap
  40. 40.  VPC Peering Approvals  Tailor Bot  Serverless – SAM migration  Open Source Very soon…
  41. 41. Autodesk and the Autodesk logo are registered trademarks or trademarks of Autodesk, Inc., and/or its subsidiaries and/or affiliates in the USA and/or other countries. All other brand names, product names, or trademarks belong to their respective holders. Autodesk reserves the right to alter product and services offerings, and specifications and pricing at any time without notice, and is not responsible for typographical or graphical errors that may appear in this document. © 2017 Autodesk. All rights reserved.
  42. 42. Serverless is a core component of modern apps
  43. 43. AWS serverless platform
  44. 44. Capabilities of a serverless platform
  45. 45. Cloud logic layer
  46. 46. NEW Cloud logic layer New Lambda runtimes • Node.js v6.10 announced in March • Python 3.6 now available
  47. 47. NEW Cloud logic layer Tagging for Lambda • Add metadata to Lambda functions using tags • Track and allocate costs per function
  48. 48. Cloud logic layer Other recent features… • Iterator age metric for Amazon Kinesis records • View Lambda function policies from the Console
  49. 49. NEW Cloud logic layer HIPAA compliance • Amazon API Gateway is now HIPAA compliant
  50. 50. 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
  51. 51. 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
  52. 52. Responsive data sources
  53. 53. 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
  54. 54. Integrations library
  55. 55. Integrations library Amazon API Gateway listings in the AWS Marketplace
  56. 56. Reliability and performance
  57. 57. 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
  58. 58. Application modeling framework Monolithic application Microservices
  59. 59. But what happens when you have an entire app made up of many functions? Composing serverless applications
  60. 60. Meet SAM
  61. 61. 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
  62. 62. 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
  63. 63. NEW AWS Serverless Application Model (SAM) New features • Support for inline Swagger • Intrinsic functions
  64. 64. 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
  65. 65. 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?
  66. 66. 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 (preview)
  67. 67. How X-Ray works Trace Requests Record Traces View Service Map Analyze Issues
  68. 68. X-Ray example
  69. 69. X-Ray example
  70. 70. X-Ray example
  71. 71. X-Ray example
  72. 72. X-Ray example
  73. 73. X-Ray example
  74. 74. X-Ray example
  75. 75. Developer tools Write code Deploy to customer Build and test Receive feedback
  76. 76. Developer ecosystem — commercial MonitoringDeployment Service Delivery Program IntegrationsCode Libraries
  77. 77. Developer ecosystem — open source Chalice Framework Serverless Java Container
  78. 78. Orchestration and state management
  79. 79. NEW AWS Step Functions update New features Integration with API Gateway Error-handling for Lambda functions Send CloudWatch Events to Step Functions
  80. 80. AWS Greengrass (in preview) • Extends Lambda functions to devices • Low latency, near-real time
  81. 81. AWS Snowball Edge • Petabyte-scale hybrid device with onboard compute and storage • Deploy AWS Lambda code to Snowball Edge
  82. 82. NEW Global scale Lambda available in most major regions in the AWS global infrastructure Now available in London and Mumbai regions!
  83. 83. Lambda@Edge (in preview) Lambda@Edge is available in all Amazon CloudFront edge locations • Low-latency request/response customization • Supports viewer and origin events
  84. 84. Amazon CloudFront triggers for Lambda@Edge functions Origin server End user CloudFront cache Viewer response Origin response Viewer request Origin request
  85. 85. Lambda@Edge use cases Content customization Visitor validation A/B testing
  86. 86. Serverless is a fundamental component of modern applications
  87. 87. Learn more about serverless Tuesday, April 18 10:15 AM - 11:15 AM Building Serverless Web Applications (SMC302) 11:30 AM - 12:30 PM Real-time Data Processing Using AWS Lambda (SMC303) 12:45 PM - 1:45 PM Serverless Orchestration with AWS Step Functions (SMC304) 2:00 PM - 3:00 PM Building CI/CD Pipelines for Serverless Applications (SMC305) 2:00 PM - 3:00 PM Serverless big data architectures (BDA303) Wednesday, April 19 12:00 PM - 2:00 PM Wild Rydes Takes Off – The Dawn of a New Unicorn (WKS407) 12:00 PM - 2:00 PM Build an Alexa Skill using AWS Lambda (WKS403A)
  88. 88. Conclusion Lambda is a fundamental component of modern application architectures It has a place in everything from data processing to simple web apps