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Microservices in the Enterprise


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This presentation provides an overview of microservices architectures in the enterprise. It includes a series of best practices and techniques for implementing microservices solutions in the real world.

Published in: Technology

Microservices in the Enterprise

  1. 1. A Practical Guidance to Microservices in the Enterprise
  2. 2. About Us • Emerging technology firm focused on helping enterprises build breakthrough software solutions • Building software solutions powered by disruptive enterprise software trends -Machine learning and data science -Cyber-security -Enterprise IOT -Powered by Cloud and Mobile • Bringing innovation from startups and academic institutions to the enterprise • Award winning agencies: Inc 500, American Business Awards, International Business Awards
  3. 3. About This Webinar • Research that brings together big enterprise software trends, exciting startups and academic research • Best practices based on real world implementation experience • No sales pitches
  4. 4. • Microservices overview • Some inspirational architectures • Microservices in the enterprise • Enterprise microservices patterns • Capabilities • Technologies Agenda
  5. 5. Microservices: What’s the fuss all about?
  6. 6. • SOA fatigue • Top down has proven to be impractical in the enterprise • Large monolithic applications can’t evolve fast enough • Large monolithic applications can’t scale fast enough • Docker and the container revolution • Emergence of new and exciting programming platforms (NodeJS, GO, etc) • Friction between the need for innovation and the constrained enterprise software development practices Factors Contributing to the Raise of Microservices
  7. 7. Microservices?
  8. 8. A Definition of Microservices Loosely Coupled Service Oriented Architecture with Bounded Contexts
  9. 9. Loosely Coupled SOAs • Service dependencies • Component sharing • Database sharing • Centralized ESBs • Organizational coupling • Conway’s Law:
  10. 10. Bounded Contexts • Inspired by domain driven design • Encapsulates the details of a single business domain • Self-contained entity for the purpose of software development • Ability to update a microservices without knowledge of its peers
  11. 11. Microservices in the Real World
  12. 12. Some Examples Scalability soa plus-2014 AWS Re:Invent : Asgard to Zuul Resiliency at Massive Scale Microservice Architecture philly-ete
  13. 13. Foundational Building Blocks of Microservices Architectures ConfigurationTooling Discovery Routing Observability Datastores Operational: Orchestration and Deployment Infrastructure Development: Languages and Container
  14. 14. Netflix OSS Microservices Architecture Edda Archaius Configuration Asgard Aminator Tooling Eureka Prana Discovery Denominator Zuul, Netty Ribbon 2.0 Routing Hystrix Pytheus SALP Observability Ephemeral datastores using Dynomite, Memcached, Astyanax, Staash, Priam,Cassandra Manual Orchestration with Asgard and deployment on AWS or Eucalyptus Java, Groovy, Scala, Clojure, Python, Node.js with AMI and Docker Containers
  15. 15. Twitter Microservices Architecture Decider ConfigurationTooling Finagle Zookeeper Discovery Finagle Netty Routing Zipkin Observability Custom Cassandra-like datastore: Manhattan Orchestration using Aurora deployment in datacenters using Mesos Scala with JVM Container
  16. 16. Gilt Microservices Architecture Decider Configuration Ion Cannon SBT Rake Tooling Finagle Zookeeper Akka Finagle Netty Discovery Routing Zipkin Observability Datastores per Microservice using MongoDB, Postgres, Voldemort Deployment on AWS Scala and Ruby with Docker Containers
  17. 17. Hailo Microservices Architecture Configuration Hubot Janky Jenkins Tooling go-platform Discovery go-platform RabbitMQ Routing Request trace Observability Datastore based on Cassandra Deployment on AWS Go using Docker
  18. 18. Microservices in the Enterprise
  19. 19. Challenges for Adopting Microservices in the Enterprise • Open source technology adoption • Organizational boundaries • Strict business processes • Traditional SOA mindset • Limited cloud adoption
  20. 20. Benefits of Adopting Microservices in the Enterprise • SOA that works • Building products instead of projects • Agility • Speed to market • Innovation • Remove friction for the adoption of new technologies
  21. 21. Microservices vs. SOA • SOA promise == Microservices reality • Federated innovation vs. Designed by committee • Small functional services vs. Large business services • REST and lightweight RPC vs. SOAP and WS-* • Lightweight middleware vs. ESBs • Decentralized governance vs. Centralized service repository • Development agility vs. Control
  22. 22. Building Enterprise-Ready Microservices Solutions
  23. 23. Relevant Capabilities of Enterprise Microservices Architectures • Service discovery • Service description • Deployment isolation • Lightweight middleware • Service gateway • Data Source partition • Verb partition
  24. 24. Microservices discovery
  25. 25. Capabilities • Removing coupling between microservices and client apps • Dynamically registering microservices in an enterprise topology • Allow client applications and other services to dynamically discover microservices and adapt to changes • Avoid the centralized registry pattern of traditional SOAs
  26. 26. Enterprise Microservices Discovery Pattern
  27. 27. Technologies • ( ): DNS-style service discovery and configuration • Netflix’s Eureka ( ): AWS service registry used for locating services for the purpose of load balancing and failover • Zookeeper ( ): Centralized service used for maintaining highly available configuration information • Etcd ( ): Distributed key value store optimized for service discovery
  28. 28. Microservices description
  29. 29. Capabilities • Express features of microservices in a descriptive format that can be understood by client applications • Manage microservices metadata • Simplify the creation of client artifacts • Manage versions of microservices
  30. 30. Enterprise Microservices Description Pattern
  31. 31. Technologies • Swagger ( ): Description language and description modeling tooling for RESTful services • API Blueprints ( ): Description language and description modeling tooling for Web APIs: • Apache Thrift IDL ( ): Highly scalable, cross language service development • Google’s gRPC IDL( ): HTTP2 framework for cross platform service development
  32. 32. IPC microservices
  33. 33. Capabilities • Enable internal communication between microservices • Provide high performance interactions between large number of microservices • Enable seamless cross language communication between microservices and client applications • Facilitate rapid microservices implementations across different languages
  34. 34. Enterprise Microservices IPC Pattern
  35. 35. Technologies • Apache Thrift ( ): Highly scalable, cross language service development • Google’s gRPC ( ): HTTP2 framework for cross platform service development • Akka ( ) : Framework for building highly concurrent, distributed applications • Twitter’s Finagle( ): RPC framework for JVM services • Netty( ): Asynchronous, even driven framework for client server solutions
  36. 36. Deployment isolation
  37. 37. Capabilities • Isolate the infrastructure between microservices • Enable continuous deployment practices • Allow microservices portability across platforms
  38. 38. Enterprise Microservices Deployment Container Pattern
  39. 39. Technologies • Docker ( ): Container platforms for packaging, shipping and distributing applications • Rocket( ): Runtime for Linux containers • Google’s Kubernetes( ): Platform for managing containers
  40. 40. Microservices: Data source partition strategy
  41. 41. Capabilities • Enable a standard model for accessing data via microservices • Partition microservices at the data source level • Facilitate the composition of data access microservices • Allow flexible data access models for client applications
  42. 42. Enterprise Microservices Data Source Partition Pattern
  43. 43. Technologies • Facebook’s GraphQL( introduction.html) : URI-centric protocol for data fetching • Odata(https:// ): REST protocol for querying data • Netflix’s Falcor( ): Data access API framework for JSON data sources
  44. 44. Microservices: Verb/Use Case partition strategy
  45. 45. Capabilities • Efficiently partition microservices by use case or function • Compose microservices to enable more complex use cases • Facilitate the functional testing of microservices
  46. 46. Enterprise Microservices Verb Partition Pattern
  47. 47. Technologies • Apache Thrift ( ): Highly scalable, cross language service development • Google’s gRPC ( ): HTTP2 framework for cross platform service development • Akka ( ) : Framework for building highly concurrent, distributed applications • Twitter’s Finagle( ): RPC framework for JVM services • Netty( ): Asynchronous, even driven framework for client server solutions
  48. 48. Lightweight middleware
  49. 49. Capabilities • Extend microservices with simple middleware capabilities such as routing, transformation, persistent messaging etc • Provide a standard model to enable the communication between client apps and microservices • Expand the message exchange patterns supported by microservices solutions
  50. 50. Enterprise Microservices Lightweight Middleware Pattern
  51. 51. Technologies • RabbitMQ ( : Simple messaging infrastructure for applications • Linkedin’s Kafka( ): Scalable publish-subscribe model for applications • ZeroMQ( ): Embeddable networking and messaging model for applications
  52. 52. API Gateway
  53. 53. Capabilities • Abstract the communication between client applications and internal microservices • Compose microservices into client-ready services • Extend microservices with enterprise ready capabilities
  54. 54. Enterprise Microservices API Gateway Pattern
  55. 55. Technologies • Mashape’s Kong ( ): Open source management platform for APIs and microservices • Apigee(): Market leader in API management • 3Scale( ): API management platform • Azure API Gateway( ): Azure native service for API and microservices management • AWS API Gateway( ): AWS native service for API management
  56. 56. Microservices Observability
  57. 57. Capabilities • Detect and prevent failures in complex microservices topologies • Trace request flow across microservices • Monitor service dependencies real time
  58. 58. Enterprise Microservices Observability Pattern
  59. 59. Technologies • Netflix’s Hystrix( ): Framework for detecting and preventing microservices failures • Twitter’s Zipkin( ): Framework for enabling request tracing across microservices • Trace( ): Platform for tracing interactions between microservices • Spigo( ): Simulate request interactions between microservices
  60. 60. Other relevant microservices capabilities
  61. 61. Other Relevant Microservices Capabilities • Failure isolation • Federated databases • Design for failure • Distributed configuration management • Testing • Security
  62. 62. Summary • Microservices are the future of enterprise distributed systems • Enterprise microservices solutions need to be implemented from the ground up • We can drive inspiration from internet giants • Foundational blocks of microservices architectures include: -Discovery -Description -Lightweight middleware -Partition by data source -Partition by verb -IPC communication -API Gateway -Observability • Start small, iterate….
  63. 63. Thanks