Integration in the Cloud, by Rob Davies
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The document discusses microservices and cloud integration technologies, focusing on the evolution of the Fabric8 microservices platform and its orchestration capabilities with Kubernetes. It highlights the advantages of microservices architecture, including deployment independence and improved scalability, as well as logging and metrics management strategies. The content provides insights into tools like Jenkins and the importance of automation in continuous integration and continuous delivery (CI/CD) within a microservices ecosystem.
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Structured Logging Example
{
"STATUS": "200”,
"REQUEST": "GET /apache_pb.gif
HTTP/1.0”,
"HOST": ”127.0.0.1”,
"REFERER": http"REFERER":
http://www.example.com/"REFE
RER":
http://www.example.com/start.ht
ml,
"USER": "frank”,
"TIME": "10/Oct/2000:13:55:36
-0700”,
"USERAGENT": "Mozilla/4.08 [en]
(Win98; I ;Nav)“,
"IDENTITY": "-”,
"SIZE": "2326”
}
Context added by the logging
process
Machine Readable
Filterable and Searchable](https://image.slidesharecdn.com/integrationinthecloud-161011194609/85/Integration-in-the-Cloud-by-Rob-Davies-54-320.jpg)
Integration in the Cloud, by Rob Davies
- 1. Integration in The Cloud Rob Davies 2016
- 2. 2 Rob Davies • Director of Middleware Engineering for iPaaS, Technical Director for Fuse • Herd the fabric8 cats • Over 20 years experience of developing large scale solutions for telcos and finance • Creator of ActiveMQ and ServiceMix • Committer on open source projects, including fabric8, Apache Camel and other stuff …
- 4. 4 Camel’s Journey to Microservices Self-Service, On-Demand, Elastic, Infrastructure as Code (Cloud) Re-Org to DevOps Automation Puppet, Chef, Ansible and/or Containers Fabric8 v1 (2010 ish)
- 6. 6 Camel’s Journey to Microservices CI & CD Deployment Pipeline One Microservice Silicon Valley DotCom Startup Meanwhile …
- 7. 7 We had to pivot and go Kubernetes and containers
- 8. 8 Why do you want to run your application inside containers?
- 9. 9 ● Lightweight footprint and minimal overhead, ● Portability across machines, ● Simplify DevOps practices, ● Speeds up Continuous Integration, ● Empower Microservices Architectures. ● Isolation Container Advantages
- 10. 10 Kubernetes: Container Orchestration • Inspired by Google’s experience with Orchestration • Automatic bin packing • Self healing • Horizontal Scaling • Service Discovery and load balancing • Automated rollouts and rollbacks • Secret and Configuration management • Storage orchestration • 2 years old – 30,000 commits
- 11. 11 Master API Server Service Layer VirtualPhysical Private Public Persistent Storage Node Node Logger Node Node Node Node Dev Ops SCM (Git/Svn) CI/CD Automation Routing Layer Registry SDN Overlay Network Controllers - Scheduler - Replication - Services - Builds - Routes - Deployment Kubernetes OpenShift - Deployments - Builds - ImageStreams
- 12. 12
- 13. 13
- 14. 14 Open Source community Version 1.3.x Hosted on GitHub 800+ contributors 34,000+ commits 16,000+ GitHub stars Red Hat HP IBM Mesosphere Microsoft Project Partners CoreOS Pivotal SaltStack VMWare http://kubernetes.io/ https://github.com/kubernetes/kubernetes
- 15. 15
- 17. 17 Peak of Inflated Expectations x Trough of Disillusionment Serious Hotness Techology Trigger Slope of Enlightenment
- 18. 18 Red Hat Definition “Microservices is an architectural approach, that emphasizes the decomposition of applications into single-purpose, loosely coupled services managed by cross-functional teams, for delivering and maintaining complex software systems with the velocity and quality required by today’s digital business”
- 19. 19 What does that mean ? Application is composed of multiple services UNIX style – do one thing, and one thing well – in one process. Language agnostic API is important Organize teams around delivery of a service
- 20. 20 Microservices characteristics … 1. Deployment Independence - updates to an individual microservice have no negative impact to any other component of the system. Optimized for replacement 2. API Focused 3. Do one thing well - small enough and no smaller 4. Fit in your head 5. Decentralized Data Management
- 22. 22 Big Team, Big Effort, High Ceremony Deployment Code offers no value until it survives in production 24 Weeks Monolithic System Business Change Requests
- 24. 24
- 25. 25 Automated Testing Continuous Integration & Build Automation 24 Weeks 8 of 3 week sprints Monolithic System 12 Weeks Business Change Requests
- 26. 26 Linux Containers (e.g. docker) Automation via Orchestration (allows Devs to become DevOps) Infrastructure as Code 24 Weeks 8 of 3 week sprints Monolithic System 12 Weeks 9 Weeks Business Change Requests
- 27. 27 Continuous Delivery Pipeline 24 Weeks 8 of 3 week sprints Monolithic System 612 Weeks 9 Weeks Business Change Requests
- 28. 28 Zero-Downtime Deployment Strategies (Blue/Green, Canary) 24 Weeks 8 of 3 week sprints Monolithic System 6 312 Weeks 9 Weeks Business Change Requests
- 29. 29 24 Weeks 8 of 3 week sprints Monolithic System 6 3 1 112 Weeks 9 Weeks 1 Business Change Requests
- 30. 30 24 Weeks 8 of 3 week sprints Monolithic System 6 3 1 112 Weeks 9 Weeks 1 Deploying faster than 3-week sprint cycles? Patches to your application as well as your “stack” are also deployments. Business Change Requests
- 32. 32 #1 – Cleaner Code Well, less code to go wrong, but Its not going to magically fix poor engineers
- 33. 33 #2 – Its Easier Only doing one thing, so it should be easier - but The complexity still exists – its moved somewhere else – the platform
- 34. 34 #3 – Its Faster Easier to optimize an isolated service, but Network is always going to be slower than co-located code
- 35. 35 #5 – Better for Scalability Microservices are better for scalability, but Only if you carefully consider what should be architected as a Microservice in the first place
- 37. 37 Its fine to mix and match monoliths and Microservices Some things are better left untouched Choose carefully what to build as a Microservice Don’t do it yourself:
- 38. 38 Fabric8: Makes cloud stuff easy – and we are building an iPaaS too
- 39. 39
- 40. 40
- 41. 41
- 42. 42
- 43. 43 Microservices Platform – the Foundations • Runtime Registry • Logging • Security • Deployment • Scalability • Loosely coupled • Resilient • Temporal From the platform: The services:
- 44. 44
- 45. 45 iPaaS 2.0 Microservices Platform • Built on top of OpenShift • Provides additional services to generate, build and test integration services • Integration Services use Apache Camel: – deployed in Spring Boot – In a Docker Container
- 46. 46 iPaaS 2.0: Microservices Platform Citizen Developer iPaaS Console Expert Developer Can view what’s under the hood Administrator Can look at Infrastructure OpenShift Dedicated Component Catalog Integration Editor Funktion Editor Data Mapper Artifact Repository Git Repository Application Logging Application Metrics Tracing Project Wizards Code Quality Automated Testing Circuit Breaker Social API Management
- 47. 47 Agility: Integrated CI/CD • Continuous Deployment automatically, with jenkins pipelines for your integration services • Automated tests • Hooks for manual approval before production
- 48. 48 What Do we need from our Microservices Platform?
- 49. 49 Logging …
- 50. 50 Why Logging ? What a system is doing What happened A record of Actions and Outcomes
- 51. 51 Traditional Application Logging Logging strategies defined by the system Storage and routing defined by the system Write to local File Centralizing Custom configurator per system
- 52. 52 Container Logging Container standardize Management of your Processes So lets standardize Logging Logs to STDOUT & STDERR Captured by Execution Environment Routed by Execution Environment Containers are Ephemeral CENTRALIZE
- 53. 53 Contextual Logging Logs are for machines, not humans Context gives logs power Structured Logging
- 54. 54 Structured Logging Example { "STATUS": "200”, "REQUEST": "GET /apache_pb.gif HTTP/1.0”, "HOST": ”127.0.0.1”, "REFERER": http"REFERER": http://www.example.com/"REFE RER": http://www.example.com/start.ht ml, "USER": "frank”, "TIME": "10/Oct/2000:13:55:36 -0700”, "USERAGENT": "Mozilla/4.08 [en] (Win98; I ;Nav)“, "IDENTITY": "-”, "SIZE": "2326” } Context added by the logging process Machine Readable Filterable and Searchable
- 55. 55 CENTRALIZE
- 56. 56 Deployment is Easy RC and Service for ElasticSearch RC and Service for Kibana daemon set for fluentd Every Container’s Log is Centralized
- 57. 57
- 58. 58 Can we do the same for Metrics ?
- 59. 59 Why collect Metrics ? Logs tell you what’s happening Metrics measure behavior Measure improvement of change Adapt to runtime changes – e.g. auto-scaling
- 60. 60 Kubernetes Infra … Kublet Runs on each node Manages Pod and container lifecycle Key Elements: • Docker client • cAdvisor client • Etcd client • Docker client • Root directory master Node Node Node Node Node Node Pod Container Container Pod Container Container Kublet
- 61. 61 cAdvisor Daemon that collects, aggregates processes and exports information about containers Collects metrics for both system components and user containers
- 62. 62 Heapster One per cluster Aggregates all metrics exposed by cAdvisor Has Pluggable backend for persistent storage: • InfluxDB • Kafka • Hawkular etc. master Node Node Node Node Node Kublet Heapster
- 63. 63 Microservices Platform – Application Metrics • Historical metrics required for diagnosis,trends, and auto-scaling • Uses Prometheus for storage • Grafana for front end
- 64. 64 In Summary Logs tell you what’s happening Metrics measure how it happened Use Microservices to capture CENTRALIZE
- 65. 65 What about Tracing ??
- 66. 66 Why do Tracing? Latency optimization – where are the bottlenecks ? Root cause analysis Measure improvement of change Continuous Analysis for Continuous Improvement
- 67. 67 Open Tracing Vendor neutral Open APIs Support for Go, Python, Java and Javascript No lock in, easy to develop, easy to switch
- 68. 68 Microservices Platform – Tracing: Zipkin • Zipkin: distributed tracing framework: • Manages both the tracing and lookup of the data. • All routes for iPaaS use camel-zipkin to record incoming and outgoing Camel messages • OpenTracing
- 69. 69 Microservices Platform – Tracing: Zipkin Architecture
- 71. 71 Writing an Integration easily: Funktion
- 72. 72 Funktion Event driven lambda style Microservices, built on top of Kubernetes Polygot - supports Java, Node.js, Groovy, Kotlin, Go … Supports hundreds of trigger endpoint URLs Trigger endpoint defined in funktion.yml: rules: - trigger: http://0.0.0.0:8080 action: io.fabric8.funktion.sample.Main
- 73. 73 Funktion supports same URLs as Camel:
- 74. 74 Funktion rules: rules: name: foo - trigger: URL action: io.fabric8.funktion.sample.Producer::message chain: URL Optional code to call Optional Mandatory – the input Out – can have multiple of these
- 75. 75
- 76. 76
- 77. 77
- 78. 78 Funktion how it works:
- 79. 79 Funktion how it works: http:// Pod
- 80. 80 Funktion: part of the Fabric8 family Code: https Code: https://github.com/fabric8io/ Code: https://github.com/fabric8io/funktion Examples: in quickstarts: https://github.com/fabric8-Examples: in quickstarts: https://github.com/fabric8-quickstarts • funktion-java-example • funktion-nodejs-example • funktion-kotlin-example • funktion-nats-example • funktion-java-kafka-example
- 81. 81 iPaaS: A lot is happening under the hood …
- 82. 82 But … the user just sees this:
- 83. 83 iPaaS is being built on fabric8 and OpenShift
- 85. 85
- 86. 86 SERVICE CATALOG (LANGUAGE RUNTIMES, MIDDLEWARE, DATABASES, …) SELF-SERVICE APPLICATION LIFECYCLE MANAGEMENT (CI / CD) BUILD AUTOMATION DEPLOYMENT AUTOMATION CONTAINER CONTAINERCONTAINER CONTAINER CONTAINER NETWORKING SECURITYSTORAGE REGISTRY LOGS & METRICS CONTAINER ORCHESTRATION & CLUSTER MANAGEMENT (KUBERNETES) RED HAT ENTERPRISE LINUX CONTAINER RUNTIME & PACKAGING (DOCKER) ATOMIC HOST
- 87. 87 Single Sign On By RH SSO Integration Services By JBoss Fuse Intelligent Process Server By JBoss BPM Suite Real time Decision Service By JBoss BRMS In Memory Data Grid By JBoss Data Grid Messaging Services By JBoss A-MQ Java EE Application Server By JBoss EAP Tomcat By JBoss Web Server API ManagementData Services By JBoss Data Virtualization