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Uploaded byEberhard Wolff
Four Times Microservices - REST, Kubernetes, UI Integration, Async
The document discusses the architecture of microservices, focusing on concepts such as service discovery, load balancing, routing, and resilience using technologies like Eureka, Ribbon, and Hystrix. It also covers the integration of user interfaces, asynchronous communication, and the use of Kafka for event streaming. Additionally, it highlights the deployment of microservices in Kubernetes for improved scalability and reliability.
Four Times Microservices - REST, Kubernetes, UI Integration, Async
- 1. Four times Microservices: REST,Kubernetes, UI Integration, Async Eberhard Wolff @ewolff http://ewolff.com Fellow
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- 5. What are Microservices? > Modulesproviding interfaces > Processes, Containers, virtual machines
- 6. What are Microservices? > IndependentContinuous Delivery Pipeline including tests > Standardized Operations (configuration, log analysis, tracing, monitoring, deployment) > Resilient (compensate failure, crashes …) therefore separate processes, VM, Docker containers
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- 12. Synchronous Microservices > ServiceDiscovery: IP / port? > Load Balancing: Resilience and independent scaling > Routing: Route external request to microservices > Resilience
- 13. Synchronous Microservices with Java, SpringBoot / Cloud & the Netflix Stack
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- 16. Why Eureka forService Discovery? > REST based service registry > Supports replication > Caches on the client > Resilient > Fast > Foundation for other services
- 17. Eureka Client > @EnableDiscoveryClient: generic >@EnableEurekaClient: specific > Dependency on spring-cloud-starter-eureka > Automatically registers application
- 18. Eureka Server @EnableEurekaServer @EnableAutoConfiguration public classEurekaApplication { public static void main(String[] args) { SpringApplication.run(EurekaApplication.class, args); } } Add dependency to spring-cloud-starter-eureka-server
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- 21. Client Ribbon: Client Side LoadBalancing > Decentralized Load Balancing > No bottle neck > Resilient Load Balancer Server
- 22. Ribbon Example private LoadBalancerClientloadBalancer; … ServiceInstance instance = loadBalancer.choose("CATALOG"); String url = "http://" + instance.getHost() + ":” + instance.getPort() + "/catalog/"; Via Dependency Injection Eureka name Need dependency to spring-cloud-starter-ribbon
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- 24. Timeout > Do callin other thread pool > Won’t block request handler > Can implement timeout
- 25. Circuit Breaker > Calledsystem fails -> open > Open -> do not forward call > Forward calls after a time window
- 26. Hystrix & Spring Cloud >Annotation based approach > Annotations of javanica libraries > Simplifies Hystrix > No commands
- 27. @SpringBootApplication @EnableDiscoveryClient @EnableCircuitBreaker public class OrderApp{ public static void main(String[] args) { SpringApplication.run(OrderApp.class, args); } } Enable Hystrix Need spring-cloud-starter-hystrix
- 28. @HystrixCommand(fallbackMethod = "getItemsCache", commandProperties= { @HystrixProperty(name = "circuitBreaker.requestVolumeThreshold", value = "2") } ) public Collection<Item> findAll() { … this.itemsCache = pagedResources.getContent(); return itemsCache; } private Collection<Item> getItemsCache() { return itemsCache; } Fallback
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- 30. Routing > One URLto the outside > Internal: Many Microservices > REST > Or HTML GUI > Hides internal structure (sort of) > Might add filters
- 31. Customer Order Catalog Zuul Proxy Automaticallymaps route to server registered on Eureka i.e. /customer/** to CUSTOMER No configuration
- 32. Netflix Stack > ServiceDiscovery: Eureka > Load Balancing: Ribbon > Routing: Zuul > Resilience: Hystrix > Non-Java microservice: specific clients or sidecar
- 33. Consul > Service Discoveryby Hashicorp > DNS interface > Platform independent > Consul Template can fill out config file templates > e.g. for load balancer > …unaware of service discovery
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- 37. Kubernetes > Docker containeron a single machine: Not resilient enough > Kubernetes: Run Docker container in cluster > …and much more!
- 38. Pods > Kubernetes runsPods > Pods = 1..n Docker containers > Shared volumes > …and ports
- 39. Replica Sets > Deploymentcreates replica set > Replica sets ensure that a certain number of Pods run > ...for load balancing / fail over
- 40. Services > Services ensureaccess to the Pods > DNS entry > Cluster-wide unique IP address for internal access > Node port … > … or external load balancer for external access
- 41. Replica Set Pod Pod Service starts DNS Cluster IP address LoadBalancer Deployment creates
- 42. Load Balancer Kubernetes ClusterServer Service 1 Service 2 Kubernetes Cluster Server Service 1 Service 2Service adds a load balancer Load Balancer (e.g. Amazon Elastic Load Balancer)
- 43. Kubernetes > Service Discovery:DNS > Load Balancing: IP > Routing: Load Balancer or Node Port > Resilience: Hystrix? envoy proxy? > Can use any language
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- 46. UI Integration > Verypowerful > Often overlooked > UI should be part of a microservices > Self-contained System emphasize UI > http://scs-architecture.org/
- 47. Hyperlinks to navigatebetween systems. System 1 System 2
- 48. Transclusion of contentserved by another application System 1 System 2
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- 50. UI Integration > Extremelydecoupled > Here is a link: http://ewolff.com > No need to know anything else about the system > What about more complex transclusion?
- 51. Server-side integration Browser UI 1 UI2 Frontend Server Backend 1 Backend 2
- 52. Server-side Integration: Technologies > ESI(Edge Side Include) > E.g. Varnish cache > SSI (Server Side Include) > E.g. Apache httpd, Nginx
- 53. ESI (Edge SideIncludes) ... <header> ... Logged in as: Ada Lovelace ... </header> ... <div> ... a lot of static content and images ... </div> ... <div> some dynamic content </div>
- 54. ESI (Edge SideIncludes) ... <esi:include src="http://example.com/header" /> ... <div> ... a lot of static content and images ... </div> ... <esi:include src="http://example.com/dynamic" /> http://www.w3.org/TR/esi-lang
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- 56. Client-side integration Browser UI 1 UI2 Backend 1 Backend 2
- 57. Client-side Integration: Code $("a.embeddable").each(function(i, link){ $("<div />").load(link.href, function(data, status, xhr) { $(link).replaceWith(this); }); }); Replace <a href= " " class= "embeddable"> with content of document in a <div> (jQuery)
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- 61. Asynchronous > Do nottalk to other microservices > ...and wait for a reply > …while processing a request. > Either don‘t wait for a reply > ...or don‘t communicate while processing a request.
- 62. Asynchronous: Benefits > Dealswith unreliable systems > Can guarantee delivery > Good fit for events > …and Bounded Context / DDD
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- 66. Kafka API > ProducerAPI > Consumer API > Streams API (transformation)
- 67. Kafka Records > Key >Value > Timestamp > No headers > Stored forever (!) Record Key Value Timestamp
- 68. Kafka Topics > Named >Topics have partitions > Order guaranteed per partition > Consumer commits offset per partition > Consumer group: One consumer per partition Topic Partition Record Record Record
- 69. Topic Partition Record Record Record Producer Offset Offset committed perconsumer Offset Partition Record Record Record Partition Record Record Record
- 70. Log Compaction > Removeall but the latest record with a given key > Idea: Old events not relevant > …if new events override > Efficient storage in the long run Partition Record id=42 Record id=23 Record id=42
- 71. Kafka Replication > NReplicas (configurable) > In-sync replicas (configurable): write successful if all written
- 72. Asynchronous Microservices > Service Discovery: viatopic > Load Balancing: via partitions / consumer groups > Routing: ./. > Resilience service fails – latency increases
- 73. Kafka Conclusion > Providesaccess to old events > Guaranteed order per key > (Log compaction also per key) > Consumer groups send records to one consumer > Additional (complex) infrastructure
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- 76. Atom > Data format >…for feeds, blogs, podcasts etc > Access through HTTP > Idea: Provide a feeds of events / orders
- 77. <feed xmlns="http://www.w3.org/2005/Atom"> <title>Order</title> <link rel="self" href="http://localhost:8080/feed"/> <author><name>Big Money Inc.</name> </author> <subtitle>List of all orders</subtitle> <id>https://github.com/ewolff/microservice- atom/order</id> <updated>2017-04-20T15:28:50Z</updated> <entry> ... </entry> </feed>
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- 79. Atom Feed > Someunneeded information > …but not a lot > Mostly links to details > ...and timestamps > Can use content negotiation to provide different data formats or details
- 80. Subscribing to Feed >Poll the feed (HTTP GET) > Client decides when to process new events > …but very inefficient > Lots of unchanged data
- 81. HTTP Caching > ClientGETs feed > Server send data > + Last-Modified header > Client sends get > + If-Modified-Since header > Server: 304 (Not modified) > …or new data
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- 83. Atom > Service Discovery: REST >Load Balancing: REST > Routing: ./. > Resilience failures just increase latency
- 84. Atom Conclusion > Canprovides access to old events if they are stored anyway. > One consumer: idempotency > No additional infrastructure
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- 87. Conclusion: Communication > Netflix: Javafocus, code dependencies > Kubernetes: No code dependencies > UI Integration: more decoupling > Asynchronous deals with challenges in distributed systems
- 88. Links > List ofmicroservices demos (sync, async, UI): http://ewolff.com/microservices-demos.html > REST vs. Messaging for Microservices https://www.slideshare.net/ewolff/rest-vs- messaging-for-microservices
- 89. EMail bedcon2017@ewolff.com toget: Slides + Microservices Primer + Sample Microservices Book + Sample of Continuous Delivery Book Powered by Amazon Lambda & Microservices