Four Times Microservices: REST, Kubernetes, UI Integration, Aync

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Four times Microservices: REST, Kubernetes, UI Integration, Async Eberhard Wolff @ewolff http://ewolff.com Fellow

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http://continuous-delivery-buch.de/ http://continuous-delivery-book.com/

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http://microservices-buch.de/ http://microservices-book.com/

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http://microservices-book.com/ primer.html http://microservices-buch.de/ ueberblick.html FREE!!!!

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What are Microservices? > Modules providing interfaces > Processes, Containers, virtual machines

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What are Microservices? > Independent Continuous 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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Microservices = Extreme Decoupling

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Operational Complexity Extreme Decoupling

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Micro Service Micro Service Link Sync Async

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Synchronous REST Microservices

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Customer Order Catalog REST internal HTTP external

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Synchronous Microservices > Service Discovery: IP / port? > Load Balancing: Resilience and independent scaling > Routing: Route external request to microservices > Resilience

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Synchronous Microservices with Java, Spring Boot / Cloud & the Netflix Stack

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https://github.com/ ewolff/microservice

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Service Discovery Eureka

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Why Eureka for Service Discovery? > REST based service registry > Supports replication > Caches on the client > Resilient > Fast > Foundation for other services

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Eureka Client > @EnableDiscoveryClient: generic > @EnableEurekaClient: specific > Dependency on spring-cloud-starter-eureka > Automatically registers application

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Eureka Server @EnableEurekaServer @EnableAutoConfiguration public class EurekaApplication { public static void main(String[] args) { SpringApplication.run(EurekaApplication.class, args); } } Add dependency to spring-cloud-starter-eureka-server

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No content

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Load Balancing Ribbon

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Client Ribbon: Client Side Load Balancing > Decentralized Load Balancing > No bottle neck > Resilient Load Balancer Server

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Ribbon Example private LoadBalancerClient loadBalancer; … 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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Resilience

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Timeout > Do call in other thread pool > Won’t block request handler > Can implement timeout

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Circuit Breaker > Called system fails -> open > Open -> do not forward call > Forward calls after a time window

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Hystrix & Spring Cloud > Annotation based approach > Annotations of javanica libraries > Simplifies Hystrix > No commands

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@SpringBootApplication @EnableDiscoveryClient @EnableCircuitBreaker public class OrderApp { public static void main(String[] args) { SpringApplication.run(OrderApp.class, args); } } Enable Hystrix Need spring-cloud-starter-hystrix

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@HystrixCommand(fallbackMethod = "getItemsCache", commandProperties = { @HystrixProperty(name = "circuitBreaker.requestVolumeThreshold", value = "2") } ) public Collection findAll() { … this.itemsCache = pagedResources.getContent(); return itemsCache; } private Collection getItemsCache() { return itemsCache; } Fallback

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Zuul Routing

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Routing > One URL to the outside > Internal: Many Microservices > REST > Or HTML GUI > Hides internal structure (sort of) > Might add filters

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Customer Order Catalog Zuul Proxy Automatically maps route to server registered on Eureka i.e. /customer/** to CUSTOMER No configuration

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Netflix Stack > Service Discovery: Eureka > Load Balancing: Ribbon > Routing: Zuul > Resilience: Hystrix > Non-Java microservice: specific clients or sidecar

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Consul > Service Discovery by 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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https://github.com/ ewolff/microservice-consul

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Kubernetes

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https://github.com/ ewolff/microservice- kubernetes

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Kubernetes > Docker container on a single machine: Not resilient enough > Kubernetes: Run Docker container in cluster > …and much more!

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Pods > Kubernetes runs Pods > Pods = 1..n Docker containers > Shared volumes > …and ports

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Replica Sets > Deployment creates replica set > Replica sets ensure that a certain number of Pods run > ...for load balancing / fail over

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Services > Services ensure access to the Pods > DNS entry > Cluster-wide unique IP address for internal access > Node port … > … or external load balancer for external access

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Replica Set Pod Pod Service starts DNS Cluster IP address Load Balancer Deployment creates

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Load Balancer Kubernetes Cluster Server Service 1 Service 2 Kubernetes Cluster Server Service 1 Service 2 Service adds a load balancer Load Balancer (e.g. Amazon Elastic Load Balancer)

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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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No code dependencies on Kubernetes!

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UI Integration

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UI Integration > Very powerful > Often overlooked > UI should be part of a microservices > Self-contained System emphasize UI > http://scs-architecture.org/

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Hyperlinks to navigate between systems. System 1 System 2

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Transclusion of content served by another application System 1 System 2

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https://www.innoq.com/ en/blog/transclusion/

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UI Integration > Extremely decoupled > Here is a link: http://ewolff.com > No need to know anything else about the system > What about more complex transclusion?

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Server-side integration Browser UI 1 UI 2 Frontend Server Backend 1 Backend 2

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Server-side Integration: Technologies > ESI (Edge Side Include) > E.g. Varnish cache > SSI (Server Side Include) > E.g. Apache httpd, Nginx

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ESI (Edge Side Includes) ... ... Logged in as: Ada Lovelace ... ...

... a lot of static content and images ...

...

some dynamic content

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ESI (Edge Side Includes) ... ...

... a lot of static content and images ...

... http://www.w3.org/TR/esi-lang

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https://github.com/ ewolff/SCS-ESI

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Client-side integration Browser UI 1 UI 2 Backend 1 Backend 2

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Client-side Integration: Code $("a.embeddable").each(function(i, link) { $("

").load(link.href, function(data, status, xhr) { $(link).replaceWith(this); }); }); Replace with content of document in a

(jQuery)

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https://github.com/ ewolff/SCS-jQuery

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https://github.com/ ewolff/crimson- insurance-demo

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Asynchronous Microservices

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Asynchronous > Do not talk 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.

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Asynchronous: Benefits > Deals with unreliable systems > Can guarantee delivery > Good fit for events > …and Bounded Context / DDD

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Order Invoice Delivery

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Kafka

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https://github.com/ ewolff/microservice-kafka

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Kafka API > Producer API > Consumer API > Streams API (transformation)

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Kafka Records > Key > Value > Timestamp > No headers > Stored forever (!) Record Key Value Timestamp

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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

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Topic Partition Record Record Record Producer Offset Offset committed per consumer Offset Partition Record Record Record Partition Record Record Record

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Log Compaction > Remove all 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

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Kafka Replication > N Replicas (configurable) > In-sync replicas (configurable): write successful if all written

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Asynchronous Microservices > Service Discovery: via topic > Load Balancing: via partitions / consumer groups > Routing: ./. > Resilience service fails – latency increases

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Kafka Conclusion > Provides access 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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REST & ATOM

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https://github.com/ ewolff/microservice-atom

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Atom > Data format > …for feeds, blogs, podcasts etc > Access through HTTP > Idea: Provide a feeds of events / orders

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Order Big Money Inc. List of all orders https://github.com/ewolff/microservice- atom/order 2017-04-20T15:28:50Z ...

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Order 1 https://github.com/ewolff/microservice- atom/order/1 2017-04-20T15:27:58Z This is the order 1

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Atom Feed > Some unneeded information > …but not a lot > Mostly links to details > ...and timestamps > Can use content negotiation to provide different data formats or details

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Subscribing to Feed > Poll the feed (HTTP GET) > Client decides when to process new events > …but very inefficient > Lots of unchanged data

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HTTP Caching > Client GETs 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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REST can be asynchronous.

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Atom > Service Discovery: REST > Load Balancing: REST > Routing: ./. > Resilience failures just increase latency

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Atom Conclusion > Can provides access to old events if they are stored anyway. > One consumer: idempotency > No additional infrastructure

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Conclusion

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Operational Complexity Extreme Decoupling

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Conclusion: Communication > Netflix: Java focus, code dependencies > Kubernetes: No code dependencies > UI Integration: more decoupling > Asynchronous deals with challenges in distributed systems

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Links > List of microservices 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

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EMail bedcon2017@ewolff.com to get: Slides + Microservices Primer + Sample Microservices Book + Sample of Continuous Delivery Book Powered by Amazon Lambda & Microservices