Microservices Corporate Style
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The document discusses microservices architecture, contrasting it with monolithic architecture by outlining the benefits of using microservices, such as easier deployment, better scalability, and improved fault isolation. It also details the design principles, challenges, monitoring tools, and technology components necessary for implementing microservices successfully. Additionally, it emphasizes the need for efficient service discovery, management, and the role of open source technology in driving innovation in microservices.
![input {
tcp {
port => 9000 codec => "json"
}
}
output {
elasticsearch {
hosts => ["localhost:9200"] index =>
"micro-%{serviceName}"
}
}
logstash-simple.conf](https://image.slidesharecdn.com/microservices-180127110046/85/Microservices-Corporate-Style-57-320.jpg)
Microservices Corporate Style
- 2. Name: Narendranath Reddy Thota d3 Whitepaper Core Team Trainer from Gama Blockchain Full Stack Developer Technology Analyst Software Developer Technology Speaker MAERSK Email: narendranath.thota@ust-global.com P: +917288838869
- 8. Monolithic Architecture Load Balancer Monolithic App Account Component Catalog Component Recommendation Component Customer Service Component Database
- 9. MONOLITHIC APP (VARIOUS COMPONENTS LINKED TOGETHER) Comparing Monolithic to MicroServices
- 12. MicroServices – separate single purpose services
- 13. Microservices Architecture Load Balancer Account Service Catalog Service Recommendation Service Customer Service Service Catalog DB API Gateway Customer DB
- 15. • Micro service architecture (MSA) is an approach to building software systems that decomposes business domain models into smaller, consistent, bounded-contexts implemented by services. • Typically implemented and operated by small teams. • Switching from SOAP to REST doesn’t make a micro services architecture. • Micro services are not a technology-only discussion.
- 19. Design Principles for Monoliths: • DDD • SoC using MVC • High cohesion, low coupling • DRY • CoC • YAGNI Design Patterns for Micro services: o Aggregator Pattern o Proxy Pattern o Chained Pattern o Branch Pattern o Shared Resources o Async Messaging and etc ..
- 23. Disadvantages of Monolith: Difficult to deploy and maintain Obstacle to frequent deployments Dependency between unrelated features Makes it difficult to try out new technologies/framework Advantages of micro services: Easier to develop, understand, maintain • Starts faster than a monolith, speeds up deployments • Local change can be easily deployed, great enabler of CD • Each service can scale on X- and Z-axis • Improves fault isolation • Eliminates any long-term commitment to a technology stack • Freedom of choice of technology, tools, frameworks
- 24. Availability • A single missing “;” brought down the Netflix website for many hours (~2008)
- 25. MONOLITHIC APPS – FAILURE & AVAILABILITY
- 26. Introduction to some popular technology components, how they help solve some of the problems of developing and delivering software using a micro services architecture. Spring Boot (spring cloud – Eureka, ZUUL, Hystrix, Ribbon, etc) Docker Nodejs Kubernetes/Openshift NetflixOSS Kafka , Rabbit MQ, CloudAMQP, Kestrel etc.. Zipkin ELK stack Prometheus with Grafana AppDynamics Akana ForgeRock API Connect etc…
- 27. Monitoring: One of the most frequently mentioned challenges related to the creation of micro services-based architecture is monitoring. Each micro service should be run in an environment isolated from the other micro services so it does not share resources such as databases or log files with them. However, the essential requirement for micro services architecture is that it is relatively easy to access the call history, including the ability to look through the request propagation between multiple micro services. Grepping the logs is not the right solution for that problem. There are some helpful tools that can be used when creating micro services with Spring Boot and Spring Cloud frameworks. Zipkin. A distributed tracing system that helps gather timing data for every request propagated between independent services. It has simple management console where we can find a visualization of the time statistics generated by subsequent services.
- 28. ELK. Elasticsearch, Logstash, and Kibana — three different tools usually used together. They are used for searching, analyzing, and visualizing log data in real-time. Distributed, independent micro services and centralized log monitoring make for the right solution. With tools like ELK and Zipkin, microservices monitoring seems to not be a very difficult problem to solve. There are also some other tools — for example, Hystrix and Turbine Prometheus with Grafana and etc.. — that provide real-time metrics for the requests processed by micro services.
- 29. Some Tools for Service Registry/Discovery: Zookeeper and Curator • Kubernetes • etcd • Consul • OSGi • Snoop NoOps: Service replication (Kubernetes) Dependency resolution (Nexus) Failover (Circuit Breaker) Resiliency (Circuit Breaker) Service monitoring, alerts and events (ELK)
- 30. Open Source Commoditization of Technology Open source is leading the charge in the technology space. This drives communities to build things like operating systems (Linux), programming languages (Go), message queues (Apache ActiveMQ), and web servers (httpd). As open source and open ecosystems have become the norm, we’re starting to see a lot of innovation in software technology coming directly from open source communities (e.g., Apache Spark, Docker, and Kubernetes, ELK Stack, Zipkin).
- 32. CHALLENGES Can lead to chaos if not designed right …
- 33. CHALLENGES Requires thinking differently about how to build, deploy and operate them. Design for Faults Building distributed systems is different from building shared memory, single process, monolithic applications. Networks are inherently unreliable. Latent network calls can be very difficult to debug. Design with Dependencies in Mind Need loose coupling in our teams, in our technology, and our governance.
- 34. SERVICE DISCOVERY • 100s of MicroServices • Need a Service Metadata Registry (Discovery Service) Account Service Catalog Service Recommendation Service Customer Service Service X Service Y Service Z Service Registry Service (e.g. Netflix Eureka)
- 35. CHATTINESS (AND FAN OUT) ~2 Billion Requests per day on Edge Service Results in ~20 Billion Fan out requests in ~100 MicroServices 1 Request 1 Request Monolithic App MicroServices
- 37. Best Practice -> Loadbalancers Choice 1. Central Loadbalancer? OR 2. Client based Loadbalancer?
- 38. Central (Proxy) Loadbalancer Account Service Load Balancer Account Service 1 Recommendation Service 1 Customer Service Service 1 API Gateway Account Service N Recommendation Service N Customer Service Service N Customer Service Load Balancer Reco Service Load Balancer
- 39. Client Loadbalancer Account Service 1 Recommendation Service 1 Customer Service Service 1 API Gateway Account Service N Recommendation Service N Customer Service Service N Account Service LB Recommendation Service LB Customer Service Service LB
- 40. Client based Smart Loadbalancer Use Ribbon (http://github.com/netflix/ribbon)
- 41. Homogeneity in A Polyglot Ecosystem
- 42. Message Queue
- 50. NetflixOSS
- 57. input { tcp { port => 9000 codec => "json" } } output { elasticsearch { hosts => ["localhost:9200"] index => "micro-%{serviceName}" } } logstash-simple.conf
- 61. Thank You
Editor's Notes
- #34: In complex systems, things fail. Hard drives crash, network cables get unplugged, we do maintenance on the live database instead of the backups, and VMs disappear. Single faults can be propagated to other parts of the system and result in cascading failures that take an entire system down. Design with dependencies in mind: This means being able to change things as quickly as the business needs without impacting those services around you or the system at large.
- #51: Netflix OSS: Netflix are pioneers in Microservices architecture. They were the first to successfully implement microservice architecture on a large scale. They contributed immensely to Microservices by open sourcing most of their microservice tools with Netflix Open Source Software Center. Spring took the opportunity to integrate many NetflixOSS projects such as Zuul, Ribbon, Hysterix, Eureka and Turbine.