Uploaded byMeysam Javadi
Microservices
This document discusses microservices architecture patterns and practices. It begins with an introduction and definitions of microservices. Key advantages of microservices include improved maintainability, testability, and scalability. The document covers topics such as decomposing monolithic applications into microservices based on business capabilities or domains, approaches to data management and communication between services, deployment requirements, and using Docker for deployment.
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Introduction to microservices: defining concepts, origin (2005, 2011), and significance in companies like Amazon and Netflix.
Defines microservices as small, independent services that enhance maintainability, testability, and autonomy, centered around business capabilities.
Comparison highlighting the decline of maintainability, complexity, and other -ilities in monolithic architecture over time.
Discusses advantages including improved maintainability, scalability, and technology independence.
Explores strategies for decomposing applications into microservices based on business capabilities, team structures, and domains.
Discusses database management strategies: private databases vs. shared databases, and the challenges of each.
Examines methods of communication between microservices, including point-to-point and publish/subscribe models.
Outlines key aspects for deploying microservices, such as language diversity, scaling, cost-effectiveness, and service isolation.
Introduction to Docker as a tool for simplifying the deployment and management of applications.
Defines core Docker components: images, containers, and the Docker engine, along with their roles.
Comparison of Docker containers and virtual machines, highlighting resource efficiency and deployment differences.
List of fundamental Docker commands for image management, container operations, and troubleshooting.
Describes the roles of developers and IT operations in the DevOps lifecycle of building, shipping, and running applications.
Various deployment patterns of microservices, discussing the benefits and drawbacks of each model.
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Microservices
- 1. Microservices Patterns & Practices By: Meysam Javadi SANAY
- 2. Objectives • Introduction andDefinitions • Monolithic vs. Microservices • Advantages • Decomposition • Data Management • Communication • Deployment • Docker
- 3. Intro. • “micro webservices" was first used by Dr. Peter Rogers during a conference on cloud computing in 2005 • Microservices used in different software architects events in 2011 • Adrian Cockcroft from Netflix called “fine grained SOA” • Amazon, Netflix and Uber
- 4. Definition 1 • isan approach to developing a single application as a suite of small services, each running in its own process and communicating with lightweight mechanisms, often an HTTP resource API.These services are built around business capabilities and independently deployable by fully automated deployment machinery.There is a bare minimum of centralized management of these services, which may be written in different programming languages and use different data storage technologies.
- 5. Definition 2 • Themicroservice architecture is an architectural style that structures an application as a set of services • Each microservice is: • • highly maintainable and testable • • loosely coupled • • independently deployable • • organized around business capabilities • • owned by a small team Chris Richardson
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- 7. Monolithic architecture: -ilitiesdecline over time • Size/Complexity • Maintainability • Testability • Deploy ability • Modularity • Evolvability Risk of Disruption Time
- 8. Advantages of Microservices •Shrinking Big problems and Small teams • Continuous Integration/Continuous delivery & Fast iteration • Improved maintainability • Better testability • Fault & Performance isolation • Technology independent • Scalability
- 9. Decomposition How to decomposean application into services? • Business capability • Stable architecture since the business capabilities are relatively stable • Development teams are cross-functional, autonomous, and organized around delivering business value rather than technical features • Services are cohesive and loosely coupled
- 10. Decomposition 2. • Domain-DrivenDesign (DDD) subdomains • How to identify the subdomains? Identifying subdomains and hence services requires an understanding of the business. Like business capabilities, subdomains are identified by analyzing the business and its organizational structure and identifying the different areas of expertise. Subdomains are best identified using an iterative process. Good starting points for identifying subdomains are: • organization structure - different groups within an organization might correspond to subdomains • high-level domain model - subdomains often have a key domain object
- 11. Decomposition 3. • Serviceper team • Enables each team to be autonomous and work with minimal coordination with other teams • Enables the teams to be loosely coupled • Achieves team autonomy and loose coupling with the minimum number of services • Improves code quality due to long term code ownership
- 12. Data management 1 Databaseper service • Private-tables-per-service • Schema-per-service • Database-server-per-service
- 13. Data management 2 SharedDatabase • One BIG Database! • Problems?
- 14. Communication • Point toPoint • Request/Response • One direction Request • Async Request/Response • One to Many • Pub/Sub • Publish/ async Responses
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- 16. Variation: Backends forfrontends
- 17. Deployment Requirements • Servicesare written using a variety of languages, frameworks, and framework versions • Each service consists of multiple service instances for throughput and availability • Building and deploying a service must be fast • Service must be deployed and scaled independently • Service instances need to be isolated • Resources consumed by a service must be constrained • Deployment must be cost-effective
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- 19. What Is Docker? •Lightweight, Simplify building, shipping, running apps • Runs natively on Linux orWindows Server • Standardized packaging for software and dependencies • Isolate apps from each other • Share the same OS kernel • Runs onWindows or Mac Development machines • Relies on "images" and "containers"
- 20. Some Docker vocabulary DockerImage The basis of a Docker container. Represents a full application Docker Container The standard unit in which the application service resides and executes Docker Engine Creates, ships and runs Docker containers deployable on a physical or virtual, host locally, in a datacenter or cloud service provider Registry Service (Docker Hub(Public) or Docker Trusted Registry(Private)) Cloud or server based storage and distribution service for your images
- 21. The Role ofImages and Containers Docker Image Example: Ubuntu with Node.js and Application Code Docker Container Created by using an image. Runs your application.
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- 23. Docker Containers vs.Virtual Machines A p p 1 A p p 2 Bins/Libs Bins/Libs Guest O S Guest O S Hypervisor Host Operating System A p p 1 Bins/Libs A p p 2 Bins/Libs Docker Engine Host Operating System Virtual Machines Docker Containers
- 24. Basic Docker Commands $docker image pull node:latest $ docker image ls $ docker container run –d –p 5000:5000 –-name node node:latest $ docker container ps $ docker container stop node(or <container id>) $ docker container rm node (or <container id>) $ docker image rmi (or <image id>) $ docker build –t node:2.0 . $ docker image push node:2.0 $ docker --help
- 25. Developers IT Operations BUILD DevelopmentEnvironments SHIP Create & Store Images RUN Deploy, Manage, Scale
- 26. Deployment Patterns • Multipleservice instances per host • Service instance per host • Service instance perVM • Service instance per Container • Serverless deployment • Service deployment platform
- 27. Deployment Patterns Multiple serviceinstances per host • Benefits • Efficient resource utilization • Fast deployment • Drawbacks • Poor/Terrible isolation • Difficult to limit resource utilization • Risk of dependency version conflicts • Poor encapsulation of implementation technology
- 28. Deployment Patterns Service perVMhost • Benefits • Great isolation • Great manageability • VM encapsulates implementation technology • Drawbacks • Less efficient resource utilization • Slow deployment
- 29. Deployment Patterns Service perContainer host • Benefits • Great isolation • Great manageability • Container encapsulates • implementation technology • Efficient resource utilization • Fast deployment • Drawbacks • Immature infrastructure for deploying containers
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