Microservices: Breaking Apart the Monolith
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The document discusses the rise of microservices as a means to decouple processes from monolithic applications, highlighting their characteristics such as independence, scalability, and focus on specific business capabilities. It covers the complexities of building distributed systems, including reliable data transmission, event-driven patterns, and the importance of API gateways. The document concludes by emphasizing the need for effective monitoring and continuous deployment practices to ensure successful microservices architecture.
Microservices: Breaking Apart the Monolith
- 1. MICROSERVICES BREAKING APART THE MONOLITH www.iron.io
- 2. About the Presenter Ivan Dwyer | Business Development ● Joined Iron.io in early 2014 to collaborate with cloud ecosystem ● Founder of a Web 1.0 Startup in 1999 ● Helped build the first mobile app program at PalmSource ● Spent 10 years in international business with ACCESS @fortyfivan
- 3. Agenda ⬢ The Rise of Microservices in the Modern Cloud ⬢ How to Decouple Processes Into Discrete Microservices ⬢ Best Way to Keep Microservices and Connected Devices in Touch ⬢ Best Practices Around Event-Driven Asynchronous Processing ⬢ The Role of the API Gateway ⬢ How to Deal With State ⬢ DevOps & The Continuous Deployment Cycle ⬢ Bringing it All Together With Monitoring & Analytics
- 4. Evolution
- 5. How We Got Here Expensive to Scale Difficult to Scale Unnecessary Overhead Complex Configurations Granular Compute Effective Separation Monolith Multi-Tier / SOA Microservices
- 6. The Modern Cloud {} Cloud-Native Protocols RESTful APIs that communicate over HTTP with JSON serialization Agile Operations Consistent environments for development and deployment Elastic Workloads Granular workload-aware computing for effective scalability
- 7. Microservices represents the convergence of the modern cloud and modern application development.
- 9. Common Characteristics Single Responsibility Independent Loosely Coupled Stateless Asynchronous Interchangeable
- 10. Organizational Impact Technology Smaller services centered around specific capabilities Independently developed and deployed functional components Lightweight cloud-native communication and processing Multiple language and data sources fit for the service Business Focused and flexible workgroups Shorter release cycles Cost-effective scalable systems No vendor or framework lock-in
- 11. Considerations ➔ Building and maintaining highly available distributed systems is complex ➔ More moving parts means more components to keep track of and configure properly ➔ Loosely coupled services means steps must be taken to keep data consistent ➔ Distributed asynchronous processes create network latency and more API traffic ➔ Testing and monitoring individual services is challenging
- 12. Microservices are meant to make development and deployment better, but not necessarily easier.
- 13. Decoupling
- 14. Where to Start From Scratch Refactor New Features
- 15. Identify Candidate Components ➔ Outside of user response loop ➔ 3rd party service API calls ➔ Long running processes ➔ Transaction Processing ➔ Scale-out / burst processing ➔ Scheduled jobs Business Capability
- 16. Loosely coupled microservices centered around specific business capabilities lead to more flexible and agile workflows across your entire organization.
- 17. Communication
- 19. Queue all the Things ➔ Acknowledge data delivery ➔ Retry down endpoints ➔ Act as delivery buffer ➔ Keep data ordered properly POST -> GET -> DELETE
- 20. Problems with Dumb Pipes Down endpoints Overloaded endpoints
- 21. Message Queueing for the Modern Cloud Queue as a Service Cloud-Native Protocols Reliable Data Persistence Advanced Feature Set Detailed Monitoring Multiple Language Support
- 22. Leveraging a message queue ensures reliable data transmission across services and connected devices.
- 23. Compute
- 24. Event-Driven Asynchronous Patterns Webhooks Respond to events from external services to initiate a process Scheduled Jobs Cron-like processes that occur on a regular schedule. Streams Real-time activities through long running agent/daemon processes Fan Out Respond to events and push to multiple process/data endpoints
- 25. Compute Environment Load Balancer Traditional Hosting Model (Apps) Ephemeral Micro Computing (Tasks)
- 26. Distribute the Load A master service can orchestrate slave services to run concurrently to handle spikes in traffic or bursts Single responsibility microservices can scale more effectively and cut down total processing time Ex: Send 4000 emails 1-1000 1001-2000 2001-3000 3001-4000
- 27. Highly Scalable Asynchronous Task Processing Containerized Environment Event-Driven Flexible Scheduling Reliable and Secure Detailed Monitoring Multiple Language Support
- 28. This new pattern of event-driven asynchronous processing with the container as the unit of scale leads to more efficient and cost-effective systems.
- 29. API Gateway
- 30. Request Handling / Routing API Gateway Auth User Request REST
- 31. Considerations Keep it Light Focus on handling requests and routing to appropriate microservices Make it Highly Available Must be deployed in a fault-tolerant distributed manner Load Balanced Must be able to handle incoming traffic spikes elastically
- 32. The API Gateway provides the foundation for your entire architecture.
- 33. State
- 34. Connections, Payloads & Caching Deliver payload Secure DB connection In-process temp storage
- 35. Polyglot Persistence Key/Value Rapid access for reads/writes SQL Transactional data NoSQL High volume reads FIle Distributed file system
- 36. While preserving stateless microservices, choose the right data store and connection for the process.
- 37. Presentation
- 39. Considerations ➔ Route via the API gateway not directly from devices ➔ Fine-grained auth support may be needed in certain cases ➔ Balance inline processing vs out-of- process ➔ Pre-process for faster loading times ➔ Out-of-process for greater responsiveness ➔ Distribute processing but not necessarily core storage
- 40. Always remember that your users see your application as one unit regardless of architectural pattern.
- 41. Operations
- 42. Configuration Environments Dependencies Deployment Support for easier migration paths Consistent runtime from development to production Empowers independent teams and workflows Choose the right language for the specific microservice Limited scope of dependent services and libraries Scoped environment variables and runtimes Build, test, and deploy on a simpler scale Smaller services and teams means faster iterations Leverage a PaaS for automated deployment configuration
- 43. Continuous Delivery Code Test Deploy
- 45. Responsibilities Runtime Monitoring Audit trails Logging Error Handling Alerting Performance Testing
- 47. With microservices, monitoring and analytics must be done at both the individual level and as part of the whole application.
- 48. Conclusion
- 49. Full Microservices Stack API Infrastructure Compute Storage Networking Message Queue Scheduler Monitoring
- 50. How We Can Help Pair Programming Get a hands-on walkthrough of our platform Architecture Review Let us share some best practices and advice Start a Free Trial Start building with Iron.io in minutes
- 51. Iron.io 325 9th St San Francisco, CA 94103 1-888-939-4623 www.iron.io ivan@iron.io THANK YOU QUESTIONS?