Systematic Migration of Monolith to Microservices
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MicroServices architecture style and its advantages over Monolith Application are known. I've tried to list down guidelines with respect to MicroServices when we want to split the Monolith.
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MongoDB can help you in this initiative by allowing you to centralize data management no matter how it is structured across channels and products and make it easy to aggregate data from multiple systems, while lowering TCO and delivering applications faster. MetLife publicly announced that they used MongoDB to enable a single view of the customer in 3 months across 70+ existing systems. We will explore case studies demonstrating these capabilities to help you industrialize your firm.
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Unique capabilities, brought to you by MongoDB
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Web-Services.pptx
The document discusses the evolution of integrating Microsoft Dynamics NAV with other systems. It describes the challenges of integration in the past which involved complex programming. The document then outlines how NAV 2009 web services simplify integration using industry standard approaches. It provides examples of consuming NAV web services from different technologies like .NET, JavaScript, and PHP. The key takeaways are that NAV is no longer isolated, web services provide simplicity using standard approaches, and integration possibilities are now limitless.
Modeling microservices using DDD
The document discusses modeling microservices using Domain-Driven Design (DDD) for a drone delivery domain. It covers DDD concepts like bounded context, tactical patterns, and identifies microservices from aggregates and domain services. It then models the drone delivery domain applying DDD, identifying bounded contexts, domain model, and refining them into microservices for the shipping bounded context.
When to Use MongoDB...and When You Should Not...
MongoDB is well-suited for applications that require:
- A flexible data model to handle diverse and changing data sets
- Strong performance on mixed workloads involving reads, writes, and updates
- Horizontal scalability to grow with increasing user needs and data volume
Some common use cases that leverage MongoDB's strengths include mobile apps, real-time analytics, content management, and IoT applications involving sensor data. However, MongoDB is less suited for tasks requiring full collection scans under load, high write availability, or joins across collections.
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In our new digital economy, keeping up can feel like a never-ending expansion of costly technical overhead. Each “trend” adds net-new operational and capital expenses to seemingly bloated run-rate measures - already challenged by leadership. Containers may feel like just another one of these trends, bringing its own additional expense. At MetLife, however, we sought to make containerization self-funding, allowing us to fuel change and tap into innovation at a large-scale. To do this, MetLife’s ModSquad, challenged established norms to prove that containers worked through production. Then, we asked Docker for help to modernize our traditional landscape to create funding sources to adopt containers, change holistically, and reduce overhead to our bottom line.
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About the event
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Systematic Migration of Monolith to Microservices
- 1. Systematic Migration of Monolith to Microservices Pradeep A. Dalvi
- 2. Monolith Application • Start out small • Add new features • Add new components • Until one day you realize…
- 3. Monolith Application • Conway’s Law • Complex codebase • Slow development process • Complex provisioning • Slow deployment
- 4. Why Microservices? • Agility and velocity of developing new features • Flexibility on required skillsets • Depend on technologies, platform and languages • Risk involved in upgrade • Rapid deployments • Scaling: Scale Out vs Scale Up • Licensing, Hardware cost, FaultTolerance
- 5. How to move to Microservices? • Big Bang rewrite? • Extremely risky - “The only thing a Big Bang rewrite guarantees is a Big Bang!” --Martin Fowler • Application Modernization • Split Monolith into small-small Microservices • Two weeks for rewriting • Two Pizza Rule by Jeff Bezos
- 6. Strategies • Authentication • IPC • Define Boundaries • Incremental Refactor • Database • Handling Partial Failures
- 7. Authentication • SSO • Distributed session • Client-sideTokens • Client-sideTokens with API Gateway
- 8. IPC • Synchronous • One-to-One (Request/Response) • Asynchronous • One-to-One (Notification or Request/Async Response) • One-to-Many (Publish/Subscribe or Publish/Async Responses) • Orchestration vs Choreography • Define IDL
- 9. Define Boundaries • Understand Business Capabilities • Identify Domains using Domain-Driven Design • Apply Single Responsibility Principle • Data Models review • Identify difficult parts
- 10. Incremental Refactor • New Development shall happen in Microservices • Split Frontend and Backend • Extract Services
- 11. New development in Microservices New Requests Old Requests API Gateway Monolith Service Glue
- 12. Split Frontend and Backend Browser Frontend Business Logic
- 13. Extract Services (Leaf) Catalog Reviews Catalog Reviews
- 14. Extract Services (Intermediate) Payment Order Shipping Payment Order Shipping
- 16. Database • Splitting DatabaseTables/Columns • Foreign Key Relationship • Shared Static Data • Shared Mutable Data • Transactional Boundaries
- 17. Splitting Database Order Shipping Order Shipping
- 18. Splitting Database Order Id User Products Shipping Order Id User Id Product Ids Shipping Id Order Id Shipping
- 19. Splitting Database - Staging Order Shipping Order Shipping Order Shipping
- 20. Foreign Key Product Id Order Id Product Id Product Catalog Order
- 21. Shared Static Data • Duplication • Static Data as Code or Config • Separate Service Catalog Shipping State Cities PIN Area
- 22. Shared Mutable Data Finance Shipping Customer Service
- 23. Transactional Boundaries • Single to SeparateTransactional Boundaries • Try again later • Abort entire operation • DistributedTransactions
- 24. Handling Partial Failures • Timeouts • Limit number of outstanding requests • Circuit Breaker • Provide Fallbacks
- 25. Microservices Chassis Framework • API Gateway • Service registry and Discovery • Circuit Breakers • IPC • Health Check • Metrics • Logging