Monolithic Nightmare: How a Monolithic App Hinders Development
Working for years developing on a monolithic architecture can cause one or more of the following consequences:
Low productivity: a monolithic application slows down the development of application services because the modules are tightly coupled, making parallel development difficult.
Security concerns: monolithic applications are often built on outdated frameworks.
Instability.
Long time to market.
Even minor changes require releasing the entire product.
Less suitable for use in CI/CD pipelines.
Tightly coupled application services.
Lower performance.
Low scalability.
Application framework not easily upgradable: migration involves an excessive amount of work with a high probability of compromising application functionality. The inability to update frameworks necessitates the use of obsolete and unmaintained libraries, posing further security risks.
Complexity.
Single point of failure.
Obsolescence of the technical knowledge of the working group.
As a result, the time comes to have a necessity to re-engineer the application architecture to adhere to the following principles:
The migration and refactoring should avoid creating another monolithic application.
The new architecture should utilize the latest market technologies.
The new architecture should be capable of being used within a CI/CD pipeline.
The new services should follow a modular architecture.
The new architecture should decouple the front end from the back end.
The new services should be designed to be scalable.
 |
| Classic monolitich architecture |
An architectural solution could be a containerized architecture, such as a microservices architecture. Here are some advantages of microservices:
Better productivity: Development teams can work on different services independently.
Faster time to market: Smaller, independent services can be developed and deployed more quickly.
Lower expenses: Optimized resource usage and reduced infrastructure costs.
Improved application stability: Fault isolation ensures that issues in one service don't affect others.
High scalability: Each service can be scaled independently based on demand.
High service availability: Redundancy and distributed deployment enhance availability.
Increased development efficiency: Continuous integration and deployment pipelines streamline development processes.
Faster fault recovery time: Individual services can be restarted without affecting the entire application.
Enhanced technology diversity: Different services can use different technologies best suited to their needs.
 |
| Faster time to market: Smaller, independent services can be developed and deployed more quickly. |
Thanks to the characteristics of microservices, the migration from a monolithic architecture to a microservices architecture could be done gradually (Strangler pattern). This approach involves introducing new microservices one at a time and incrementally adding new functionality to the application. Additionally, all functionalities should be enabled or disabled through specific on/off parameters, ensuring flexibility and control over feature deployment. This gradual migration minimizes risks and ensures a smoother transition from the monolithic system to the microservices architecture.
 |
| Thanks to the characteristics of microservices, the migration from a monolithic architecture to a microservices architecture could be done gradually (Strangler pattern). |
Microservice architecture is more suitable to work inside Continuous integration.
Continuous Delivery pipeline. CI/CD improves automation strategies and removes a lot of manual activities. Migrating from a monolithic architecture to a more modular architecture, such as microservices, can bring significant benefits, including improved scalability, maintainability, and deployment flexibility. However, it is also a complex and challenging process. Here’s a detailed guide on how to approach this migration:
1. Assess the Current State
Understand the Monolith: Analyze the current monolithic application to understand its structure, dependencies, and data flows. Document the different modules, their interactions, and critical components.
Identify Pain Points: Determine the limitations and issues with the current monolithic system, such as deployment difficulties, scalability issues, and maintenance challenges.
2. Define Objectives and Strategy
Set Clear Goals: Define the objectives of the migration. Common goals include improved scalability, faster deployment cycles, better fault isolation, and easier maintenance.
Choose a Migration Strategy: Decide on a migration strategy. Common approaches include the Strangler Fig pattern (incremental migration), a big bang approach (complete rewrite), or a combination of both.
3. Design the Target Architecture
Microservices Design: Design the new microservices architecture. Define service boundaries, data ownership, and communication patterns. Ensure services are loosely coupled and highly cohesive.
Technology Stack: Choose appropriate technologies for the microservices, such as languages, frameworks, databases, and messaging systems.
4. Plan the Migration
Prioritize Services: Identify and prioritize which parts of the monolith to migrate first. Often, it's beneficial to start with less critical services to gain experience and build confidence.
Develop a Roadmap: Create a detailed migration roadmap, outlining the steps, timelines, and milestones. Include a plan for continuous integration and continuous deployment (CI/CD) setup.
5. Implement the Migration
Incremental Refactoring: Start refactoring parts of the monolithic application into microservices. Use the Strangler Fig pattern to route requests to new services gradually.
APIs and Gateways: Develop APIs for the microservices and implement an API gateway to handle routing, authentication, and load balancing.
Data Management: Decide on data management strategies, such as database per service or shared databases. Implement data synchronization and migration scripts as needed.
6. Testing and Validation
Comprehensive Testing: Implement unit, integration, and end-to-end tests to ensure the new services function correctly and interact properly with existing components.
Performance Monitoring: Set up monitoring and logging for the microservices to track performance and identify issues early.
7. Deployment and Scaling
Automate Deployments: Use CI/CD pipelines to automate the build, test, and deployment processes. Tools like Jenkins, GitLab CI, or AWS CodePipeline can be useful.
Orchestration: Use container orchestration platforms like Kubernetes or Docker Swarm to manage and scale the microservices efficiently.
8. Training and Documentation
Documentation: Maintain comprehensive documentation for the new architecture, including service APIs, deployment processes, and operational guidelines.
Training: Provide training sessions for development and operations teams to familiarize them with the new architecture, tools, and processes.
9. Gradual Decommissioning of the Monolith
Service Cutover: Gradually cut over traffic from the monolith to the new microservices. Monitor performance and user feedback closely.
Legacy Code Removal: Once confident in the stability of the new services, begin decommissioning the corresponding parts of the monolithic application.
10. Continuous Improvement
Feedback Loop: Establish a feedback loop to continuously assess the performance and reliability of the microservices. Make iterative improvements based on feedback and monitoring data.
Scalability Enhancements: Continuously optimize and scale the services to handle increased load and demand.
 |
| Automation strategies should be at the core of a well-organized deployment pipeline. |
Automation Strategies
Automation strategies should be at the core of a well-organized deployment pipeline. Currently, the market offers a wide range of open-source tools that can be integrated into a deployment pipeline, from development to production release. Manual activities that could be automated are prone to errors and are a waste of time. Pipelines with many manual steps are slow and insecure. A good deployment pipeline should consist of a sequence of repeatable, automated operations to ensure efficiency, accuracy, and security.
A pipeline can be hosted in the cloud or on-premises and may rely on one or more of the following tools:
Continuous Integration Tools
Bamboo
Bitbucket Pipelines
Build Tools
Source Control Management
Containerization Tools
Google Kubernetes Engine (GKE)
Testing Tools
Code Quality and Security Analysis
Deployment Automation Tools
Google Cloud Deployment Manager
Monitoring and Logging Tools
Artifact Repositories
Nexus Repository
JFrog Artifactory
Google Artifact Registry
Notification and Collaboration Tools
Email Notifications (various providers)
HipChat (discontinued, migrated to Slack or similar tools)
Configuration Management Tools
Infrastructure as Code (IaC)
Serverless Deployment Tools
Google Cloud Functions
Orchestration Tools
Docker Swarm
Secret Management Tools
Google Secret Manager
These tools offer a comprehensive suite of capabilities to build, test, deploy, and monitor applications in a CI/CD pipeline.
Conclusion
Migrating from a monolithic to a microservices architecture is a significant undertaking that requires careful planning, execution, and monitoring. By following a structured approach and leveraging best practices, you can achieve a successful migration that results in a more agile, scalable, and maintainable system.
References
Join the Conversation
About Me
I am passionate about IT technologies. If you’re interested in learning more or staying updated with my latest articles, feel free to connect with me on:
Feel free to reach out through any of these platforms if you have any questions!
Comments
Post a Comment