Priciples of Scalable System Design

Designing a scalable system is a challenging yet rewarding task in today's rapidly evolving world. It requires careful consideration and analysis of numerous key factors, especially when preparing for growth. Balancing performance, reliability, and scalability is crucial to ensure the system can seamlessly handle increasing demand and adapt to changes.

Here are some essential principles included.

• Modularity
• Decoupling
• Statelessness
• Load Balancing
• Caching
• Async Processing
• Monitoring and Observability
• Redundancy and Failover
• Security
• Data Consistency and Integrity
• Continuous Deployment and Integration (CI/CD)

Let’s learn those principles step by step.

Modularity

Modularity involves breaking the system into smaller and manageable chunks. Like for example in the eCommerce domain, you can break the system into different chunks like.

1. Catalog Module
2. Orders Module
3. Products Module
4. Identity Module

By doing this you will achieve modularity in your design and help you manage and scale independently.

Decoupling

Minimize the coupling between modules as much as possible and allow them to grow individually. Decoupling involves several techniques like using a messaging system to communicate between modules.

Different techniques

1. Messaging Queues
2. Pub-Sub pattern

Statelessness

Statelessness means your requests should not store the session information between them. It enhances the fault-tolerance since the fault occurs in one instance or one request will not affect others.

Load Balancing

It’s the technique of dividing the traffic between different instances to give them a chance to avoid bottlenecks. Mean a single server or instance will not manage the whole traffic.

We can divide the traffic based on,

1. Round-Robin Algorithm
   • Distribute requests sequentially among servers.
2. Least Connection
3. IP-based distribution among requests.

Caching

Caching is the technique of storing frequently accessed data in the main memory or distributed environment stored in a Radi’s cache. The purpose of using a cache is to reduce the load on the database server.

Types of cache

1. In-Memory Cache (storing in the main memory).
2. Distributed Cache like (Redis and Memcached).
3. CDN for (Static Content).

Asynchronous Processing

Offload the time-consuming tasks to background jobs. Allow the system to only handle concurrent requests. Like updating the statuses of a particular entity or sending emails etc.

Several ways

1. Tasks queues
2. Workers Process.
3. In the .NET eco-system, you can utilize (Quartz, Hangfire, .NET Hosted services).

Monitoring and Observability

This is a very crucial part of the scalable system that will allow you to monitor and observe your system state or health checks. It will help to analyze the load, stack trace debug the system and take considerable steps to improve the system's performance.

Several tools to implement this,

1. Prometheus.
2. Grafana.
3. ELK stack

Redundancy and Failover

The system can continue to operate if the failure of some components. A system should fail gracefully, which means if one thing is not working, then other modules should not be affected by this downtime.

Several methods or techniques can be considered.

1. Use redundant servers.
2. Data replication.
3. Automated failover mechanisms (In .NET, Polly lib is an excellent choice).

Security

As the name suggests, the gate of the system should be secured. Take security measures at each layer of the architecture.

1. Use encryption and decryption.
2. Authentication and Authorization (e.g. Token system).
3. Applying software updates or bug fixing that can cause the system to crash.
4. Security patches (finding vulnerabilities).

Data Consistency and Integrity

Making sure that data is consistent and available for every part of the system, especially in a distributed environment.

1. Use ACID (Atomicity, Consistency, Isolation, Durability) principle.

Continuous Deployment and Integration (CI/CD)

Automate the process of deploying and testing. Changes (new features or fixes) should quickly be tested and deployed.

Several tools can be used to implement CI/CD.

1. Bitbucket pipelines.
2. Azure DevOps pipelines.
3. Jenkins.
4. GitLab CI.
5. Sonar-Qube code quality control.

Conclusion

We have discussed several principles that are essential for each system to be scaled and perform nicely. Developing a scalable system will help you focus on the key areas of your system.

Thanks for reading, will see you in the next, Bye!