Have you ever wondered how big tech companies run their many services without crashing?
The answer? Distributed systems.
These are groups of independent computers that can grow when needed and keep everything working smoothly.
Think of it as having a team of computers instead of relying on just one powerful machine. However, while they seem like a great solution, distributed systems have their own challenges.
In this article, we’ll explore how distributed systems work, why they’re so powerful, and how you can leverage them to build an infrastructure that keeps your business running.
Why Distributed Systems?
Among modern computing platforms, distributed systems stand out—and for good reason. Their extensive benefits allow businesses to tackle complex operations while maintaining optimal efficiency, flexibility, and cost-effectiveness.
Scalability
Distributed systems excel in scalability. As demand grows, you can easily add more computing units without overhauling your entire setup. For example, during peak shopping seasons, e-commerce sites can quickly deploy extra servers, ensuring a smooth user experience.
Availability
Availability is another key benefit. If one unit fails, the rest continue functioning, ensuring your service remains operational. This fault tolerance is crucial for high-availability services like financial platforms and streaming services. For instance, if a Netflix server goes down, millions can still watch their favorite shows with minimal interruption.
Performance and Cost Optimization
Distributed systems optimize performance and costs. Instead of investing in a single supercomputer, you can use multiple, more affordable units. This allows businesses to scale efficiently. A startup can begin with a small system and expand as needed, improving performance while keeping costs low.
Consistency
Consistency ensures that data stays synchronized across all units. Depending on the application, different levels of consistency can be chosen to suit specific needs. This setup allows for the easy addition of units during increased demand without major infrastructure changes.
When demand increases, you can easily add more units without needing to replace the entire infrastructure. Plus, if one component goes down, the others continue running smoothly.
Failures: They Happen, But You Can Plan for Them
Failures in distributed systems are inevitable, whether due to network issues or software bugs. The real challenge lies in keeping the system running smoothly when things go wrong.
Failures can be subtle—sometimes, they only show up under specific conditions. Other times, a minor error causes a domino effect. Proactive testing is the solution.
Let’s discuss three strategies that will help you identify and mitigate potential system failures.
Image: Freepik
Strategy 1: Formal Verification
Think of Formal Verification as a magnifying glass. It rigorously tests your system’s design to ensure it performs as expected, even when confronted with rare, tricky bugs. Formal Verification tools allow system designers to define the distributed system model and use verification tools to uncover elusive error cases.
First, formal verification requires designers to precisely define the distributed system model so that it can be verified. This includes specifying both the correctness and liveness properties of the system. The tool then systematically explores the system’s behavior by injecting failures and checking whether the model satisfies the desired specifications in all possible states. If it identifies any path where the system fails to meet these correctness or liveness conditions, it flags that path for designers to address and resolve.
With tools like TLA+ and P, engineers can specify the exact conditions for system behavior and simulate potential failures. This method isn’t just about finding obvious bugs—it uncovers the subtle, rare ones that can cause the biggest headaches.
For example, when designing a distributed payment system, formal verification tests that transactions will process correctly under specified conditions, even during network disruptions.
Actionable Step: If you’re building a system that handles critical data (think financial or healthcare applications), integrate formal verification early in your design process to catch bugs that traditional testing might miss.
Strategy 2: Chaos Testing
Imagine testing a skyscraper by simulating earthquakes instead of waiting for one to hit. That’s what Chaos Testing does for distributed systems. It deliberately injects failures to see how the system recovers.
Examples of failure injections include:
- Terminating nodes
- Restarting nodes
- Simulating an availability zone outage
- Causing network dependency failures
- Exhausting node resources
Distributed systems face complex interactions that can hide latent bugs. Failures like untested failover paths or dependency retry storms can cause significant disruptions and take systems offline for extended periods. By uncovering these issues in a controlled way, Chaos Testing helps prevent major outages.
Actionable Step: Start small. Disable a few nodes or simulate a minor network failure to test your system’s resilience. Gradually increase the complexity as your confidence grows.
Strategy 3: Fuzz Testing
Fuzz Testing injects invalid or unexpected inputs into your system to uncover hidden bugs. Feeding your program malformed data reveals vulnerabilities like crashes or data leaks that typical tests might miss.
For example, fuzzing a messaging platform might expose certain message formats and crash the system. Unlike Chaos Testing, which tests system-wide failures, fuzzing targets individual components and how they handle random inputs.
Tools like AFL and LibFuzzer make fuzz testing easy to integrate. They mutate known inputs to test different scenarios, helping ensure your system can handle unpredictable inputs without breaking.
Actionable Step: Use AFL or LibFuzzer to start fuzz testing your software, catching bugs early and preventing real-world failures.
Making It All Work: Putting Theory into Practice
Developing distributed systems is challenging, but with a commitment to implementing the right strategies, it becomes feasible to design infrastructures that are infinitely scalable, recover quickly from issues, and maintain consistency. Given the critical role these systems play in modern computing, mastering their complexities enhances competitiveness.
Key techniques include Formal Verification to simulate potential issues, Chaos Testing to ensure resilience under stress, and Fuzz Testing to uncover hidden vulnerabilities. Each approach strengthens your system’s ability to perform under real-world conditions.
Ultimately, success in distributed systems comes from proactive planning and ongoing testing. With careful design and continuous improvement, you can build systems that not only work but thrive under pressure.
