Whether you’re building a simple web app or a large distributed system, users don’t just expect it to work → they want it to be fast, always available, secure, and to run smoothly without unexpected interruptions.
These expectations are captured in what we call system quality attributes or non-functional requirements.
In this article, we’ll explore the most critical attributes that any serious system should aim to deliver, especially in distributed environments. We’ll cover why each attribute matters for the users, how to measure it, and how to achieve it both proactively and reactively.
Reliability
Definition: Reliability is the ability of a system to operate correctly and continuously over time, delivering accurate results without unexpected interruptions or failures.
Why It Matters
Users rely on your system to behave predictably. If your banking app transfers money to the wrong account or your flight booking app glitches, it erodes customer trust instantly.
How to Measure:
- Mean Time Between Failures (MTBF): Average time system runs before failing.
- Error rate: Frequency of incorrect results (e.g., data corruption or logic bugs).
Proactive Techniques (making the system reliable in advance)
- Fault prevention (Stop mistakes before they happen) → Write clean code, perform code reviews, use static analysis tools.
- Fault removal (Find and fix mistakes early): Use automated testing, debugging, and formal verification.
Reactive Techniques (handling faults when they occur)
- Fault tolerance (Keep working despite faults) → Use retries, replication/redundancy, graceful degradation, and error correction.
- Fault detection (Spot problems quickly) → Monitor logs, set up alerts, use health checks and diagnostics.
- Fault recovery (Fix issues promptly) → Restart services, failover to backups, roll back to safe states.
Availability
Definition: Availability is the ability of a system to be up and responsive when needed, ensuring users can access it at any time. It focuses on being ready to serve, not on whether the response is correct (which is covered by reliability).
Why It Matters
If your system crashes or is down during peak hours, users will leave. For mission-critical systems like trading, even seconds of downtime can be disastrous.
How to Measure
- Uptime percentage → e.g., 99.9% uptime = ~8.7 hours of downtime/year.
- Mean Time to Recovery (MTTR): How fast you recover from failure.
- High availability (HA) typically refers to uptime of 99.9% or more, achieved through redundancy and failover strategies.
Proactive Techniques
- Capacity planning: Predict demand and provision enough resources.
- Redundant infrastructure: Extra hardware or cloud zones ready to take over.
Reactive Techniques
- Failover mechanisms: Automatically switch to backup nodes or servers.
- Auto-healing: Restart crashed services or containers automatically.
Scalability
Definition: Scalability is the ability of a system to handle more users or more data by adding more resources, without significantly slowing down or crashing.
Why It Matters
What works smoothly for 10 users might completely break when 10,000 people show up. If your product becomes popular, you want it to grow without falling apart.
How to Measure
- Throughput → How many requests per second your system can handle.
- Latency under load → How fast your system responds when many users are active at once.
Proactive Techniques (preparing for growth in advance)
- Design for scalability (Build with growth in mind) → Use stateless designs, modular components, and databases that can be partitioned or scaled out.
- Capacity planning (Plan ahead for future load) → Estimate how much traffic or data you’ll have later and make sure your system can handle it.
Reactive Techniques (handling growth when it happens)
- Auto-scaling (Add resources on the fly) → Automatically spin up more servers when traffic spikes.
- Load balancing (Distribute work evenly) → Spread incoming requests across multiple servers so no single one gets overloaded.
Maintainability
Definition: Maintainability is the ability of a system to be easily changed, updated, fixed, or improved over time without introducing new problems.
Why It Matters
Requirements always change. Bugs appear. New features need to be added. If your system is messy or overly complex, even small changes become risky and time-consuming. A maintainable system is easy to understand, modify, and operate day to day, letting teams respond quickly and confidently to new needs.
How to Measure
- Mean Time to Modify (MTTM) → How long it takes to make a change or add a new feature.
- Code churn → How frequently the code is updated or changed, which can indicate areas that are difficult to maintain or keep stable.
Proactive Techniques (making the system easier to change in advance)
- Modular design (Break it into manageable parts) → Structure your system as small, independent components that are easier to understand, test, and replace.
- Simplicity (Avoid unnecessary complexity) → Keep designs and code clear and straightforward to reduce errors and make it easier for new developers to pick up.
- Clear documentation and standards (Help everyone stay aligned) → Write understandable docs and follow consistent coding styles so others can safely make changes.
- Operability considerations (Design for smooth running in production) → Build clear configuration, easy deployment processes, and good monitoring hooks to simplify day-to-day management.
Reactive Techniques (improving it over time)
- Refactoring (Clean up continuously) → Regularly improve the structure of code without changing its behavior to keep it healthy and easy to work with.
- Automated regression tests (Prevent breaking existing features) → Run tests that ensure changes don’t accidentally introduce new bugs.
- Incremental improvements (Make small, safe changes) → Tackle technical debt gradually without big risky rewrites.
Security
Definition: Security is the ability of a system to protect itself from unauthorized access, misuse, or attacks.
Why It Matters
A single security breach can damage your reputation, leak sensitive data, or cause big financial losses. Attackers don’t wait for you to be ready → you have to plan ahead.
How to Measure
- Time to detect and respond → How quickly you can find and fix security issues.
- Number of vulnerabilities over time → Track how many security flaws are open and how quickly they’re closed.
- Compliance scores → Certifications like SOC2 or ISO 27001 that show your security practices meet industry standards.
Proactive Techniques (protecting the system in advance)
- Threat modeling (Think like an attacker) → Identify and fix weak points before someone exploits them.
- Secure defaults (Build security in by default) → Use encryption, strong passwords, and access controls.
- Security scans (Catch issues early) → Run automated tools to find known vulnerabilities in your code.
Reactive Techniques (responding when something goes wrong)
- Intrusion detection (Spot attacks fast) → Use systems that alert you to suspicious activity in real time.
- Incident response (Limit the damage) → Apply security patches quickly and have a plan to contain and fix breaches.
If you have any feedback on the content, suggestions for improving the organization, or topics you’d like to see covered next, feel free to share → I’d love to hear your thoughts!
Top comments (0)