In today’s data-driven world, information is gold, and the systems that store and manage it serve as crucial infrastructure. I have seen people talk a lot about terms like “distributed computing”, “scalability”… but one fundamental characteristic is often overlooked: reliability. Without it, scalability, maintainability, flexibility, anything-bility are meaningless, like a beautiful castle built on sand.
What is Reliability?
Everyone has their own intuition about what is reliable:
- A piggy bank is reliable because it consistently holds your money and accurately reflects what you’ve deposited. You trust that when you put a coin in, it will be there later, and the total will reflect your savings. And when you want to make a withdrawal, you can get your money immediately.
- A calculator is reliable because it consistently produces accurate results based on your input. You trust that regardless of who uses it, 2 + 2 will always equal 4. And the result should appear instantly on the screen.
Different systems have different reliability requirements. In general, we can define reliability as follow:
Reliability refers to the ability to always do the expected things in the expected way.
For software, reliability means consistently performing the designed function at the expected level of performance. Consider a calculator: we expect it to immediately display 4 after typing in 2+2. If it shows me 5, I will give it 1 star and never use it again. If it takes me 5 minutes to do such a simple arithmetic addition, I will send an email to the United Nations to report it as crypto-mining malware. (actually I won’t)
Wait a minute! There is one more important word in my definition above: “always”. What do I mean by “always”? A piggy bank wouldn’t be very reliable if it held my money and suddenly became inaccessible for a week. Of course, there is no perfect “always” in real world. There may be unforeseen situations that cause systems to stop working. But systems should be designed in such a way that the disruption doesn’t hurt business operations. Reliability focuses on minimizing the occurrence of system failures and their impact on functionality.
Reliable Data system
Just like you trust your piggy bank to hold your coins securely, you need to trust your data systems to hold your information reliably. Your piggy bank wouldn’t be very reliable if the coins sometimes disappeared, a data system wouldn’t be reliable if the information kept changing or disappearing. Reliability means you can trust the information it holds. This means the data is always available, accurate, and delivers consistent results when you need it. Common expectations for a data system:
- Integrity: This ensures the data is accurate, complete, and consistent. Imagine your piggy bank if someone took coins without putting them back, or if different amounts appeared out of nowhere. It wouldn’t be reliable! Similarly, data integrity prevents missing, incorrect, or inconsistent information, thereby ensuring its reliability.
- Availability: You wouldn’t find your piggy bank locked when you need it most. Likewise, reliable data systems must be accessible when you need them. This means the data is readily available for authorized users, minimizing downtime and ensuring critical information is always at hand.
- Performance: A sluggish piggy bank wouldn’t be very useful. Similar to how you expect quick access to your coins, data systems should deliver reasonable performance. This translates to fast retrieval times, smooth operation, and responsiveness to your needs, enabling efficient decision-making.
- Timeliness: Data freshness is crucial. Old coins are worth the same, but old data is not. In data systems, timeliness ensures that information is current and up to date. This reduces reliance on outdated data, resulting in more accurate insights and informed actions.
- Safety: Just like keeping your piggy bank safe from theft, protecting your data is critical. Data safety ensures that information is protected from unauthorized access. If someone you don’t trust knows where you keep your piggy bank, you won’t put any coins in it.
How important is Reliability
Reliability is not limited to life-or-death situations such as nuclear power plants. It is fundamental to all software applications, large and small. Sure, bugs in a note taking app may not have catastrophic consequences, but they do cause frustration and erode user trust. Let’s shift our focus from “avoiding disaster” to “delivering value”. Every software application has a purpose, whether it’s to simplify tasks, improve communication, or entertain users. When an application crashes, malfunctions, or produces incorrect results, it fails to fulfill its purpose. Every software application has a responsibility to its users. Frustrated users abandon unreliable applications, businesses lose productivity, and trust erodes. Investing in reliability is about more than avoiding the negative consequences of failure. It’s about building trust, delivering value, and ensuring that your software does what it’s supposed to do.