What Is the Difference Between Availability, Maintainability, and Reliability?

We live in an era of reliability in which users rely on consistent access to services. There are no more essential features for users when choosing between competing services than reliability. But what does reliability mean?

To answer this question, we will decompose reliability according to other measures in reliability engineering: availability and maintainability. Distinguishing these terms is not a semantic issue. Understanding these differences can help you better prioritize your development efforts on customer satisfaction.

Availability

Availability is the most straightforward component of reliability. This metric describes the percentage of time the service is running, also known as the "uptime" of the service. Availability can be monitored by continuously querying the service and confirming the returned response with the expected speed and accuracy.

Service availability is the main factor of user-perceived reliability. With this in mind, it is tempting to set a goal of 100% uptime. But SRE tells us that failure is inevitable; Accidents leading to shutdown always occur beyond the expectation of the project. Availability is commonly represented by "9", which indicates how many decimals places the percentage of standard running time can reach. Some major software companies will boast about their "five nines" or 99.99% uptime, but there will never be a guaranteed 100% uptime.

In addition, users can tolerate or even fail to notice the downtime in some service areas. Development resources dedicated to improving the availability beyond expectations will not increase customer satisfaction. It will be better to use these resources for maintainability.

Maintainability

Another significant component of reliability is maintainability. By describing the generation and solution of downtime, maintainability factors are considered in availability. When an event leading to a shutdown occurs, the maintainable service can be repaired quickly. The sooner the event is resolved, the faster the service will be available again.

Maintainability has two main components: active maintainability and reactive maintainability.

Proactive maintainability includes building a codebase that is easy to understand and change. As the development goes on, there will be an incompatibility with the existing code. If engineers write spaghetti code instead of prioritizing maintainability, it is prone to problems and difficult to find and fix. Proactive maintenance also includes procedures such as quality assurance and testing.

Reactive maintainability describes the ability of a service to be repaired after an accident. This is affected by the incident response process of the service. The response and prevention of large-scale accidents are necessary. If the accident response procedure is reliable, the team will quickly solve the incident. Appropriate accident response also helps to reduce recurrence. Highly maintainable services allow engineers to learn these lessons effectively.

Maintainability is reflected in availability indicators. Reducing downtime or downtime frequency can improve availability. However, maintainability is not the only way to achieve availability. Such an approach could lead to the misallocation of development resources. Investments in maintainability may not immediately lead to better uptime. When you refactor old code to resolve technical debt, the service will function the same as before, with the same usability. You won't see this high maintainability benefit until something happens. Maintainability should be seen as an investment in reliability, not just a component of availability.

Reliability

Reliability can be defined as the likelihood that a service will perform as expected when a user accesses it. This seems to be the same way we define usability, but critical differences exist. Availability checks whether the service is working and whether users are accessing it. If users access services uniformly at all times and functions, availability will determine reliability. In general, this cannot happen.

Take two cases as examples:

Serve A：

• The availability of the user login page is 97%
• Directory search availability is 97%
• The availability of the site settings page is 97%

Serve B:

• The user login page has 99% availability
• Directory search availability is 98%
• The availability of the site settings page is 90%

In terms of availability measurement only, service wins. However, if the login page is used by 100% of users, the directory search is used by 90% of users, and the site setting page is used by only 30% of users, service B will be considered more reliable. Reliability needs to consider the actual use and convert the availability index into the measurement index of customer satisfaction.

By understanding the system's reliability, developers can avoid wasting time improving availability beyond customer expectations. Service level indicators bundle indicators such as delay and availability into more effective measures and then set the service level goal at the threshold of customer dissatisfaction. This approach sees reliability from the customer's perspective, as for them, the reliability of the service is more important than its availability.

This criterion can also assess maintainability. Time spent responding to incidents drains error budgets for service uptime...SLI and SLO can help allocate development efforts to improve maintainability and the incident response process that most affects customer satisfaction.

Reliability is more than a collection of metrics or the quality of a codebase. It's a global concept that encompasses the user's perspective, the inevitability of change and growth, and the people who develop the code. This holistic approach is the foundation of SRE, a collection of practices and a cultural curriculum that enhances service reliability.