Reliability vs availability: Understanding the differences

What is system reliability?

Reliability is the probability that a system or component consistently performs its intended function without failure over a specified period. Teams must understand how to measure and ensure reliability to make informed decisions about system performance and enhance customer satisfaction. 

For instance, payroll systems must reliably process direct deposits within a set timeframe each month, while cold storage systems must detect power outages and switch to backup generators without fail. Across industries, maintaining reliability in automated processes and tracking performance through incident management KPIs is crucial, as failures can lead to significant financial repercussions.

Definition of reliability

Reliability is the probability that a system or component will perform its intended function without failure under specified conditions for a given period. It measures a system’s or component’s ability to maintain functionality and performance despite faults or failures. 

Reliability is critical to system design and maintenance, as it directly impacts a system's overall performance, safety, and cost-effectiveness. High reliability means the system or component will operate correctly and consistently, which is essential for maintaining customer confidence and operational efficiency.

How to measure and calculate failure rates for reliability

You can measure reliability with standard incident management metrics, such as:

• Mean time between failures: Calculate MTBF by dividing the total operation time by the number of failures. This metric is crucial for understanding the average time duration between failures.

• Failure rate: Calculate failure rates by dividing the number of failures by the total time in service. Handbooks like MIL-HNDBK-217 can lead to inaccuracies due to the assumption of a constant failure rate, which may result in misleading predictions about component reliability, especially as components age.

It’s important to consider additional factors, such as service level agreements and what customers expect from the system. Reliability standards can vary based on what’s at risk if a system fails. For example, will failure cause a group of tax preparers to take the afternoon off? Or will it strand thousands of airline passengers far from their homes?

Reliability calculations

Reliability calculations use mathematical models and statistical techniques to estimate a system's or component's reliability. They typically use failure rates, mean time between failures (MTBF), and other reliability metrics to determine system or component failure probability. 

By analyzing these metrics, businesses can identify potential weaknesses and areas for improvement. Reliability calculations can be performed using various methods, including fault tree analysis, reliability block diagrams, and Markov modeling. These techniques help visualize and quantify complex systems' reliability, enabling decision-makers to make informed choices about design, maintenance, and resource allocation.

Mean Time to Failure (MTTF) and Mean Time Between Failures (MTBF)

Mean Time to Failure (MTTF) is the average time a system or component takes to fail, while Mean Time Between Failures (MTBF) is the average time between failures. MTTF is typically used for non-repairable systems, while MTBF is used for repairable systems. Both metrics are important for reliability calculations, as they provide insight into the frequency and likelihood of system or component failures. 

By understanding these metrics, businesses can better predict maintenance needs, plan for replacements, and improve overall system reliability. Calculating MTTF and MTBF involves collecting data on failure events and using statistical methods to compute the average time to failure and between failures, respectively.

How to improve reliability

There are a few steps businesses can take to improve service reliability:

• Create routine maintenance schedules to keep systems up-to-date and modernized.
• Implement system redundancy to prevent component failures from halting processes.
• Complete quality control and testing when upgrading or making system changes so teams can correct issues before they reach production.
• To understand system reliability and performance, utilize comprehensive data collection and analysis methods on a large scale.

• Improve incident communication to decrease response and recovery time.

What is availability?

Availability is the percentage of time that a system or component is operational and can perform its function—its up-time.

Large online retailers, for example, must maintain site availability 24/7 to meet customer demand or risk losing market share to competitors. Availability takes into account a variety of conditions, such as user internet speeds and peak traffic times.

Definition of availability

Availability is the probability that a system or component is operational and available at a given time. It is a measure of the ability of a system or component to perform its intended function when needed. 

Availability is often calculated using the formula: Availability = (MTBF / (MTBF + MTTR)), where MTTR is the mean time to repair. This formula clearly explains how often a system is expected to be operational and ready for use. High availability is crucial for systems that require continuous operation, such as online services and critical infrastructure. By focusing on MTBF and MTTR, businesses can improve their systems’ availability and meet user expectations.

How to measure availability

Measuring availability is a single percentage metric. It is the total elapsed time minus the total downtime divided by the total elapsed time:

availability percentage = (total elapsed time – downtime) / total elapsed time

For example, if an online retail site is down for three hours in a day due to traffic overload, its availability score is 87.5%. The standard may be closer to 99.5% for large international retailers, giving the online retailer much to improve.

ITSM software such as Jira Service Management helps teams track incidents and collect data for measuring availability.

How to improve availability

There are several ways companies can improve availability:

• Implement proactive, standard maintenance schedules to ensure high availability.
• Add system redundancy with failover mechanisms.

• Create rapid repair processes as part of incident management.

Proactive maintenance, in particular, can help businesses gain greater availability and service reliability. Conducting a reliability, availability, and maintainability (RAM) study can provide important insights into where to focus maintenance efforts.  

Reliability vs. availability

Reliability and availability are often mistaken for the same thing. However, they not only differ but also don't always align.

Even the standards by which companies measure them can differ, depending on the system and its function. To gain an accurate view of any business system, you should analyze reliability vs. availability metrics separately.

• Reliability measures whether the system has delivered the correct output at a specific, defined time—e.g., transferring payroll funds to the correct accounts on the right day. 
• Availability measures the system’s up-time—for example, providing uninterrupted oxygen monitoring to premature babies during their necessary incubation period.

Jira Service Management includes automation templates that collect data, elevate incident communication, and improve overall customer service.

Differences

Reliability vs. availability metrics and their differences become more apparent when considering how to use them to improve performance. Reliability aims to minimize system failures and downtime, while availability aims to maximize operational time.

Measuring the service reliability of a grocery self-checkout system may involve analyzing how often customers require clerk assistance to complete a transaction. Measuring availability may involve checking whether customers attempt self-checkout at all.

Similarities

Reliability and availability complement each other. Competitive businesses strive to improve both metrics for the best results. For example, systems with high availability but frequent reliability failures are unlikely to serve customer needs no matter how quickly they resolve them.

Improving both areas often requires similar approaches, such as performing routine maintenance, adding redundancy, contingency planning, and testing.

Factors affecting reliability and availability

Several factors can affect system reliability and availability:

• Environmental: This can include IoT components, such as pressure gauges with exposure to inclement weather, or cyclical user patterns, such as high retail site traffic on specific days. Mean and standard deviation are applied to various parameters to assess the probability of failure and enhance safety factor methodologies.
• Component quality: Examples include third-party integrations or hardware. The importance of standard deviation in understanding the variability of calculation outcomes and the probability of failure in structural analyses cannot be overstated.

• Operational: This may include the frequency of inspections and maintenance or investment in modernized software.

Businesses can improve overall service reliability and availability by standardizing environmental thresholds and adding redundancy, requiring ISO compliance for component quality, or implementing procedures to inspect, test, and maintain every aspect of the system.

Balance reliability and availability with Jira Service Management

With the right tools and approach, companies can balance system reliability and availability, especially in our always-on world. Jira Service Management enables teams to restore service rapidly.

Jira and Jira Service Management empower customers to report issues and help service teams centralize alerts for rapid categorization and prioritization. Rules and communication channels ensure that no one ever misses a critical issue.

Learn more about Incident Management in Jira Service Management 

What is an example of reliability vs. availability?

Consider new technology like driverless cars. Service reliability standards are near or at 100% because a single failure can result in injury or death. 

Conversely, the availability of driverless cars affects the user experience. The higher the availability or operational time, the better the experience. Low availability may cause the business to lose market share, but it is unlikely to result in injury or death.

Why are reliability and availability important?

Both reliability and availability impact a business’s bottom line because they affect customer satisfaction. In addition, systems that are not available or reliable cost companies money in lost revenue, spoilage, unplanned maintenance costs, and lost productivity.

Focusing efforts to increase service reliability and availability can result in a greater competitive advantage, an increased market share, better revenue, and an improved budgeting plan for maintenance costs.

What are the trade-offs between reliability and availability?

Businesses sometimes have to prioritize reliability over availability or vice versa. Real trade-offs may be necessary when timelines are short or investment funds are limited.

In the case of driverless cars, businesses are likely to invest more time and effort in increased reliability, even if it negatively impacts availability. However, in less critical situations, such as online retail, a business may focus on increasing availability because being “always open” is one of the key differentiators between e-commerce and brick-and-mortar competitors.

Why reliability calculations matter for system design

Reliability calculations are critical to system design and maintenance. By understanding the concepts of reliability, availability, and failure rates, decision-makers can make informed decisions about system design, maintenance, and repair. 

Reliability calculations can help minimize downtime, reduce maintenance costs, and improve overall system performance. By implementing robust reliability and availability strategies, businesses can enhance their operational efficiency, maintain customer satisfaction, and achieve a competitive edge in their industry.

Key points revisited

• Reliability is the probability that a system or component will perform its intended function without failure, under specified conditions, and for a given period of time.
• Reliability calculations involve mathematical models and statistical techniques to estimate a system's or component's reliability.
• Mean Time to Failure (MTTF) and Mean Time Between Failures (MTBF) are important metrics for reliability calculations.
• Availability is the probability that a system or component is operational and available for use at a given time.

• Reliability calculations can help to minimize downtime, reduce maintenance costs, and improve overall system performance.

By focusing on these key aspects, businesses can ensure their systems are reliable, available, and capable of meeting the demands of their customers and operations.