How organizations can successfully measure an application health monitoring process

Organizations today require every employee, application and process to work in coordination to produce value. Organizations increasingly depend on their technology stack—which comprises the totality of their network interfaces, CPUs, virtual machines, operating system information and installed applications—to deliver consistent service to the end user. This means companies especially need their software applications to perform optimally because they are often a source of competitive advantage (link resides outside of ibm.com).

This is also why application health monitoring is so critical for modern organizations. Application health monitoring is a diagnostic process that involves identifying application health issues and creating a resolution plan before they turn into greater issues for an organization.

Organizations cannot risk unnecessary unplanned downtime or increased latencies because an application failed or underperformed. The inherent dependencies of applications can mean that one failure can have cascading effects on the entire service offering. As such, it is critical to invest in application health monitoring and to ensure that your apps can handle the demands of an organization’s daily requirements. Since any disruption to this flow can have significant consequences for the company’s bottom line and its customer relationships, it is important to prioritize application monitoring within modern organizations.

Monitoring application health shares some similarities with application performance monitoring, which monitors digital experiences like load time, response time and uptime and availability. While both improve how applications work for end-users, application health monitoring is primarily concerned with an application working, while application performance monitoring also focuses on improving the user experience (link resides outside of ibm.com).

Organizations need to have a comprehensive plan to ensure the health of their applications, but one key component of any application health monitoring process is data collection. Applications fail or underperform for many different reasons. As a result, it’s important to track several key health statuses and performance metrics so you’re not discovering performance issues too late. As such, many organizations attempt to manage their application health and track key metrics through advanced health reports.

Here are seven important metrics that identify the relative success of your application health monitoring process:

1. Application availability and uptime: This is the amount of time an endpoint (such as a mobile device, computer or virtual machine) can access and use an application. Software downtime is a huge organizational risk because it decreases customer satisfaction and potentially violates a service-level agreement (link resides outside of ibm.com) with end users. Maintaining application uptime has only become more difficult recently due to multiple applications being connected and many pulling from provider APIs to pull in external resources. Organizations must know when performance issues happen and how to troubleshoot them.
2. App launch time and response time: This relates to initial application load time and response time to requests or user queries. For example, a user opens an application, which queries the servers to display the application’s home screen. An app that takes a long time to open will decrease customer satisfaction and it may be a sign of a larger issue. That’s why organizations need automated, real-time health checks of how long it takes for apps to perform so they can make appropriate changes to functionality if the app response threshold is below acceptable rates. Organizations that understand their response times can likely plot proactive remediation strategies before the application fails.
3. Resource usage: This measures the percentage of available resources an application is using at any particular time. Certain applications that are resource-intensive can impact performance elsewhere. You likely have experienced something like this—for example, when your computer is slow because you have multiple applications open or one overloaded application (like a browser with dozens of opened tabs).
4. The number and severity of instances and problems: It’s also important to identify how severe each incident is and how its failure or underperformance impacts the overall system. Application health monitoring often influences incident management and problem management, which involves the remediation of those issues discovered by application health monitoring.
5. Mean time to detect (MTTD): It can take anywhere from a millisecond to several days to determine that an application failed or started underperforming beyond an acceptable margin. MTTD (also sometimes referred to as mean time to discover) measures the average time it takes to identify that an application or part of the IT system has failed. Ideally, an organization either has established automated notifications or data visualization graphs and workflows so human intervention can take place to identify issues quickly.
6. Mean time to repair (MTTR): MTTR measures the average time it takes to repair a system or piece of equipment after it has failed. MTTR tracks the time from when the failure occurs to when the application functions properly again. MTTR is a key metric to monitor because it tracks the efficacy of repair efforts, a key component of application uptime or availability.
7. The number of cybersecurity incidents: IBM research finds that the global average cost of a data breach is $4.45 million in 2023, a 15% increase over 3 years. There has been a “near-sevenfold increase in spear-phishing attacks” (link resides outside of ibm.com) since the beginning of the pandemic. There are many reasons why an application may fail or underperform, but one of the most worrisome is it failed because of an external cybersecurity threat. Using monitoring tools to detect potential security issues like malware injections, distributed denial of service (DDoS) and others can improve overall application health.

Organizations depend on their applications working to increase the efficiency of their operations and deliver services to their customers. The best way to improve application health is through a regimented process that identifies and tracks key metrics that illuminate how individual applications are performing and provides a holistic view of the overall system.

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