Modern application environments are increasingly complex and distributed. They are fluid in function and often run on a mix of hardware and software platforms.
This means that it can be challenging to pinpoint the exact issue. But digital teams aren’t able to deliver user experiences and business outcomes without accurate performance insight.
User experience is often impacted by response times. A slow application can frustrate users and prevent them from using the system effectively. It can also damage brand reputation.
For example, if users notice that their web browser takes more than a second to display a page, they may not be willing to continue using the site. Ideally, a response time should be less than one second so that the user can stay engaged in the task at hand.
Response time can be difficult to monitor because it relies on various elements such as network performance and user device capabilities. To accurately measure response time, it is recommended to use transaction tracing tools that stamp packets with a code as they pass across different server tiers (Web Servers, Application Servers, Database Servers, etc.) to get a complete picture.
Error monitoring enables teams to identify issues that unit and end-to-end tests miss. This speeds up problem resolution and prevents revenue loss from slow downs that frustrate customers.
Insecure error handling is one of the most common flaws that impact application performance and security. OWASP recommends that developers use error handlers that produce simple messages for users and diagnostic information for site maintainers, while revealing no useful information to attackers.
An APM solution can analyze error logs to determine where and when problems occur, as well as provide IT professionals with historical trends to help them anticipate future performance issues. This eliminates the need for IT to search event logs manually or build synthetic monitors, saving time and associated costs. It also helps ensure that the overall environment for applications is stable and secure, ensuring that business operations are not affected.
Throughput is the rate at which data is processed and transferred. It’s used to measure the performance—meaning speed—of everything from hard drives and RAM to Internet and network connections.
IT and development teams rely on throughput measurements to answer questions about the capacity of their systems. They also use them to set application performance testing goals.
Unlike bandwidth, which measures the amount of data that could theoretically be transferred over a network, throughput provides a practical measurement of how much data is actually transferred over a given period of time. Throughput is also affected by network latency, which is the time it takes to send packets from one end of a network to another. The more latency there is, the lower the throughput. Error debugging is crucial to understanding and reducing network latency.
A cache’s effectiveness is based on the ratio of cache hits to misses. A cache hit means that the requested data is available in the cache; a cache miss means the required data cannot be found in the cache and must be fetched from the primary data source.
There is a cost to caching, however. If the cache contains sensitive information, like user logins or credit card numbers, it may expose those sensitive details to security attacks by hackers.
Companies must be able to translate their metrics into a narrative that reveals the reliability of the system and provides insight into the user experience. In this way, they can provide value to both technical and executive teams.
For example, CPU usage is a key application performance metric that helps businesses understand the impact of their software code on the responsiveness of their applications. High spikes in CPU usage might indicate that an application has reached its processing limit or is experiencing memory leaks.
Metrics also help enterprises develop a streamlined AppSec approach and channel their team’s efforts to achieve security goals. For instance, identifying the number of outstanding vulnerabilities and their severity ranks helps organizations prioritize their patching activities to ensure that the most critical applications are secured first.