“34% of tech pros feel they need to improve their current skill set/ability to track impact across key business metrics to more confidently manage their organization’s IT environment.” (Cloud Confessions 2020)Delivering a consistent, acceptable user experience requires IT teams to learn new skills. In addition to learning how to make things in the cloud do what they’re supposed to do, IT teams must learn to extract information about application performance from new data sources. There are two main classes of application-specific measurements potentially available. The first concerns application performance metrics coded into the applications themselves during application development. The second class of application-specific measurements concerns user performance metrics. User performance metrics can be determined by recording and “playing black” synthetic transactions and measuring their performance. This is typically referred to as “synthetics.” Synthetics are popular for web-based applications as they can literally “walk” the transaction flow as a potential user might; giving insights into web page availability, page load speeds, and where bottlenecks might be—enabling optimization and monitoring of webpage performance for the web application. Code can also be seamlessly and automatically injected into a web frame, so actual, real user performance experience can be measured, a process called real user monitoring (RUM). Finally, independent of application-specific metrics, you must also use a set of indirect metrics. Determining why an application is performing poorly means determining the state of multiple intermediate networks comprising the internet path(s) between the end user and the application or between an application and something else. (Machine-to-machine performance can matter just as much as user experience!) Application performance management (APM) tools exist to help with this. They combine broad sets of application, database, server, virtual host, and container performance metrics, determining application performance in terms of application transactional throughput and response time. APM tools can offer chronological and relationship-based alignment for metrics and events, allowing IT teams to see what individual infrastructure components were doing when an error or slowdown occurred. Additionally, they give IT teams the ability to view what happened before and after an event to see what may have contributed to the issue. Better APM tools allow for a seamless marriage (in context) between application-specific performance metrics, end-user experience metrics, and the underlying IT infrastructure performance metrics such as database, server, virtual host, and container. Finally, APM tools typically offer analysis capabilities, simplifying the challenges associated with determining application performance using solely infrastructure or indirect metrics. In short, APM tools provide IT teams with the information they need to brief business leaders on how their apps are performing and what this means for the business—even when the applications they’re supervising aren’t under their direct control.
The Importance of Applications for Business Success
May 17, 2020
Applications
In developed economies, people who don’t use information technology are rare. Organizations not utterly reliant on IT are virtually unheard of. Everything is an app, and apps are at the heart of modern business success. So what’s the best way to ensure the applications we all depend on are operating as expected and when they’re needed?
Monitoring is at the core of IT operations. You can’t fix what you don’t know about and don’t measure. After years of stagnation, however, the art and science of monitoring is evolving, devaluing traditional best practices and requiring organizations to rethink their entire approach to IT operations.
Today’s IT teams are—as they’ve always been—ultimately responsible for application performance. The rise of cloud computing, mobile devices, and remote work and the inextricable intertwining of supply chains, however, present IT teams with new issues.
These teams are now responsible for the performance of applications they have no direct control over. Some examples include software as a service (SaaS) applications, applications provided by suppliers, and third-party data sets, such as those provided by open government initiatives.