OpenText™ Observability differs from traditional monitoring in that observability not only gathers data but also analyzes that data to provide actionable insights. Those extra steps provide a more comprehensive understanding of system/application behavior and help to identify issues that would otherwise be difficult to detect.
Observability is not new; the term “observability” was coined in 1960 in conjunction with control theory. Observability has moved into other disciplines, including IT. Because of the complexity of hybrid cloud, the term “cloud observability” is also now popular.
Observability is often confused with monitoring, but the two are quite different.
Monitoring refers to observing a system’s performance over time. Monitoring tools typically collect data from specific sources, such as log files or performance counters. For example, monitoring can tell you how many users are on the system, but it is not proactively telling you when you’re reaching a capacity limit. Monitoring is a reactive approach to problems as monitoring requires you to know what’s important to monitor in advance. The limitation of monitoring is that it’s focused on capturing metrics at a specific point in time.
Observability serves a broader function than monitoring. Observability tools gather data from all available sources, such as logs, performance counters, and application code. Then the tools analyze that data to gain visibility into the inner workings of a system and understand its behavior. This data can be used to detect issues before they cause problems by identifying trends and gaining insights into how the system can be improved.
Observability is an outcome of monitoring and analysis, much like sight is an outcome of your eyes and your brain’s visual processing. AIOps or Artificial Intelligence for OpenText™ IT Operations tools are geared to provide observability and more. In addition to providing observability, AIOps uses its analysis to determine what corrective actions can be taken and then automates remediation.
A smooth environment requires observability, especially if you have cross—functional teams and a highly distributed computing environment. In fact, observability enhances critical daily IT operations, including:
Observability has broad-reaching applications—from optimizing web transactions to ensuring that IT performance meets customer expectations. Here’s a use case that highlights its value:
Let’s say you're a developer trying to identify the cause of a system crash. With monitoring, you would have to make sure all relevant systems had been monitored, manually collect data from them, and then try to piece together what happened. This process would be difficult and time consuming because your data would be from after the crash occurred.
With observability, you would have automatic access to data from all available sources. You would also have the help of analytics to find anomalies that could point you to the problem before it crashes the system.
Organizations can take advantage of the following key benefits and gain complete IT observability. These benefits include:
When implemented correctly, observability can be a powerful tool for gaining complete IT visibility—which translates to positive impacts on an organization’s IT performance quality, efficiency, time to market, and profitability.
AIOps transcends observability and translates it into action. Observability can provide developers insight such as application behavior to specific parts of code. AIOps can help operations teams respond automatically to outages and slowdowns while expending much less effort. When your organization uses these tools, teams gain maximum visibility and a deep understanding of issues and their impact.
Observability is an important element in understanding the entire state of your entire infrastructure. The influx of tools that were implemented with good intentions has left a mess of your IT estate and it’s causing your systems to be more complex than they’ve ever been.
That makes troubleshooting and managing these systems rife with difficulties. More tools lead to a greater array of problems, especially when heavily relied on tools stop working, they’re harder to detect and fix.
Effective observability tools provide a proactive remediation approach to help uncover problems quicker.