The terms observability and monitoring are often used interchangeably, but they serve distinctly different purposes in IT operations, with observability offering deeper insights and the ability to optimise performance proactively.
This is according to Alvin Barnard, Solution Consultant at OpenText, who says observability takes monitoring to the next level, adding context that helps improve performance, streamline issue resolution and enhance IT service delivery.
Monitoring vs observability
Barnard explains: “While monitoring focuses on tracking system performance by collecting data from specific sources like log files or performance counters, it operates reactively. It can highlight system usage trends but does not proactively predict potential failures. Monitoring is limited to predefined metrics, offering snapshots of performance rather than a comprehensive analysis.”
Monitoring tools outputs include metrics and utilisation, events, logs and traces (MELT), he says.
“For example, on metrics, think numbers indicating health and performance (my fuel tank is 90% full, disc utilisation is 10%, network line utilisation is 100%, is there the word error in this file, true/false). Events relate to an alert created by placing a condition on a metric (ie, when my fuel tank only has 5% left, send me an event saying time to fill up with petrol). Logs are textual information about system status/activity used for troubleshooting, and traces are how requests flow through systems and show how the components interact and identify bottlenecks.”
Barnard says observability, on the other hand, provides a deeper understanding of a system’s behaviour by gathering data from various sources, including logs, application code and performance metrics.
“By analysing this data, IT teams can gain real-time insights into system operations, detect issues before they escalate and optimise performance proactively. In essence, observability is an advanced outcome of monitoring, enabling organisations to maintain complex IT environments efficiently,” he says.
Barnard elaborates: “Without monitoring, there cannot be observability, and most organisations have many monitoring tools – typically by technology domain. For example, by server (Windows/Linux/Unix), database/storage or applications. A lot of the tools would likely already be in existence in the different organisations. Observability comes about when the output of the tools gets consolidated into a single place through integrations and context is applied.”
The role of observability in IT operations
Barnard notes that traditionally, IT operations teams rely on monitoring tools to ensure uptime and performance. When an issue arises that isn’t linked to a hardware or software failure, they escalate the matter to developers, who use observability tools to investigate.
He says: “Developers often conduct in-depth analyses using tools like Prometheus, which enable them to track system failures and identify root causes. The adoption of OpenTelemetry has simplified data collection and correlation, allowing IT teams to access comprehensive observability insights without requiring expertise in complex query languages. Instead of manually analysing logs, teams can leverage automated tracing and correlation, making issue resolution faster and more effective. While IT operators may not modify code, they can pinpoint performance bottlenecks and direct issues to the appropriate team or third-party vendor.”
Barnard adds that observability also benefits infrastructure teams. “Due to the complexity of environments these days, we are seeing observability being applied across disciplines, including cloud observability, network observability and infrastructure observability. We also see the emergence of the SRE (site reliability engineer), where the typical IT silos are being knocked down and someone is responsible across the stack.”
Using context
Barnard says the context observability helps teams focus on preventing or resolving any problem as quickly as possible.
Using the car example, Barnard says: “We monitor the fuel percentage – full metric. When it gets to 95%, the monitoring tool generates an event saying fuel tank needs to be filled.
"The car is also continuously logging data about what it’s doing; for example, the driver accelerated to 70%, the driver hit the brakes, the driver took a corner. As a trace, we have a tracker in the car, and we can see: ‘Leaving Jhb 12:01, five people in car, arriving in Pta 12:31 – 30 minutes.' The output of observability would be to make sense of all the data in context.”
The context shows that the driver completed a 45 minute trip in 30 minutes. Because of his excessive speed and the fact that the car was overloaded, they ran out of petrol and the driver is now stuck in Pretoria.
Key benefits of observability
Barnard highlights several key benefits of observability.
“Continuous observation helps detect critical issues early, leading to more reliable systems and improved user satisfaction. It also supports faster debugging, reduces downtime and improves productivity. This also supports faster time to market for new applications and updates,” he says.
“Observability enables data-driven insights that help improve decision-making by providing key performance indicators (KPIs) such as return on investment (ROI) and system health metrics.”
By correlating logs, metrics and traces, observability accelerates issue identification and resolution, and enables proactive resolution of issues before they impact service quality and brand reputation. It also ensures better oversight of cloud, Kubernetes and IT infrastructure performance and helps organisations optimise resources and plan for future growth. Observability also supports collaboration: a shared understanding of system behaviour fosters smoother communication between development, operations and business teams.
By implementing observability strategies, IT teams can gain full visibility into system performance and support long-term operational success, Barnard concludes.
To learn more, download OpenText’s white paper on observability:
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