As organizations increasingly depend on distributed system architectures to provide modern applications and microservices, their legacy monitoring tools struggle to keep pace. These outdated systems are often based on predictable failures, but when an unforeseen performance issue occurs, it can lead to outages and unplanned downtime that impacts your customers and your business.
Observability and monitoring are two methods IT Ops and DevOps teams use to quickly find and resolve the underlying root cause of these problems. While the terms are often used in tandem or even interchangeably, there are important distinctions between the two.
To help you understand the difference between observability vs. monitoring, let’s take a closer look at what these concepts mean, how they work, and how you can use both effectively across your IT infrastructure.
What Is Observability?
In control theory, an observable system is one in which you can infer the internal state based on external output information. IT Ops and software vendors borrowed the term "observability" to refer to the similar process of analyzing logs, metrics and traces to understand the internal state of IT systems.
Observability tools connect multiple systems and sources across your infrastructure to continuously collect telemetry data. These actionable insights enable IT teams to stay agile and proactive while providing enhanced context for informed decision-making.
Why Is Observability Essential?
As more organizations trend toward cloud infrastructure and distributed system architectures, the amount of interconnected, moving parts increases exponentially — and with it, the types and number of failures. This has made it exceedingly difficult to identify, diagnose and prevent IT service issues.
Data observability is critical for IT Ops and DevOps, providing greater control over these increasingly complex hybrid systems. Not only does it offer actionable insight into applications, but it also accelerates innovation and improves the end-user experience.
What Is Monitoring?
Of course, observability solutions wouldn’t be possible without monitoring. This is the process of collecting and analyzing systems data to assess the health of individual components and the overall infrastructure. With detailed information on application utilization and availability, monitoring systems enable IT teams to detect and resolve issues as they arise.
IT monitoring as a whole is generally divided into three primary categories:
Infrastructure Monitoring
Infrastructure monitoring looks at the underlying components and resources of your IT infrastructure, including servers, storage devices, databases, software and other elements. This type of monitoring typically tracks metrics such as CPU utilization, memory, disk space and network bandwidth to ensure optimal availability, performance and capacity.
IT Service Monitoring
IT service monitoring is the process of continuously observing and managing the performance and availability of IT services. The goal is to ensure these crucial services function within expected parameters and service level agreements, facilitating optimal service delivery to end users. With this information, you can proactively identify and resolve issues, thereby improving service quality, reducing downtime and enhancing overall user satisfaction.
Application Monitoring
Application monitoring narrows down even further to monitor the performance and availability of software applications within your IT ecosystem. By tracking response time, throughput, error rates, resource consumption and other performance metrics, you can identify issues that impact IT services, troubleshoot and resolve them, and optimize the end-user experience.
However, traditional monitoring tools require you to know which metrics you need to track. That means you'll have to set specific parameters to look out for "known unknowns," which could result in issues going unnoticed for the data you aren’t tracking.
Why Is Monitoring So Important?
While an observability solution enables you to track the "unknown unknowns" and make sophisticated queries of the data, it does not collect metrics, logs or traces from your IT systems. That’s why monitoring is essential: It allows you to automatically aggregate this telemetry data for analysis. The insights you gain from monitoring can help you track system performance, detect known failures and resolve issues before they become significant problems. More importantly, though, monitoring is a prerequisite for observability.
Observability vs. Monitoring Tools — Spot the Difference
The key difference between observability and monitoring tools is in the issues they identify. Whereas monitoring allows you to detect and react to problems you know can or will happen, observability enables you to find the root cause of unpredictable problems, particularly in cloud infrastructure.
Observability tools take monitoring to the next level, enabling IT and DevOps teams to correlate collected data in real time, providing a comprehensive view of their systems and applications. With insight into performance issues that occur outside of predefined monitoring parameters, observability also enables faster root-cause analysis and proactive issue resolution for cloud-native applications.
How Does Telemetry Play a Role?
Telemetry data is the "output" information that monitoring and observability solutions rely on to identify and resolve issues. This information comes in three different types:
- Metrics: A metric is any measurement of the behavior, health or performance of your infrastructure components.
- Logs: An event log is a time-stamped record of events over a specific period of time.
- Traces: A trace follows the entire journey of a request or action through your distributed system.
Telemetry systems use a variety of sensors and other devices to automatically collect this information for real-time analysis, or to transmit it to storage for later analysis.
What to Look For in an Observability and Monitoring Tool
To manage increasingly complex distributed architectures, IT Ops and DevOps teams need a dedicated set of solutions that can provide real-time insights, visualize operational states and alert staff of potential issues or failures.
Your monitoring and observability tool should automate data aggregation and centralize this information on a single platform. That way, you get a single source of truth to track health and performance across your entire infrastructure. With this reliable data, you can proactively detect and resolve problems as they occur and make informed decisions around infrastructure changes.
Beyond this essential capability, monitoring and observability tools should:
- Handle large-scale environments with high volumes of data.
- Integrate seamlessly with your existing systems and IT infrastructure.
- Provide distributed tracing functionality across multiple microservices and components.
- Offer interactive visualization features to dive deeper into your data.
- Enable robust querying and analytical capabilities to uncover hidden insights.
It's important to remember that a monitoring tool is not the same thing as an observability tool. Choosing the right solution for your business will depend on your specific needs, so it's crucial to assess the features, capabilities and compatibility of each before making a decision.
Modern Monitoring and Observability From Zenoss
Enterprise systems are constantly evolving, incorporating a complex mix of modern and legacy technologies. These dynamic environments can be difficult to monitor, but observability platforms provide your IT teams with the visibility they need across your entire hybrid ecosystem.
Read our white paper to learn more about modern monitoring and observability with Zenoss Cloud.
