Observability vs. Monitoring: Key Differences Explained

Updated June 1, 2025.

As IT infrastructures have evolved beyond on-premises data centers to include the private cloud, public cloud, hybrid cloud, and multi-cloud architectures industry, so has the need for effective monitoring and observability strategies and tools. While each offers different insights, people often confuse the two and even use the terms for the same things. There are a few notable differences, but they work together to identify areas of weakness within a system and provide information to troubleshoot the issue. Observability is especially important, as monitoring does not work on a system that is not observable. Read on to learn more about observability vs. monitoring and why you need to utilize them both.

• What Is Observability vs. Monitoring?
• The 4 Pillars of Observability
• What Is the Difference Between Observability and Monitoring?
• Differences at a Glance: Observability vs. Monitoring
• Why You Need Both Monitoring and Observability
• Monitoring vs. Observability: When to Use Each
• FAQs
• Unleash Cloud Potential with Deep Observability

What Is Observability vs. Monitoring?

Even though the terms are often used interchangeably, there are some important differences between observability and monitoring. Both systems work together to keep your organization’s data, systems, and security perimeter safe, but how do they do that? To understand the differences and benefits, you first need to know what these two types of tools are designed to do and how they can be used to keep your IT infrastructure running smoothly.

Observability

Observability focuses on the output of your system to assess the system’s overall state. If there are problems within your infrastructure, any abnormalities can help point you in the direction of what has gone wrong, which is why observability is crucial. Using different logs and metrics, as well as specific algorithms, you can monitor the health and status of your IT systems and catch problems before they escalate into something more serious.

Monitoring

Monitoring, on the other hand, focuses on collecting and analyzing data from the system about how things move through the different modules. While observability helps identify where the problem is, monitoring is what alerts you to the issue in the first place. One facet of monitoring that helps make it easier to analyze the data that has been collected is the use of dashboards displaying the different metrics. However, this only works if you track the right metrics. This is why monitoring a more complex system can be more challenging; it uses predefined metrics and logs to track trends, but the more complex a system is, the harder it is to predict.

The 4 Pillars of Observability

Four main pillars of observability are used to track the health of your system, including logs, metrics, events, and traces, often referred to using the acronym MELT. To provide the clearest picture of what is happening within the system and where any issues are originating, each of these gathers information about a different aspect.

1. Logs

Perhaps the most straightforward of the four pillars to describe, logs are time-stamped records of discrete events that happen within an application or database or on a network. Logs are typically the first data source that network and security professionals will refer to when any kind of unexpected event has been identified. Because of this, logs are often targets for bad actors looking to disguise their steps as they attack a network.

2. Metrics

Unlike logs that record specific moments or events, metrics are measurements that are taken over time — for example, the time taken to respond to a specific query. These metrics make it possible to identify performance issues such as bottlenecks that need to be remedied to meet service level or user experience goals.

3. Traces

Software developers build traces into their application code to identify where performance or other issues have occurred within their application. As such, traces are typically used within the development and testing process but can also be very useful to network and security professionals who need to identify problems in production applications and then work with developers to solve these problems.

4. Events

Events are any action that occurs at the application or system level on a network: for example, “user X clicked a radio button” or “a sysadmin updated setting Y on a server.” There can be millions of such events every day in large-scale environments, which means that event data can be difficult and slow to query. However, it is important to have access to this data for security forensics.

What Is the Difference Between Observability and Monitoring?

The simplest way to understand observability vs. monitoring is to think about the purpose of each: Monitoring is intended to alert you to any problems within the system, and observability indicates what caused the problem.

As part of the discussion about these two strategies, you will likely also hear about telemetry and application content performance monitoring (APM) information, but how do they play into the process? Telemetry refers to collecting data across different systems. APM information is very similar to observability, but it offers more of a surface-level view of system failures instead of an in-depth analysis of abnormalities within the output.

Observability and monitoring work best when used together, and there are a few key differences between the two that must be understood to grasp how they complement each other. Below are some of these differences and what they mean.

• Collection vs. context: Monitoring is all about collecting data to spot-check your systems. Observability, however, offers context for the collected data that allows you to take action.
• The characteristic vs. the act of observing: Observability refers mainly to the characteristic of being able to observe what is happening, whereas monitoring is the act of doing so.
• Process vs. potential: As with characteristic versus act, observability is all about the potential of a system to be monitored throughout the process. Monitoring is the process of using that potential to find events and track what is happening.
• Single plane vs. traversable map: The act of monitoring takes place on a single plane, in that all you have to do is set up rules for when you receive alerts about events. Observability is more involved and requires a traversable map that offers context to interpret the data that you collect.
• Key criteria vs. complete assessment: Observability is a key criterion for application development and offers insight into the system. In this way, observability provides a complete assessment of the operations and where to focus efforts when making improvements.
• Understanding vs. action: Before you can take action to fix a problem, you have to understand the state of the system, which is where monitoring comes in. Once you have an understanding, you can put observability into practice by acting based on the data you have gathered.
• Tracking vs. knowledge: Monitoring is the tool that you use for tracking performance. Observability is the knowledge that tells you what to monitor so that you can gather the most useful information.
• Wide vs. deep: If you are looking for a wide view of what is happening in your system, you will want to focus on monitoring. Observability, on the other hand, offers a deeper insight into the health of the system and all of its components.
• Limited vs. sustainable: It is necessary to continue monitoring the system over time as adjustments are made, and observability offers a sustainable approach.

Each of these differences boils down to one thing: what versus why. Monitoring strategies tell you what, while observability tells you why.

Differences at a Glance: Observability vs. Monitoring

Why You Need Both Monitoring and Observability

The terms observability and monitoring are often used interchangeably because the two work so closely together. They complement each other and serve different purposes that combine for optimum efficiency and results from your IT software development and operations strategies. Today’s modern enterprises need to utilize both monitoring and observability to ensure that all IT systems are functioning properly and that any breakdowns in the system are caught quickly.

Monitoring vs. Observability: When to Use Each

Choosing between monitoring and observability, or knowing when to use both, depends on your specific IT environment, goals, and system complexity.

Monitoring is most useful in well-understood environments where issues are predictable and predefined thresholds can be established. For example, if you’re tracking uptime or CPU utilization for a known application, monitoring tools can help detect and alert you to deviations from the norm. It’s particularly effective for:

• Maintaining service-level objectives (SLOs)
• Tracking key performance indicators (KPIs)
• Alerting operations teams of critical failures in real time
• Supporting application filtering based on predefined parameters

Observability, on the other hand, becomes crucial in complex or dynamic systems, especially in cloud-native, containerized, or microservices-based environments where unknown issues can arise and simple monitoring falls short. Observability enables a deeper dive into the “why” behind system behaviors, helping teams debug, diagnose, and optimize in real time. You should rely on observability when:

• You’re dealing with unpredictable issues or unknown failure modes
• Your system architecture spans multiple environments (such as hybrid or multi-cloud)
• You need to correlate and analyze MELT data for faster root cause analysis
• You want to future-proof your infrastructure by enabling proactive troubleshooting

From a cost and operational efficiency standpoint, observability also allows teams to reduce tool cost  by consolidating siloed data sources into a unified view. Instead of layering tool after tool for various point solutions, organizations can gain a comprehensive understanding of their systems with fewer tools.

In short, use monitoring for real-time alerts and basic system checks, and use observability when you need a deeper understanding of application health, user behavior, and system anomalies. Together, they form a responsive and sustainable operations strategy.

FAQs

Why is observability important in modern IT environments?

Modern IT environments are increasingly complex, distributed, and dynamic. Observability provides the contextual insights needed to understand how systems behave, uncover root causes of failures, and optimize performance across hybrid and multi-cloud environments. It allows teams to move from reactive firefighting to proactive and predictive operations.

Can you have monitoring without observability?

Yes, but it’s limited. Monitoring without observability means you’ll receive alerts and performance metrics, but lack the deeper context to diagnose and solve complex or unexpected issues. Observability makes monitoring actionable by providing insight into why something went wrong.

How do observability and monitoring work together?

Monitoring acts as your alert system, while observability provides the tools and context to investigate and understand the root cause. Together, they enable teams to detect, diagnose, and resolve issues more effectively, minimizing downtime and optimizing the user experience.

How does Gigamon’s Deep Observability Pipeline enhance traditional observability?

Gigamon’s Deep Observability Pipeline extends traditional observability by incorporating network-derived intelligence into observability data streams. This allows organizations to gain actionable context into encrypted traffic, lateral movement, and application behavior across physical, virtual, and cloud environments. It enhances security, performance, and compliance use cases beyond what other standard observability platforms can offer.

What role does monitoring play in Gigamon’s observability framework?

Monitoring is foundational to Gigamon’s observability framework. It provides the alerting and visibility layer that triggers deeper investigations. When integrated with Gigamon’s Deep Observability Pipeline, monitoring becomes enriched with network-level intelligence, allowing teams to not only know what is happening, but also why.

Unleash Cloud Potential with Deep Observability

Both observability and monitoring play a large role in the health of your IT infrastructure and can help you protect sensitive data. Gigamon offers deep observability, which takes observability further by combining network intelligence with metric, log, event, and trace data. This extends the capability and value of observability tools by enabling them to address security use cases.

Ready to see the difference for yourself? Request a free demo and discover how Gigamon can help you maximize visibility, strengthen security, and reduce operational risk across your hybrid and multi-cloud environments.

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