Monitoring vs. observability: the differences explained

Poor software performance can lead to significant financial losses, reputational damage, and compliance issues for businesses. It also results in increased development and maintenance costs and missed opportunities. In 2020, the Consortium for Information & Software Quality estimated that inadequate software cost the US economy $2.08 trillion. So, how can your company tackle this problem head-on? 

Read on to compare monitoring vs. observability and discover how you can use these processes to more effectively solve software problems, optimize system performance, and maintain uptime. 

What is monitoring in IT systems?

Monitoring involves collecting and analyzing metrics and logs to track the performance and health of IT systems. The main focus is on keeping tabs on known issues and areas where incidents are most likely to occur. Developers deploy tracking systems and alerts to notify teams of anomalies based on specific thresholds or conditions. 

Examples of monitoring in IT systems include:

• CPU and memory usage: Tracking hardware or virtual machine resource use is critical for ensuring systems are not overburdened. Abnormal spikes could suggest poor management, outdated hardware, or malicious activity. 

• Application Performance Monitoring (APM): Measures the time it takes for an application to respond to user requests. High response times could indicate performance bottlenecks in the code, database, or server.

• Real-time log monitoring: Monitors logs in real-time to detect and alert on specific patterns, such as failed login attempts.

• Uptime monitoring: Identifies whether critical services (like web servers, databases, or APIs) are up and running.

Monitoring is important for maintaining IT infrastructure and provides key insights into known risks and current performance. However, as an isolated solution, monitoring does not provide the context developers need to understand how modern, complex IT systems are functioning. For that, a broader approach is necessary. That’s where observability comes in. 

What is observability in IT systems?

Observability refers to the ability to understand the internal state of a system based on its external outputs. Observability makes it possible for developers to trace issues straight to the source using system interaction data and historical performance insights. In sophisticated, cloud-based environments, this approach gives developers context to understand what’s driving system behavior. It also enables organizations to adapt faster to changing IT configurations, troubleshoot more efficiently, and reduce operational costs.   

Examples of observability in IT systems include:

• Dependency mapping: Mapping system interactions to determine how a service or event affects or is affected by other services within the system

• Real-time event correlation: Correlating events with other real-time events or deployments to identify potential cause-and-effect relationships.

• Dynamic load testing: Simulating different load conditions to observe how a service or system changes under various scenarios, helping to predict potential issues before they occur in production.

Monitoring vs. observability

Monitoring and observability are often confused, yet understanding their differences is essential for optimizing your IT operations. Here’s a breakdown of the key differences: 

Which approach is more effective: Monitoring or observability?

While both approaches have their merits, observability offers more comprehensive insights and flexibility for managing the complexity of modern IT systems. 

Here are the key benefits of observability:

• Holistic system understanding: Provides a complete picture of system behavior, including unexpected issues.

• Adaptability to change: Better suited for dynamic and evolving IT environments.

• Enhanced troubleshooting: Enables faster and more accurate root cause analysis in complex scenarios.

• Future-proofing: Prepares organizations for unknown future challenges in system management.

• Improved collaboration: Enables better communication between development and operations teams.

• Cost-efficiency: Reduces overall operational costs by minimizing downtime and optimizing resource allocation.

However, it’s important to note that monitoring provides a good foundation for observability. Poor quality software can lead to significant financial losses, reputational damage, and compliance issues for businesses, potentially threatening their survival. It results in increased development and maintenance costs, lost revenue, and missed opportunities. Additionally, it can cause legal penalties and competitive disadvantages. The most effective approach often combines elements of both.

The three pillars of observability

Developers build observability processes on three main pillars. Understanding these fundamental concepts is crucial for gaining a comprehensive view of system behavior. Let’s take a look:

1. Logs

Logs are detailed records of events within a system. These messages include various important details, such as the date and time of the event and the ID of the process sending the log. Real-time logging allows developers to capture events as they occur to gather context for troubleshooting. This supports an in-depth analysis of system behavior over time. 

Example of classic format for log messages in Fastly. 

2. Metrics

Metrics are quantitative measurements of system performance. These offer numerical data points that can be tracked and analyzed for trend analysis and performance monitoring. Once a baseline is established, metrics tracking can support anomaly detection by identifying out-of-the-ordinary system behaviors. 

Example of a dashboard tracking a metric in Fastly.

3. Traces

Traces, the third pillar of observability, are sequential records of related events across distributed systems. With traces, developers debug distributed software architectures, gaining end-to-end visibility into request flows. This makes it easier to find the source of problems and optimize system performance. 

Example of a trace, generated with Fastly and OpenTelemetry.

Optimize your IT operations with Fastly's observability and monitoring capabilities

Monitoring is effective at tracking known issues and providing performance metrics, while observability is the ideal solution for understanding complex systems through external outputs. Together, they enable proactive problem-solving, minimize downtime, and enhance system performance, reliability, and user experience in modern IT infrastructures.

Fastly is the cloud-edge platform that enables you to bring these benefits to life. With Fastly’s monitoring and observability features, you can continuously keep tabs on your site, product, or service and get the deep, real-time insights you need to troubleshoot errors and improve performance. Our approach integrates logging, metrics, and tracing capabilities to provide a holistic view of your IT infrastructure.

Here are the benefits of using Fastly for monitoring and observability:

• Real-time logging: Stream logs instantly to various destinations, enabling quick debugging and issue resolution.

• Flexible metrics: Access 180 service-level metrics for detailed performance analysis and monitoring, including black box data like traffic between origin and cache.

• Distributed tracing support: Maintain request tracing parameters across Fastly's platform for end-to-end visibility.

• Customizable dashboards: Visualize data through intuitive interfaces for improved decision-making and accessibility.

• Third-party integrations: Easily connect with popular monitoring and analysis tools like Datadog, New Relic, and Splunk.

• Designed for various needs: Fastly's observability features cater to multiple needs, from cloud-native startups to enterprises managing complex, hybrid multi-cloud environments. 

The observability, speed, and security that Fastly provides is a game-changer. Find out for yourself by signing up for your free trial today.