Software Development Updates

The concepts of observability and monitoring are most often used in DevOps, system engineering, and administration. Although there are a few similarities, both of these concepts have clear disparities. Before employing them as a part of your DevOps best practices, it is necessary to understand these concepts, how they work, and where they can be implemented effectively. This article on DevOps observability vs monitoring explores both concepts and discusses their differences to determine their capabilities and establish their scope of work, helping you pick a suitable approach for your DevOps project. 

1. What is Observability?

Observability is an approach to evaluate your IT workload’s health and performance. It collects data from various sources, like traces, metrics, and logs, to derive valuable insights into the overall performance and health of the system in the context of providing an enhanced user experience. 

It’s similar to the patient who’s given routine medical care for experiencing severe pain. In the case of the patients, doctors analyze symptoms and in the case of IT systems, developers assess the external outputs. They provide a better understanding of the system’s internal functioning. 

The goal of observability is to obtain a granular picture of the infrastructure, which is more than a monitoring system offers, to identify the root cause of the problem with certainty, especially when working with complex or distributed systems. 

2. What is Monitoring?

The tracking of a system or an application is referred to as monitoring. It is usually carried out in two ways: synthetic monitoring and real-user monitoring. 

Synthetic Monitoring: It focuses on monitoring short-term trends. It also leverages automation tools to measure the functionalities of the system.

Using sample values to determine if the web app is performing up to expectations or not is an example of synthetic monitoring. 

Real-user Monitoring: It is implemented for long-term trends where the user interactions with the app are recorded to determine if the app’s performance is up to expectations or not. 

However, you must define the metrics you need to monitor before implementing this approach. These predefined sets of metrics help you gather relevant data from the system to help find any errors and disruptions or highlight ongoing trends. 

Monitoring is mostly used in the DevOps environment to assess the performance and health of the data storage, network, and servers. All monitoring processes act as a subset of the organization’s overall observability goals. 

3. Key Differences between Observability and Monitoring

The line that distinguishes observability and monitoring is quite blurry. After all, monitoring is a part of the process that works towards achieving the objectives of observability. Monitoring is your organization’s early warning system, whereas observability is about finding the source of the problem and fixing it from its roots. Let’s discuss the differences between monitoring and observability.

3.1 Collection vs Context

Monitoring is conducted with a set of predefined metrics. So, it can easily identify the predetermined set of failure modes. Basically, monitoring can tell if there is a problem in your system, such as

 experiencing issues with going online or maintaining expected performance. 

On the other hand, observability tells you exactly what is the problem with your system, how it was caused, and how it can be fixed. It gathers the necessary details to give you a complete overview of the problem and its impact on your system. 

3.2 Tracking vs Knowledge

Monitoring tracks certain aspects of the system defined by the metrics. It warns the IT professionals when any issue arises relevant to these metrics. The observability gathers data on the internal functioning of the system to deduce the cause of the problem. Monitoring is about discovering faults in the system, observability is about discovering what needs to be monitored. 

3.3 Data Collection vs Data Interpretation

Monitoring functions on predetermined sets of metrics. Its work is highly specific to core KPIs. Used for collecting data about the health and performance of the specific aspect of the system, it allows developers to identify what’s working and what’s not. 

Meanwhile, observability provides surface-level data that needs to be interpreted in various contexts of the system’s functionalities and performance. It would also include data on complementary systems such as CI/CD pipelines and would aggregate data from logs and traces as well. It’s up to the developers to give context to the data to measure the overall health and performance of the system. 

3.4 Key Criteria vs Complete Assessment

With observability, cross-functional teams can understand what’s happening in highly distributed systems. With a complete assessment of the whole system, you can easily identify the problems and what you need to do to overcome them. 

Monitoring, on the other hand, is used to track core KPIs. it tells you if there is any difference in the predetermined values and the real-time data. Monitoring follows certain criteria in anticipation of the concerns you have about the system’s performance. 

3.5 Limited vs Sustainable

Because monitoring is restricted to selective functionalities of the system, its usefulness in the improvement of the system’s performance is also limited. On the other hand, observability allows you to assess the entire system, find problems, and suggest how to fix them. This is more of a sustainable approach that helps keep your applications performing well for the long term.

3.6 Single Plane vs Traversable Map

Monitoring warns you if there is an issue relevant to the predefined metrics. Although it alerts you by predicting the potential failure or errors in the system, it does act on a single plane as it can only tell if there is an issue or not. Meanwhile, observability allows you to traverse through the architecture and codebase to find and pinpoint the origin of the problem that’s hurting the overall health and performance of your system. 

4. A Quick Comparison

In the previous section, we saw a detailed comparison between DevOps observability vs monitoring. This section gives you a quick glance at the key differences between them.

Observability	Monitoring
Helps you find the reason behind the problem.	Helps you identify problems in your system.
Acts as a knowledge base and tells you what to monitor.	Monitors the system and tells you the faults in the system.
Allows you to give context to the accumulated data.	Collects the data.
Thoroughly analyze the whole system infrastructure.	Assess the pre-defined KPIs.
It’s a traversable map.	It’s a single plane.
Provides you with the whole picture.	Offers data specific to the predetermined metrics.
Give opportunities to monitor various events and services.	It’s the subset of observability.

5. Similarities between Observability and Monitoring

Observability and monitoring have similar goals. Both aim to derive insights into the complex infrastructure of the distributed system so that you can deliver an enhanced user experience. The monitoring works at a limited level, whereas observability works application-wide. 

However, both observability and monitoring tools in DevOps use the same kind of telemetry data; logs, metrics, and traces, which are also known as the three pillars of observability.

• Logs: The records of the events happening in your system and software application, offering context and details regarding the issue’s impact on the system. 
• Metrics: They help carry out a numeric assessment of how many resources are required and how well the system performs on those resources. Metrics are used to identify the changes between past data and real-time data over time or within a specific period. 
• Traces: It depicts how the operations move across the distributed environment. Traces provide context for troubleshooting certain service relationships or specific user interactions.

6. How Does Observability and Monitoring Work?

Both monitoring and observability are critical for the effective implementation of DevOps. This section explores how they work. 

6.1 Monitoring

This approach has been used since the initialization of computing systems. It allows you to monitor the system based on the predetermined metrics. It helps relevant data to check if the system is performing up to expectations. Monitoring provides a detailed report on the system’s performance and alerts the IT team in case of an error or anomalous data values. 

For example, the monitoring tools will gather data to measure deployment time. If it exceeds the expected time then the tool will immediately alert the team, indicating there is a problem with the app release. DevOps monitoring covers the entire software development project, wherein its subset APM (Application Performance Monitoring) monitors the apps running in production. It uses metrics prioritizing user experience. 

6.2 Observability

Observability works on a larger scope than traditional monitoring tools. It thoroughly investigates the system interactions and historical and anomalous events data. Observability enables you to find the root cause of the errors whose alerts were given by the monitoring tools. This approach helps deal with system issues, especially those arising via multi-component interactions. 

Leveraging observability tools, you can easily debug your application architecture or distributed systems. It also allows you to keep track of your system’s health and performance in real-time. The observability software helps map the whole distributed system and shows how each component is interconnected, as well as their interactions and dependencies. 

7. The Interrelationship of Observability and Monitoring

It’s a misconception that observability and monitoring are two separate concepts, hence unrelated to each other. We have already seen that the monitoring process is a subset of observability. And just because two concepts have a few differences doesn’t mean they are completely unrelated. In truth, both complement one another and each serves a unique purpose. 

One concept notifies you if something is wrong with your system. After knowing that, you use another concept to understand the problem and identify its source. The monitoring tells you WHAT doesn’t work, whereas the observability tells you WHY it doesn’t work. 

Although monitoring tracks the health of your app, it’s only possible if your system is observable. While monitoring tells you about the problems your software has, observability allows you to ask questions and brainstorm on how to improve your system’s health and performance. 

8. Observability vs Monitoring vs Telemetry vs APM

In DevOps, tracking the performance and overall health of the applications is critical. Observability, telemetry, monitoring, and APM are different concepts that help IT teams monitor systems to varying degrees. Let’s understand the differences between them. 

Telemetry is an automated collection of data such as logs, traces, and metrics from diverse and disparate systems, environments, and cloud architectures. The data is stored in a centralized location and is used to understand the performance and behavior of the system. 

Monitoring leverages the data collected by telemetry tools to alert the IT teams about errors and anomalies. While telemetry is possible for the whole system, monitoring is only possible for specific metrics. However, both monitoring and telemetry can only inform you about the health and issues of the system. Observability takes it up a notch and helps find what causes the problems and how to solve them. 

APM also gives detailed insights into the end-to-end performance and the availability of the application. The level of insights it offers is higher than telemetry and monitoring, but it doesn’t dive deep enough like observability to solve the issues from its roots. 

Although each concept works at a different level, one thing is remarkably common among them. They all leverage telemetry data to derive insights and help IT operations teams with their unique capabilities. 

9. Use Cases of Observability and Monitoring

The major differences between observability and performance lie in the extent of their coverage. Monitoring focuses on a single aspect of the system, whereas observability software provides complete visibility over your system. Let’s take a look at the use cases of these methodologies. 

9.1 Observability Use Cases

• Application Modernization: Observability tools make it easy to manage a growing app that constantly evolves to meet the changing customer requirements. It provides a unified system and dashboard to offer visibility and control over the entire system architecture. 
• Microservices Troubleshooting: Observability can easily track each request for multiple services and discover bottlenecks and failing components. 
• Cloud Infrastructure Observability: With observability, you can handle complex systems by aligning the team’s efforts with the cloud infrastructure. It acts as a single source of insights for UX improvement. 
• Performance Optimization: With observability, you get detailed insights into the performance of your software. You can easily identify which areas need improvement and how much. 
• Cost Optimization: Full stack observability of your system and infrastructure provides reliable and real-time data that helps you put a stop to unnecessary costs. 
• Root Cause Analysis: In the event of errors, observability enables you to trace the events and interactions to find the root cause of the problem. It is quite useful in instances where failure modes can’t be predicted. 
• Application Security: May it be large enterprise apps or distributed cloud environments, observability helps you ensure the security of your software systems. It can detect and address the errors automatically. If your system has any security vulnerabilities, then it can identify and resolve them immediately. 
• Dependency Tracking: A dynamic system would have numerous dependencies, but with observability, you can track down every one of them. Moreover, you can also track each interaction between components. You would also be notified in case any dependency fails.

9.2 Monitoring Use Cases

• Resource Utilization Monitoring: when you want to keep track of resource utilization in your system such as disk space, memory, or CPU, then monitoring is an ideal approach. It also helps with efficient resource management and allocation. 
• API Monitoring: Most of the modern apps are now using API for internal communication. So, to keep your app functional, it’s necessary to keep the API resources responsive, functional, and available. By monitoring APIs, you can collect necessary data to ensure uninterrupted operations. 
• Real User Monitoring: The app performance differs in the real-world scenario in comparison to the controlled environments. To ensure that your app performance doesn’t take a hit in real-world scenarios, real-user monitoring tracks all the user interactions. This provides the data you require to deliver an enhanced user experience. The data contains information on the app and service crashes, HTTP requests, page load events, and more. 
• Alerting for Critical Metrics: Alerts are triggered in monitoring when the system breaches the predefined thresholds. It allows you to quickly address the issues like low disk space or high server load. 
• Predictable Failures: When you know the common patterns of failure in the system, monitoring can come in handy. For example, it can alert you if the database reaches full capacity or any service crashes down. 
• Availability Monitoring: You can reduce downtime and its harmful effects on your app performance with availability monitoring. It keeps track of components like servers to check if they are available and if something goes away, it immediately alerts the IT team. 
• Security Monitoring: This helps keep your app secure by monitoring the access patterns and system logs to identify any anomalies and unauthorized activities. 
• Web Performance Monitoring: To monitor the availability of web services and other fine-grained parameters like loading errors, page load speeds, and more. 
• Application Performance Monitoring (APM): It is used to monitor the performance of websites and applications with a focus on parameters responsible for delivering a better user experience.

10. What to Choose? Observability or Monitoring?

During DevOps projects, observability and monitoring systems complement each other. But if the question is to pick one, then you might have to decide which one is an ideal option for your team and system. 

If you need to be aware of the problems the moment they occur, then you have to pick monitoring. On the other hand, if you have to eliminate the problems from its roots, then the observability platform is your best bet. In an observable system, all tools work in unison to ensure that both the performance of your applications and the user experience they deliver are seamless. 

11. Conclusion

At the end of the DevOps observability vs monitoring, it is important to note that every concept is unique and has a different role to play in the DevOps methodology. But the purpose of both remains the same; to maintain the security and performance of your system and applications. 

When you employ observability or monitoring to track the system’s health and performance, it also helps keep your system secure. Monitoring tells you about the loopholes in the system and observability tells you how to fix them. So, you no longer have to worry about faults in your system when you can leverage these methodologies to your benefit. 

FAQs 

What is the difference between observing and monitoring?

The biggest difference between observing and monitoring is their scope of work. Monitoring works for limited and pre-defined metrics whereas observability helps you assess the interactions across the entire system. This helps you find the root cause of the problem. 

What is observability in DevOps?

Observability in DevOps is all about understanding how your system works through the development cycle. It also allows you to detect and fix bugs before they affect the entire system, and deliver better user experience. 

What is monitoring in DevOps?

Monitoring in DevOps is all about keeping an eye out on the software development process from the planning stage to maintenance and operations. It provides real-time data on the system’s health and performance which can be compared to the expected values. It warns you if a service or system functionality faces any kind of problem. 

What are the three pillars of observability?

Logs, Metrics, and Traces are the three pillars of observability.