Software development firms need to develop and deploy software solutions and changes quickly, safely, and as demanded by the client. DevOps can help! There’s a major subset of DevOps you can’t overlook: observability.
What Is Observability in DevOps?
What use is monitoring without observability? According to Wikipedia, a system is observable if you can estimate its current state using only the information from outputs.
Observability in DevOps is a technical solution that focuses on helping IT firms understand what processes are going on in an application by looking at the application’s output. Observability also lets firms understand problems in the application operation by pinpointing how, where, what, and why the application operation is malfunctioning. It also provides insight into which process has failed.
Why Is Observability Vital to DevOps?
The need for observability in DevOps can’t be overlooked. It’s a major component if you want to harness the maximum benefits offered by DevOps. Since DevOps consists of practices that involve constant delivery of projects, it’s important to get feedback.
For instance, most DevOps models require CI/CD (Continuous Integration and Continuous Delivery). It’s crucial to know if new changes will break the application! This is where observability comes in. It allows developers to keep activities in check when shipping products to users.
Sometimes, people compare observability to monitoring. However, the two processes are different. In monitoring, developers collect and aggregate information. In contrast, observability helps people understand what’s going on in the system with the data collected. Simply put, monitoring exposes that there’s an error in the system, while observability pinpoints the area of error.
Applications have gone from being monolithic to being more distributed in nature. This makes it difficult to pinpoint error occurrences by just monitoring.
Observability helps you solve this complexity. First, it lets you understand the compound internal state of the application just by observing its external outputs. Also, it traces and identifies where and when the problem happened.
Components of Observability
For proper observability of a DevOps model, there are some basic components that you should know. These components are the pillars of observability! They are:
Metrics are a set of data that show the performance of a system. They’re collected over a specified period, which could be days, weeks, or even months. Metrics deliver a continuous, point-in-time overview of the system. This enables DevOps teams and developers to spot specific trends as regards the performance of the system. And that makes it easy to point out where the problem originated.
Metrics usually measure and monitor various aspects of system performance, such as the traffic and even the memory usage of the system. This in turn makes it easier to find and solve common and known problems. For instance, teams can use metrics such as website traffic to monitor turnover rates by users.
Event logs are simply a written record of events ongoing in the system. You can get this component of observability from the record of incidents from past and present events while running the application.
Logs give you a view of events and errors experienced by the system, providing context to the problem at hand. Event logs help DevOps teams understand an error’s cause, allowing them to learn from previous occurrences.
A trace provides DevOps teams an overview of the system based on the request or transaction made in the system. First, a request is made to the system, and then it records the request flow from one service to another. Traces are a major pillar of observability because they make the system under observation more visible and understandable.
Tracing is achieved through the provision of a detailed view of what happens in the various parts of the system when a request is processed. It helps you understand the relationship between the cause and effect of an issue by telling you which services are contributing to the poor performance of the system.
Note that each of these components gives a different type of external output. Observability involves using these external outputs to understand the internal workings of the system, despite how complex the system is.
Benefits of Observability
Observability has been beneficial to the growth of software development companies in all aspects of a company’s business. The benefits include the following:
- It helps the IT firm to have a complete understanding of the internal workings of their system.
- Observability reduces the downtime spent in resolving issues, as it tends to bring the possible causes of the issue into focus.
- It gives the DevOps team the ability to identify the root causes of issues.
- Observability makes debugging and troubleshooting easier.
- Observability helps companies monitor the performance of the application or system.
- It helps in speeding up the Mean Time to Detection (MTTD) and the Mean Time To Resolution (MTTR) for software infrastructure and services.
- Observability also enhances customer satisfaction if staffers use data from logs and metrics to improve services.
Common Pitfalls in Observability
It’s normal for IT firms to experience some pitfalls when using observability in their systems. Here are some to keep in mind when you’re incorporating observability into DevOps.
Pitfall 1: Uneven Distribution of Information
IT firms sometimes relegate the knowledge of the workings of the observability system to only the DevOps team. Don’t make this error! Rather, observability has to be integrated into the knowledge of all developers working within the firm. This will help in debugging since information is spread evenly among employees.
Pitfall 2: Working Without the Right Tools
Without proper tools, it becomes difficult to observe activities in the system. For instance, without proper tools, teams can’t collect the right data during monitoring. And inconsistent data fed into the system often leads to improper warnings.
To avert these issues, it makes sense to use a tool like Netreo. Its telemetry data features give you access to the data you need for your system observability.
Pitfall 3: Poor Alerting System
In observability, teams tend to prioritize symptom-based alerts and ignore cause-based alerts. This is often because developers tend to write alerts for every possible error in the system without looking into their causes. For instance, the cause of slow response can be an overloaded CPU.
Another problem is to deliver all the possible alerts to the entire team using a single pathway. This can lead to ignoring alert calls. To prevent this, use different pathways for different alerts.
Best Practices in Observability
There are some do’s and don’ts that the developer or the DevOps team should put into practice when it comes to observability. These rules include:
- Don’t try to monitor everything. Instead, gather only the necessary data.
- Focus more on monitoring essential things and fixing them if they fail.
- Avoid storing every log or data available. Rather, store those that give insights to critical events.
- Put up alerts on critical events.
- Create data graphs that are easily understandable by every team member, as this will improve the usability of the information.
Conclusion and Further Reading
In this article, you’ve learned what observability in DevOps is and why it’s necessary. You’ve also learned about the components of observability and common pitfalls to look out for when you’re incorporating observability in the DevOps model.
Now that you know why observability in DevOps is important and how to go about it, you can check out Netreo. It’s a great tool for IT infrastructure monitoring, for when you want a hands-on experience of observability in your DevOps model. Also, because observability works together with monitoring, you can explore these monitoring tools.