Software deployment is somewhat similar to driving in a rally. Either way, the entire process is full with obstacles, teamwork, flexibility, and an unwavering quest for greatness. Developers race against time and technical challenges, relying on their expertise, teamwork, and strategic thinking to cross the finish line with a polished and efficient piece of software. 

However, the key difference between the pole position and the second place lies in the capabilities of the team to ‘observe’ the race beforehand. Every software development project begins with charting the roadmap and assessing the tools and technologies to use. 

Nevertheless, a development team that predicts the possible pitfalls and deploys on-the-fly remedies to counter them, i.e., observability, is a team that functions as a ‘well-oiled’ machine and leads the organization to achieve success. 

You can easily confuse observability with visibility or monitoring and this article aims to disburse the confusion, explain what observability is, its importance in software engineering, and how to implement it.

Introduction to Observability

In most software development projects, one of the most common mistakes committed by the development teams are looking at surface-level aspects of an application or system. This approach is highly time consuming as the team has limited visibility and is incapable of predicting any problems or roadblocks and will only address issues when they arise. A direct comparison to this would be playing a game of whack-a-mole. Your team is ‘whack’ing out the problem when it raises its ugly head. 

Observability is about gaining deeper insights about an application in the form of data gathering through dependencies, metrics, logs and traces. Experts run the numbers to identify the cause of any issues and debug it for a better system performance. This is a highly effective method in software development, with companies migrating to cloud-based solutions and the distributed system architecture making it difficult for tools to trace origins of an issue from the thousands of processes running on the cloud. 

The observability concept is derived from monitoring, which is the process of gathering, evaluating, and turning system data into useful insights. Observability is more associated with using the data generated from monitoring to provide a holistic understanding of your system.

Importance of Observability

When restricted to a single system, system admins have little difficulty in managing the resource allocation for complex tasks. The team can deploy appropriate fixes after assessing the CPU, memory, databases, and network resources. However, this approach severely fails when troubleshooting a cloud-based solution or an application installed over a distributed system where each server fulfills a different purpose.

There are too many interconnected parts in a distributed system, so the scope of something failing becomes higher. Multiple services as well as components come together to deliver a specific functionality. To pinpoint the issues, observability provides the DevOps team with adequate data, which they can use to quickly diagnose and resolve issues.

Instead of the development team burying themselves in the application codes to identify any bottlenecks, they use observability to collect and assess application logs, database metrics, and network traces to generate a complete picture of everything happening behind the scenes. This way, they can also identify patterns/ trends of an issue and prevent it from growing into a blow-up failure. In fact, 91% key decision makers in software development domain see observability as critical at every stage of the software lifecycle (Source: NewRelic) 

The Four pillars of Observability

Quite contrary to what is most commonly known about observability, there are four pillars instead of three. Software engineers use these four pillars of observability to determine the KPIs and create an observable system that provides them with reasons behind an unexpected issue in an application’s operations. The four pillars of observability are:

Using Metrics

Developers can use the metrics shown in observability tools to create innovation in their next product releases. Developers can see trends over a predetermined time period by using observability tools, which gather data from various endpoints and applications. For instance, to ascertain the busiest period of the day for the company, engineers could look for trends in application performance and usage spikes over the course of a month.  

Using Traces

To track known issues, traces are required. Developers can use traces, for instance, to identify the root cause of a particular problem. These mistakes may have been caused by specific infrastructure problems, problems with the programming, or a lack of scale and resources.

Using Dependencies

Modern softwares employs many dependencies and libraries to carry out application functions. These dependencies could be handled by outside developers, thus it is important to keep an eye out for any modifications and mistakes. The application architecture is mapped to dependencies by observability tools to track upgrades, vulnerabilities, and code audits.

Using Logs

Logs gather real-time data that enable developers to immediately replay suspected flaws and troubleshoot difficulties. Hence, logs play a vital part in whole stack observability and accurate debugging. 

The monitoring and observability of systems in both on-premises or cloud contexts depends on logs. They include all the information gathered from various points throughout the environment for analytical, graphic, and other reporting applications.

How Observability Can Benefit Your Software Engineering Process?

Some of the common pain points faced by software development teams would be some of the following: 

• Lack of clarity in processes
• Hiccups in workflow
• Absence of alert mechanisms

Once implemented, observability offers a plethora of benefits as long as you follow the best practices and have them integrated in your software development system. Here are some ways that observability can highly benefit your software engineering process:

Early Issue Detection

Using observability tools, developers have real-time insights on software system behavior. So any potential issues such as performance bottlenecks, error in code, or incompatibility is detected and addressed before it can impact the end user or evolve into a critical problem.

Quicker Troubleshooting

Using the four pillars of observability, developers can pinpoint the exact root cause of any problem. So less time is invested in troubleshooting, reduced downtime, and quicker issue resolution.

Better System Performance

Every software requires periodic optimization to provide optimal efficiency and responsiveness. Using observability, you can monitor critical performance metrics such as resource utilization, response times and fine tune the application processes accordingly.

Better Decision Making Capabilities

Developers and stakeholders can make informed choices about software architecture, feature prioritization, and resource allocation based on real-time insights and historical trends. By understanding what your customers’ biggest frustrations are, development resource allocation becomes easy and the team can prioritize their product roadmap or bug backlog.

Improved Collaboration

Using metrics, data logs, system traces, and dependencies, the DevOps can observe improved collaboration within the team as everyone has a shared understanding about the system behavior. 

Scalability and Capacity Planning:

Observability helps you understand how your software behaves under different workloads. This information is crucial for planning and optimizing the capacity of your system to handle increased traffic and demand.

Tightened Security

Monitoring access logs, user behavior, and system activities can help your team to detect and respond to security threats in a timely manner.

Better Quality Assurance:

Observability allows for more effective quality assurance processes. Developers can monitor test environments, track the impact of changes, and validate the expected behavior of software features.

Support for DevOps and Continuous Delivery:

Observability aligns with DevOps principles by promoting collaboration and transparency between development and operations teams. It also supports the continuous delivery pipeline by providing insights into the health of the software at every stage.

How to integrate Observability?

At this moment, we assume you are on-board with introducing observability and want to know how to get started.

There are several approaches your company can choose such as 

• using logging frameworks
• instrumenting code with metrics and traces
• leveraging specialized observability tools such as Honeycomb, 

Irrespective of the approach you choose, the vital aspect of observability is starting with a plan on what data you need to collect and how you will analyze it. It is not possible without collaboration between developers, operations teams, and other stakeholders to identify the most critical metrics and events to monitor.

Conclusion

While this article may have clarified your concepts of observability, you may be looking for more information about the challenges you may face, the best practices to follow, and the common observability tools businesses are using. Stay tuned for a follow up article on the same.