In today’s day of age, data can be your most valuable asset. Unfortunately, many companies lose considerable feedback and potential revenue if they don’t track software health and performance. And without a helpful visualization tool, data can often be difficult to understand. This article will help you learn what goes into designing an effective DevOps dashboard, something that I’ve spent quite a bit of time thinking about as Co-founder and CEO of ContainIQ, a Kubernetes monitoring company.
A DevOps dashboard is a visual display of your app’s performance and health statistics. It is a way to see how good or bad your application is performing and identify the key areas that need improvement.
There are many reasons why you should strive to build an effective dashboard for your application:
● Team Alignment: Well-designed dashboards bring the entire team on the same page. You can aid your DevOps team’s meetings with dashboards to explain goals and understand results quickly.
● KPI Visualization: For each KPI that your team tracks, there are one or more performance metrics attached with it. Dashboards can help you relate your efforts directly with the outcome they are generating.
● Flexibility: While it is good to have more and more data, it can get challenging to manage and navigate through after a certain point. Dashboards help you arrange and navigate through data of any size quite easily.
● Interactiveness: Running basic operations and transformations is a fundamental task done on almost every dataset. Dashboards can reduce the manual effort needed by providing quick shortcuts to interact with the data and get more value out of it.
The list can go on and on. The crux is that data visualization is an inevitable part of everyday operations and business strategies. This is why you need to know how to design effective DevOps dashboards without much hassle.
We will now discuss a seven-step process to building just the right DevOps dashboards.
Before you set out to build a dashboard, you need to determine the purpose that it will serve. Without a goal, your dashboard will just be a collection of random metrics and graphs that will hold no meaning when put together.
For instance, you need to determine if you are trying to track your app’s outage incidents, its performance bottlenecks, or your team’s deployment activity. All of these need entirely different sets of data to build, and mixing their elements will not yield anything useful.
A good practice at this stage is to keep your dashboards simple. Do not try to solve more than one problem with a dashboard. Unless two tasks are highly related, do not build a common dashboard for them.
Once you have your purpose clear, the next step is to understand your audience. Data visualization involves a great deal of story-telling, and singing nursery rhymes to an eighth-grader will never make any sense. This is why you need to identify with and learn your audience’s expectations from the dashboard.
For instance, if you are designing a dashboard for on-call teams, you need to convey as much information as possible with very little clutter. If you are creating it for upper-level management, you need to focus on the bigger picture — mean time to recovery, lead time to change, etc. The best way to understand what your audience wants is to put yourself in their shoes.
With the audience and purpose in mind, you need to mold your idea into a popular preset. While innovation with dashboards is highly encouraged, most cases will fit into commonly used dashboard types. If you can adjust your requirements to fit one of these, you will save time and effort:
● Agile Project Management Dashboard
● End-User and Application Performance Dashboard
● Platform Observation Dashboard
● Alerts Tracking Dashboard
However, it is essential to understand that you don’t necessarily need to alter your initial requirements to fit one of the preset dashboard types. If your dashboard plan overlaps more than one of such dashboard types, you should consider building it as long as it will enhance productivity and add value to your team’s workflow.
The next step is deciding on the metrics for your dashboard. With a dashboard type in mind, you will automatically have a suggested list of metrics to start with. Try to stick to those if possible. If you need to include something that does not belong there, feel free to do so as long as it serves your dashboard’s purpose.
Also, you should maintain a balance between general metrics like deployment frequency, error rates, etc., and platform-specific metrics like failed pods, node resource consumption, etc., in K8s, for instance. General metrics help you see the big picture, while platform-specific metrics support it with relevant explanations.
Here’s a quick list of key metrics you should consider tracking:
● Change Frequency
● Pipeline Failures
● Mean Time to Recovery (MTTR)
● Application Health
● Other platform-specific metrics
Your dashboarding tool makes a bigger impact on your dashboards than you can imagine. It affects how you design things, ranging from its default dashboards to how you can modify visual elements. Therefore, you should always look for a tool that gives you absolute control when editing while providing a fair number of preset dashboards for an easy start.
Dashboarding tools are available both as paid offerings and open-source alternatives. While it might seem tempting to opt for a free, open-source solution, it will usually invite more effort on your part to achieve desired results. Paid solutions will make your job easier but will also burn a hole in your organization’s pocket if overused. Finding which type works for you is crucial before settling down with a tool.
When setting up monitoring, you can also opt for tools that offer visualization. Such tools can help you create dashboards easily, but you should remember that you might lose flexibility in some cases.
If your DevOps teams use Kubernetes in their day-to-day, you should consider taking a look at a tool designed keeping Kubernetes in mind. Kubernetes specific solutions, like ContainIQ, often offer a wide range of preset dashboards with alerting capability on prominent K8s elements such as events, pods, nodes, etc., and you can get started with it in under a few minutes.
All dashboards are composed of visual elements. These elements need to present figures and not be cluttered simultaneously. To do this, it is crucial to understand a few basic principles of UI/UX and use them to your advantage:
● Use whitespace properly: Do not fill all elements into one screen. Try to use blank spaces to add breaks between various pieces of information. This will reduce the visual load on your audience’s eyes.
● Minimize figure dimensions: Always prefer one-dimensional bar graphs over two-dimensional area charts or three-dimensional volumes where possible. This is because elements with more dimensions can be challenging to compare easily.
● Reduce data classes: Keep the number of classes compared in each graph low. While adding more classes makes it easy to see everything in one place, it can add noise to the visualization making it difficult for viewers to understand anything useful.
● Know when to use an element: A pie chart is suitable for comparing things in proportion, while a bar chart helps when looking at absolute values. Therefore you should study all available elements at hand and choose the one that fits your use-case properly.
The list above is not exhaustive. With every additional principle that you take care to implement, you will be improving your dashboard, enhancing its overall output.
The key to designing great dashboards is to track their reception and impact on their audience and improvise based on their responses. It is pretty natural not to get everything right on the first try. But if you can gain feedback on your dashboard from its audience, you can iterate on it and enhance it just like you would on a software project.
Effective DevOps dashboards can enhance the productivity and output of your DevOps efforts. While there are many ways to design a dashboard, following a well-defined strategy is vital to gaining value from your visualizations. We hope that the checklist this guide has charted out will help you when working on your next big DevOps dashboard!
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