3 Strategies for a Smart DevOps Metrics Dashboard
Many businesses adopt DevOp principles for the sake of streamlining their workflow. Frequent production deployments are indeed attractive, but quality intelligence is the real showstopper. Data-driven decision-making is the cornerstone of DevOps, and the dashboard’s primary function is to provide your company with actionable insights. The advice that follows will guide you through the setup of a smart DevOps metrics dashboard.
What makes a DevOps metrics dashboard intelligent?
Companies have begun to rely heavily on DevOps methodologies. However, without the proper support systems, you may still end up still falling short of business goals. Your DevOps metrics dashboard is an opportunity to alleviate some of the weight DevOps is expected to carry on its own. A smart dashboard covers all the following bases:
- Measurement of technical performance in relation to business goals
- Easily digestible presentation of data
- Delivery of insights about development and operational processes
- Ability to turn insight into actionable advice
1. Avoid Vanity Metrics
The term “vanity metrics” refers to metrics that look nice but lack functionality. While avoiding these seems like a given, identifying vanity metrics may be trickier than you think. A common trait of vanity metrics is their focus on the outcome rather than the process. Instead of emphasizing the result, a DevOps metrics dashboard must outline each factor that could have contributed to it. The best problem-solving methods don’t just address the problem itself but the conditions that created it.
2. Acknowledge Interdependencies
Since we now know how to spot and steer clear of vanity metrics, let’s look towards the direction we should be heading instead. Your DevOps metrics dashboard needs to highlight leading indicators or the factors that impact your goals. The easiest way to do this is to identify the causal connections between various elements of your business.
For example, when production deployment frequency increases, so does the pace of value delivery. Consider creating dashboard elements that indicate possible areas of influence that may arise from specific actions. Familiarizing yourself with the way one aspect influences another enhances your company’s collective understanding of business processes.
Identify Value Paths
One concept that many companies struggle with is the translation of business goals into technical requirements. DevOps seeks to reduce this struggle by introducing more transparency to the software development life cycle (SDLC), but it’s not an end-all solution. The build of your DevOps metrics dashboard should be capable of answering these five questions:
- Is the current release candidate ready for deployment? If not, what needs to be fixed?
- What improvements can be made to avoid service outages and maintain user experience?
- How can the service or product in use be improved to meet consumer demands?
- Can the speed of value delivery be increased?
- Is the success of our release being measured both in terms of technical quality and business goals?
The questions above are important because they each represent one value path.
Measure and Improve Upon Value Paths
Your DevOps metrics dashboard should be organized according to the four value paths outlined above. These components act as a set of standards that your company can use to maintain focus. DevOps metrics dashboards provide so much insight into so many intricately connected facets that it can be easy to lose sight of the overarching themes. Your value paths act as a roadmap. Accordingly, a metrics tree should be assigned to measure each one.
3. Calculate a DevOps Value Creation Index
Give each metric tree a normalized index score (target = 100). This approach allows us to present metrics with varying measurement units on one unified scale. Index values are simple to judge in terms of ‘good’ (> 100) and ‘bad’, so no subject matter expert is needed to interpret results.
Metric trees can also exist under other metric trees (with an index for each). With this, you can calculate a DevOps value creation index and observe the trends that unfold. Once your metric trees have been organized according to causality, finding the right levers to turn becomes light work.
Seize Machine Learning Opportunities
Modeling casualties through your DevOps metrics dashboard creates an exciting opportunity for leveraging machine learning. Machine learning algorithms can detect fluctuations and patterns far more precisely than the human eye. In addition to making predictions, machine learning turns insight actionable by making data-driven recommendations.
The analytics application also helps us validate our causality assumptions with cold, hard facts (AKA, data). In short, your DevOps Metrics dashboard should provide accurate insights with topical relevance. The strategies above can help you create a dashboard that links the goals of DevOps to broader business goals, like customer satisfaction.
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