Skip to main content
DevOps icon showing cogs

This post is from the XebiaLabs blog and has not been updated since the original publish date.

Last Updated Jun 07, 2017 — DevOps Expert

8 Mistakes You Can Avoid Using DevOps Intelligence


You took the plunge into DevOps, starting with automating part of your software delivery process. The results have been great—less manual work, more efficiency. The improvements were so strong that, a few months later, you started scaling your DevOps operation to integrate tools, processes and teams across the organization. But things could still be better. Delivery could be faster. You’re still wasting too much time fixing things in production. And, you missed a deadline—understandable given that, with so much going on, it can be hard to see the forest for the trees.

But these problems are not inevitable and may simply be signs that it’s time to take the next step toward full DevOps maturity…analyzing your end-to-end delivery pipeline and using the intelligence gathered to make your process even better. Imagine the impact of visualizing, analyzing, and integrating detailed information in areas like these… across all the tools in your release pipeline:While you might be able to search for each individual piece of information in the list above, DevOps Intelligence synthesizes these kinds of metrics into actionable insight, for example: business goals as a function of reduced time to delivery; failed releases decreasing as a function of deployment frequency; change volume as a predictor of bad outcomes; or success rate as a correlation of adopting certain tools and technologies. Let’s look at how DevOps Intelligence can help you avoid a few common problems with your software delivery lifecycle and significantly improve operations across the enterprise.

1. Missed Deadlines

Missed deadlines happen occasionally, but they don’t have to be the norm. DevOps Intelligence lets you uncover the components of your pipeline that slow down releases and put them at risk—things like tasks that take too long or handoffs that never happened. For those dealing with the complexities of managing dozens of simultaneous releases, DevOps Intelligence helps you quickly spot when a release is in trouble so you can fix it and stay on schedule. And, when the release is done and out the door, DevOps Intelligence lets you figure out where you need to improve so future releases are even faster.DevOps Intelligence spans time to provide deep actionable insight into your software delivery process.
DevOps Intelligence spans time to provide deep actionable insight into your software delivery process.

2. Wasted Money and Resources

You put a lot of effort into planning projects and finding the right people for your team. But too often, your resources are misdirected because you’re focused on the wrong things. Know which tasks would most benefit from automation. Get cross-project views across tools and releases so you can find and fix the biggest gaps. Know who did what and when so you can have the most effective release retrospectives. The real-time visibility and analytics capabilities that DevOps Intelligence offers show you exactly what happened and where waste occurs in your processes. With this insight, you can focus your efforts on the right areas and assign your staff in a way that makes the best use of their talent—and your budget.

3. Chaotic Delivery Pipeline and Tired Teams Working Weekends

If you don’t have visibility into when and where problematic activity is happening in your delivery pipeline you might be inviting trouble. For example, can you quickly identify when your development team is overloaded? When delays are occurring? When tasks are failing…as early in the process as possible? Avoid fire-fighting and the working weekends that go with it. A good DevOps Intelligence tool will make issues clearly visible and allow you to adjust your planning or process to prevent your team from being overwhelmed by changes, smoothing the flow of work and preventing last-minute chaos.


Release Pipeline Orchestration 

An Essential Practice for Continuous Delivery at Enterprise Scale

Learn how release pipeline orchestration solutions help even the largest of enterprises efficiently manage and optimize their software release pipelines.

4. Lost Revenue…or Worse

How long does it take to get value into your customers’ hands? If your processes are slow, you could be sacrificing revenue, or worse, giving customers a reason to churn. By measuring the duration and activities across your pipeline—in the development, testing, and release phases—you can find bottlenecks so you can fix them and get insight into where you can improve. Your releases move faster so you realize revenue sooner. As well, a good DevOps Intelligence solution provides insight into customer usage of a new feature so you know what to build in upcoming releases to maximize revenue.

5. Failed Releases and Blowups in Production

Are you discovering task failures and delays late in the process when they’re expensive to fix, or worse…are your releases failing in production? If so, you’re probably struggling with major blind spots in your pipeline. DevOps Intelligence changes that. It lets you see what’s happening across hundreds of releases in real-time…and benefit from predictive analytics capabilities that assess risk and proactively let you know which releases are most likely to fail before they get too far along. With DevOps Intelligence, you’ll know what kind of events across systems are failing and how frequently so you can determine where to focus to improve reliability. You can analyze your pipeline across the delivery lifecycle to prevent production blowups and optimize processes for future releases.

6. Lack of Alignment with Business Goals

According to DevOps expert Gary Gruver, “A full 50% of new software features are never used or don’t meet their business intent.” Many companies spend a lot of time designing features but very little figuring out their impact and whether they’re meeting the goals of the business. Which features are your customers using? How are they using them? Are you getting the intended results? DevOps intelligence uses feedback loops and ongoing measurement of release outcomes so you get information about how your customers are using your software as you’re developing it. This insight allows you to focus your efforts on features that provide the highest value to your customers.

7. No Executive Support

So, you pitched executive management on a new DevOps tool or initiative but they rejected your proposal. A common problem among technical people is that they talk to management using technical instead of business terms. DevOps Intelligence helps you understand the true cost of application delivery by allowing you to easily see the entire pipeline, from development through production. See which sections are working well, which are costing money and time, and which you can most easily improve. Deep insight into your processes provides the basis for accurately estimating the cost of waste and showing management how the changes you’re proposing can vastly increase ROI.

Learn More About DevOps Intelligence

As the next step in improving software delivery, DevOps Intelligence is essential for companies that want to stay ahead of the competition. To learn more, or to find out how to implement DevOps Intelligence yourself, check out these additional resources:

More from the Blog

View more
Ascension Launch Banner
Apr 26, 2022

Get ready for peak performance with’s newest AI-Powered DevOps Platform Ascension Release

Today, is excited to announce our latest AI-Powered DevOps ...
Read More
Jan 24, 2022 Value Stream Delivery for SAFe®: The key to amazing business outcomes

The Scaled Agile Framework (SAFe) is the world’s leading framework for ...
Read More
Dec 09, 2021

How SaaS and cloud-based solutions helped the U.S. Department of Veterans Affairs achieve digital transformation

Modernizing legacy systems was an ongoing goal for the U.S. Department ...
Read More
Nov 29, 2021

Increase velocity and reduce risk with AI and machine learning

Artificial Intelligence (AI) and machine learning (ML) have proven use ...
Read More
Contact Us