DevOps optimization through careful planning, results measuring, and constant refinement can pay dividends
If there’s any one word a DevOps team leader will appreciate, it’s efficiency. DevOps is built on the belief that an agile team spanning development and operation works more efficiently than two teams splitting that load. But one of the core tenets of DevOps is that processes can always improve. When proper DevOps resource optimization can have such an outsized impact on productivity, leaders have a lot to gain by refining their DevOps processes. Here’s how (and why) to do so.
Why Is DevOps Resource Optimization Important?
Although DevOps is designed to streamline product development and operation, it’s still vulnerable to inefficiencies. Tools deployed in one part of the workflow may not work as expected. Engineers may find they struggle with one set of operations but excel at another. Each of these misalignments can create drag on a DevOps team. The slower your team, the slower you can improve your product.
However, if you focus on DevOps optimization, you’ll improve the efficiency of your team over time. The more working hours a DevOps team saves without losing productivity, the greater the return on time invested becomes. Therefore, the more optimized your DevOps team, the greater the ROI of investing in it. For example, automation is a key pillar of DevOps because it saves engineers from constantly performing simple, repetitive jobs such as testing. The process takes even less time if you can deploy automation via a no-code platform like DuploCloud. That helps with DevOps resource optimization by freeing workers up for more productive tasks. To learn more about how DuploCloud can accelerate DevOps, click below.
How Do I Achieve Peak DevOps Resource Optimization?
Of course, not every process investment has an ROI as clear as automation. That’s why team leaders need a framework for DevOps resource optimization that helps them systematically maximize their time savings.
Step 1: Audit Current Resource Allocation
The first step in meeting any challenge is understanding it. For DevOps optimization, that means auditing how your resources are currently distributed. You’ll likely need time-tracking software to figure out how long each task takes on average. While your engineers work, map the projects each works on, including the tools used and the workflows the projects slot into. If you don’t already have process documentation, this is a great time to flesh it out for faster and easier onboarding in the future. The goal here is to create a baseline against which you’ll compare the results of your changes.
Step 2: Identify Pain Points
Once you have reliable data about time usage and a working process map, you should start to see bottlenecks in your DevOps workflow. To get even more detail, you’ll need to talk to your engineers. Are they happy with their tools? Is work flowing in an order that makes sense to them? By collecting this data, you’ll develop a picture of your employee pain points.
But remember: DevOps engineers don’t have the full picture. They may highlight workflow components they find the most frustrating, but these won’t always be the bottlenecks most worth removing. There may be smaller, simpler fixes in your processes that can save time without investing in a new tool, say, or hiring another worker. DevOps resource optimization requires balancing these smaller fixes with larger-scale ones.
Using a combination of employee input and time-tracking data, determine which bottlenecks you’ll address first. Try to address no more than three at a time. Managing the rate of optimization helps you isolate the variables you’re aiming to improve. That makes it easier to measure results and minimizes the chaos of workflow changes.
Step 3: Plan for Upcoming Goals
Now consider the targets you hope to hit in the near future. Will any go through the bottlenecks you plan to address? Wherever they do, determine how you plan to streamline work and make note of any new tools or processes you expect to use. Create a plan for how each workflow change will fit in. The more answers your workers have, the more quickly they’ll adapt, and the faster you’ll get accurate data about your efficiency improvements.
Just as a scientist needs a hypothesis to interpret their findings, you’ll need proper context to understand how your changes have impacted overall productivity. To that end, use historical time-tracking data to estimate how long each task or project will take. Be sure to account for any new changes to the workflow. These may slow down productivity in the short term, but they should eventually streamline development cycles and operational tasks.
Step 4: Implement Changes and Start Measuring
Here’s where the rubber meets the road. As your engineers truck through their workloads, keep an eye on how long they spend on each task. How much time are they saving or losing? How will continued use affect those results? Will developers grow more accustomed to their new tools and workflows, making them more efficient in the long term? Hard data from time-tracking can shed light on these questions, but so can qualitative information from employees. Frontline engineers may even see additional paths to DevOps optimization within the new workflows.
Keep in mind that staying agile means being open to reverting changes. If a process adjustment hasn’t brought about the time savings you planned for, returning to the old way of doing things isn’t a failure. That data will help you continue to refine your DevOps, learning what works for your team and what doesn’t.
Step 5: Do It All Again
Once you’ve collected enough data, you can make calls about which changes to keep, which to roll back, and what needs more attention. Return to the beginning of this process with new information in hand and determine what bottlenecks to address next. Repeat this process often and you’ll build out a DevOps team with an ever-escalating productivity.
Leverage Automation to Drive DevOps Optimization
Automation provides some of the best bang-for-buck DevOps resource optimization available. While it's true building your own automations from scratch can pay dividends, using a no-code/low-code automation platform can deliver results faster and more efficiently. DuploCloud's tools aim to do just that, accelerating infrastructure provisioning by a factor of ten even as it reduces costs by 75% relative to the standard app lifecycle. Compliant out of the box and sporting thorough documentation, the DuploCloud platform makes it easy to achieve peak DevOps optimization. Schedule a demo today to learn more.
