By Darren Patterson | Trace3 Sr Director of Platform Engineering, Digital
Quantifying the Impact of Processes, Tools, and AI Solutions
Measuring developer efficiency and quantifying the benefits of new processes, tools, and AI solutions are vital for staying ahead of the curve. Engineer Insights products offer tools designed to provide clear, actionable data that can transform how development teams operate.
Measuring Developer Efficiency
One of the primary capabilities of Engineer Insights products is their ability to track and analyze DORA, SPACE, and other metrics related to developer productivity. These metrics include change lead time, code deployment frequency, developer satisfaction, communication and collaboration, failures in new releases, the frequency and size of code commits, and the time taken to resolve bugs (failures) or deploy new features to your clients. By visualizing these data points, managers can identify bottlenecks, areas for improvement, and opportunities for improving the developer experience.
"Setting metrics as a goal… increases the likelihood that teams will try to game the metrics."
https://dora.dev/guides/dora-metrics-four-keys/
DORA has some great guidance on pitfalls to avoid when adopting software delivery metrics in your environment. Metrics are valuable, but leaders should avoid the common pitfall of setting metrics as a goal for development teams.
Quantifying the Benefits from Changes
Implementing new development processes and tools can be challenging, but Engineer Insights products make it easier to assess their impact. We have seen a large number of new AI solutions:
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Coding assistants like Github Copilot, Windsurf, Cursor, Augment Code, and others
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AI enhanced observability solutions
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Intelligent code review systems
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AI-driven debugging solutions
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Even the advent of "vibe coding"
"[GitHub CoPilot's] AI pair programmer helps developers code up to 55% faster and made 85% of developers feel more confident in their code quality"
These solutions all promise improved efficiency, but every team, company culture, and platform environment is going to have unique aspects that will affect your return on investment (ROI). Measuring impact and outcomes in your environment is the best way to demonstrate ROI.
Many organizations can also benefit significantly from DevOps and Platform Engineering practices. For instance:
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Build and provide Golden Paths for developers to consume
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Implement an Internal Developer Portal (IDP) for developers to use for self-service
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Fully automate provisioning of developer environments using Infrastructure as Code (IaC)
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Automate and enhance the efficiency of approvals to reduce developer wait times
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Optimize your CI/CD experience to reduce developer toil
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Standardize your observability tools and processes for all developers and DevOps/Ops to consume
Again, measuring the impact of these solutions and changes is important to demonstrate ROI and to avoid changes that do not contribute to tangible improvements. Even if you are just starting to implement agile methodologies, continuous integration (CI), continuous delivery (CD), or automated testing frameworks, the reports provided by an Engineer Insights platform can quantify improvements in efficiency, code quality, and team collaboration. These insights enable teams to make data-driven decisions, ensuring that each new platform change contributes meaningfully to the overall development goals.
Conclusion
In the time since I started writing this article, I have come across a lot more discussion about how Platform Engineering teams have the opportunity to be AI enablers, helping establish an AI center of excellence/community of practice, and to remain flexible while establishing best practices. I think it is a perfect time for platform teams to start measuring what matters! It is critical for leaders to invest in AI where they get the greatest return, instead of using qualitative measures for making decisions.
Engineer Insights products empower software development teams with the data they need to enhance efficiency, validate new processes, and embrace innovative tools and AI solutions. By leveraging these insights, teams can not only keep pace with industry standards but also create new business value through faster releases of solutions to their clients.
"Even with existing AI capabilities, organizations have years of implementation work ahead to fully realize the potential benefits. The focus should be on extracting practical utility from these tools."
Please reach out to us if you would like assistance adopting effective AI solutions for your DevOps, SRE, and Platform Engineering teams.
Darren possesses over two decades of experience in diverse areas such as automation, public and private cloud infrastructure, security, monitoring, observability, high-performance computing (HPC), artificial intelligence (AI), Site Reliability Engineering (SRE), DevOps, and Platform Engineering. Complementing his robust technical background in Computer Science, Darren holds an Executive MBA and has extensive consulting and leadership experience. In his leisure time, Darren enjoys exploring the Rocky Mountains, fly fishing, camping, and hiking with his wife and three children.