Kong announced the launch of the latest version of Kong AI Gateway, which introduces new features to provide the AI security and governance guardrails needed to make GenAI and Agentic AI production-ready.
CloudBees announced new capabilities within CloudBees DevOptics that make it the only solution purpose-built to provide real-time value stream visibility and insights to monitor, measure and manage DevOps performance across the organization.
The new functionality solves a major issue organizations face when adopting DevOps practices: They are investing in new ways of delivering software, but at the same time struggling to understand the impact their investment has on the business.
Measuring the same set of key indicators popularized in the annual DevOps Research and Assessment (DORA) State of DevOps Report, CloudBees DevOptics gives executives, managers and practitioners the ability to better understand DevOps performance and evaluate the impact of DevOps investments.
The four key metrics called out in the 2017 State of DevOps Report are: Deployment Frequency, Mean Lead Time, Mean Time to Recover and Change Failure Rate. These metrics provide clear, objective measures of DevOps effectiveness to identify problem areas, make changes in processes and automation, and continuously improve the way teams work.
- Deployment Frequency (DF): The frequency of successful deployments identified in a value stream, or the end-to-end software delivery pipeline. This metric should trend up.
- Mean Lead Time (MLT): The mean time it takes from code commit to code successfully running in production. This metric measures process efficiency, helping to identify bottlenecks or breakdowns. It should trend down as automation is implemented and processes are improved.
- Mean Time to Recover (MTTR): The mean time it takes to fix failures when they occur. This metric should trend down, over time, as improvements to recovery processes are made.
- Change Failure Rate (CFR): The percentage of unsuccessful pipeline runs caused by introducing new changes. An increasing failure rate reveals process issues. This metric should decline over time.
“Identifying the right performance indicators and committing to a streamlined measurement process can make the difference between a successful and a less than optimal DevOps implementation,” said Dr. Nicole Forsgren, founder and CEO, DevOps Research and Assessment and an author of the State of DevOps Report. “Having the ability to track these metrics and make improvements is what DevOps is all about. The end result is improved software delivery across the organization.”
Additionally, CloudBees DevOptics includes new monitoring capabilities and associated metrics that provide a central shared services team one view into all software delivery activity. Monitoring helps to identify value stream waste, enabling it to be eliminated and improving the software delivery process. With the monitoring data, you can do things like:
- Anticipate high activity times to throttle capacity and keep teams productive
- Uncover restrictions to improve feedback cycle time and reduce build costs
- Balance cluster workloads to keep jobs running
- Identify low periods of activity that are ideal for maintenance or upgrade work, reducing impact on in-process development work
Along with measuring and monitoring value stream efficiency, CloudBees DevOptics helps organizations improve software delivery operations. CloudBees DevOptics connects teams, tools and processes to enhance collaboration and ensure consistency across the entire software delivery life cycle.
“While organizations appreciate the value of DevOps in principle, they haven’t had a good mechanism to measure its efficiency,” said Ben Williams, Senior Director, Product Management, CloudBees. “CloudBees DevOptics collects, analyzes and presents important indicators of DevOps performance, giving organizations insights they can use to improve software delivery processes, drive more value and maximize returns.”
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