Parasoft(link is external) is showcasing its latest product innovations at embedded world Exhibition, booth 4-318(link is external), including new GenAI integration with Microsoft Visual Studio Code (VS Code) to optimize test automation of safety-critical applications while reducing development time, cost, and risk.
According to Puppet's State of DevOps Report 2021, 83% of IT professionals report their organizations are implementing DevOps practices to achieve faster time to delivery, gain increased security of systems and unlock higher business value. No surprise.
What is a bit eye-opening is that those same DevOps teams report that finding the right metrics to monitor and measure success is still a challenge.
Here are a few simple metrics that all DevOps professionals should monitor and measure on a regular basis.
1. Deployment Time
Deployment Time is the time it takes to deploy a release into a development, testing or production environment.
Monitoring deployment time brings focus to areas of redundancy, bottlenecks, and timewasters in the pipeline where innovation of data delivery methods, processes and automation tools has the biggest return.
2. Change Failure Rate
Change Failure Rate is the percentage of failures such as outages or data corruption resulting in degraded services.
By monitoring the change failure rate on a regular basis, DevOps teams gain a better understanding of deployment process efficiency. They can also make data-driven decisions to improve the deployment process.
3. Recovery Time
Recovery Time is time to recovery measures how long it takes to restore a service following an outage or impairment. Measuring this metric is critical to ensure the team recovers quickly from incidents and makes proactive changes in the process to avoid further outages.
4. Release Cadence
Release cadence determines how often and at what frequency a product or update releases to market.
Measuring this metric helps DevOps professionals understand how fast their products are reaching the market in comparison to competitors and when it's time to adopt enhanced automation tools.
5. Lead Time
How long does it take a team to advance from committing code to pushing code successfully out into production? Lead time is a good overall metric of DevOps efficiency and shows whether or not a DevOps team and its tech stack can handle a high volume of requests and still ensure quality.
Measure thoughtfully
DevOps teams need metrics that identify leverage points in the process to speed up deployments. Data can improve deployment processes, especially in comparison to industry standards and competitive comparisons. By establishing simple process metrics and sharing them widely across the team and stakeholders, you'll be well on your way to success.
Industry News
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JFrog is partnering with Hugging Face, host of a repository of public machine learning (ML) models — the Hugging Face Hub — designed to achieve more robust security scans and analysis forevery ML model in their library.
Copado launched DevOps Automation Agent on Salesforce's AgentExchange, a global ecosystem marketplace powered by AppExchange for leading partners building new third-party agents and agent actions for Agentforce.
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JFrog released JFrog ML, an MLOps solution as part of the JFrog Platform designed to enable development teams, data scientists and ML engineers to quickly develop and deploy enterprise-ready AI applications at scale.
Progress announced the addition of Web Application Firewall (WAF) functionality to Progress® MOVEit® Cloud managed file transfer (MFT) solution.
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