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CNCF Elevates Platform for Managing Bare Metal Servers Running Kubernetes

CNCF elevates Metal3.io to incubation, advancing open-source automation for managing Kubernetes clusters on bare-metal infrastructure ...

Mike Vizard | September 3, 2025 | AI workloads bare metal, Baremetal Operator BMO, cloud-native infrastructure automation, Cluster API Provider Metal3 CAPM3, CNCF incubation project, CNCF open source projects, Ericsson Metal3, Ironic framework, Kubernetes automation, Kubernetes bare metal, Kubernetes infrastructure management, Kubernetes on bare metal, Kubernetes operators, Metal3.io, Red Hat Metal3

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Modernizing Manufacturing: How to Move from Legacy Infrastructure to Cloud-Ready Operations

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ADR vs. EDR: Why EDR Isn’t Enough in the AI Era

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Software Testing and Test Automation

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Which of the following best describes your involvement in software testing or test automation at your organization? (Select one)*
- I actively perform software testing or test automation
- I manage or lead software testing or QA teams
- I make decisions about testing tools, frameworks, or automation strategy
- I do both hands-on testing and make strategic/tool decisions
- None of the above

How much of your organization's software testing is still performed manually today? (Select one)*
- Almost all
- More than half
- About half
- Less than half
- Almost none

How much effort does your team spend maintaining existing automated tests compared to creating new test coverage? (Select one)*
- Mostly maintaining existing tests
- More maintenance than new coverage
- About equal
- More new coverage than maintenance
- Very little maintenance required

How much has AI-assisted software development increased the pressure on your testing teams over the past 12 months? (Select one)*
- Significantly increased pressure
- Moderately increased pressure
- Slightly increased pressure
- No meaningful impact yet
- Unsure

What is the biggest obstacle preventing your organization from expanding software test automation and adopting agentic testing? (Select one)*
- Automated tests are too difficult or costly to maintain
- Release cycles move too quickly to keep tests current
- Too much coding or scripting expertise is required
- Testing tools and frameworks are too fragmented
- Lack of time, budget, or staffing
- Difficulty proving business value or ROI
- Insufficient AI or intelligent automation capabilities

Which improvement would create the greatest business impact for your organization over the next 12 months? (Select one)*
- Reducing manual testing effort
- Reducing automated test maintenance
- Accelerating release cycles
- Expanding test coverage across more technologies
- Consolidating testing tools and frameworks
- Enabling more non-developers to automate testing
- Improving the resilience and adaptability of automated tests

Which statement best reflects your organization's current perspective on AI-powered or agentic software testing? (Select one)*
- We are actively evaluating or adopting AI-powered testing approaches
- We are interested, but still assessing practical value and trust
- We believe current automated testing approaches are sufficient
- We are primarily focused on improving existing automation before adopting AI-assisted testing
- We have not yet explored AI-powered testing in a meaningful way

How important is the ability to execute continuous, largely autonomous software testing with minimal human intervention ("lights-out" or "dark factory" testing) to your organization's future software delivery strategy? (Select one)*
- Critical strategic priority
- Important, but still early-stage
- Somewhat important
- Low priority today
- Not relevant to our organization
- Unsure

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