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metrics, agents, ai, cloud-native, cloud native, project, istio, ambient, architecture, modules, cloud native, CCoE Kubernetes Virtana CrowdStrike cloud native

AI Agents Power Cloud-Native Transformation

AI agents are redefining cloud-native development by embedding intelligence into DevOps workflows — optimizing pipelines, automating debugging, and accelerating release cycles. Experts like Promevo CTO John Pettit explain how these autonomous systems ...

Nathan Eddy | October 30, 2025 | AI agents, AI code reviewer, AI in DevOps, AI in software engineering, AI observability, AI-powered debugging, autonomous systems, CI/CD optimization, cloud infrastructure management, cloud-native transformation, DevOps automation, intelligent automation, platform engineering, shift left security, software delivery lifecycle (SDLC)

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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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