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Reimagining CI/CD: AI-Engineered Continuous Integration
AI has the potential to greatly improve the efficiency, accuracy and effectiveness of DevOps continuous integration (CI) practices.
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8 articles

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A release can pass every pipeline check and still leave an organization uncertain about whether to proceed. Security evidence may exist in another system, the recovery plan may be incomplete, and nobody may own the final decision.…
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AI has the potential to greatly improve the efficiency, accuracy and effectiveness of DevOps continuous integration (CI) practices.
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AI can support monitoring and observability by analyzing logs and metrics to predict potential system failures or performance degradation.
Blogs
In my recent article Revolutionizing the Nine Pillars of DevOps with AI-Engineered Tools, I explained that the continuous delivery pillar is an approach where code changes are auto…
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In my recent article Revolutionizing the Nine Pillars of DevOps with AI-Engineered Tools, I explained that design-for-DevOps practices, a DevOps pillar, involves designing software…
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In my recent article Revolutionizing the Nine Pillars of DevOps with AI-Engineered Tools, I explained that AI-engineered tools can help with automating repetitive tasks, improving…
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In my book “Engineering DevOps,” published a few years ago, I classified DevOps into “nine pillars of DevOps best practices” – a comprehensive framework that covered the full scope…
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When I think about the challenges of DevOps transformations, I love the viewpoint expressed by Ryan Harmon, strategic accounts manager at Trace3: “DevOps is a complex maze that has…