Kubernetes co-creator Kelsey Hightower offers a grounded perspective on AI's impact on engineering careers. He draws parallels between past tech shifts like Kubernetes and current AI trends, emphasizing foundational skills over hype.
A clear, phased roadmap promises to cut through the confusion of DevOps learning, guiding engineers from foundational skills to advanced integration in months. This approach emphasizes practical application and interconnected knowledge for true career value.
A recent Ask Me Anything session provided deep dives into the evolving landscape of AI's impact on DevOps and SRE, alongside practical advice on critical cloud-native tooling and career development. Gain insights into navigating complex technical decisions and leveraging new technologies for enhanced efficiency.
An expert AMA session delves into AI's evolving role in DevOps and SRE, offering practical advice on tools, frameworks, and strategic considerations for engineers. The discussion also covers critical insights into cloud-native deployments, secrets management, and the future of job security in an AI-driven landscape.
As AI agents move beyond experimental autocomplete to indispensable tools understanding entire codebases and managing infrastructure, 2026 marks a pivotal year for broader adoption across development and operations. Discover the practitioner-recommended tools and platforms poised to redefine workflows and unlock significant productivity gains.
Discover the strategic career pivot that took Israel from civil engineering to a Lead DevOps Engineer in the UK within nine months, despite facing visa deadlines and financial constraints. This article details his journey, learning strategies, and insights for breaking into high-demand tech roles.
A new approach tackles Kubernetes' elusive definition of an 'application,' offering a logical grouping mechanism to untangle resource relationships and improve cluster observability.
A recent deep dive illustrates how foundational networking concepts evolve as applications scale from single servers to complex, cloud-native environments. Understand the persistent principles behind modern infrastructure.
An 'Ask Us Anything' session dives into the perceived shift from MCP to 'skills' in AI, alongside the evolving roles of platform engineering and cloud infrastructure. Experts debate the future of developer tooling and AI integration, highlighting critical industry shifts.
Cloud-native experts provided insights on AI's role in policy management, recommended Gateway API over Nginx Ingress, and shared strategies for efficient platform engineering with Backstage, Flux, and Crossplane. The session also touched on CubeCon trends and the synergy between CI/CD tools.
A deep dive into Kagent and KMCP evaluates their ambition to integrate AI agents natively into Kubernetes. We explore the practical challenges and user experience of managing intelligent agents within cloud-native environments.
A new approach leverages AI to automate the entire lifecycle of Kubernetes incident management, promising an end to manual 3 AM debugging sessions. This solution covers detection, root cause analysis, remediation, and validation with a strong emphasis on security.
A new deep-dive evaluation challenges standard LLM benchmarks, revealing critical performance gaps and unexpected leaders for agent-based technical workflows. Discover which models truly deliver for Kubernetes operations, policy generation, and complex troubleshooting under real-world production constraints.
A new approach outlines how to leverage Kubernetes events and strategically deploy AI to transform incident response from manual firefighting to intelligent, self-healing systems. Discover the maturity model for automating detection, analysis, and remediation in production environments.
As AI agents integrate with external systems via MCP servers, selecting an optimal deployment strategy is crucial. This article outlines key methods, from simple local execution to advanced, enterprise-grade cloud and Kubernetes solutions.