Contributed Content
GitOps Implementation at Enterprise Scale — Moving Beyond Traditional CI/CD
Sumanth Kadulla | | ArgoCD, change traceability, CI/CD migration, CI/CD reliability, cloud native delivery, configuration drift, declarative infrastructure, deployment automation, deployment rollback strategy, DevOps at scale, devsecops, dora metrics, gitops, GitOps adoption, GitOps security, infrastructure as code, Kubernetes continuous delivery, platform engineering, policy as code, pull-based deploymentsTraditional CI/CD pipelines hit scaling limits. Learn how GitOps improves deployment reliability, security, and DORA metrics—and what it takes to migrate successfully ...
When DevOps Meets the Cloud: A Real-World Transformation Story
Yashwanth | | CI/CD Automation, cloud migration, DevOps transformation, infrastructure as code, observabilityA real-world DevOps and cloud transformation story showing how automation, observability, and cultural change improved reliability and delivery ...
Why AI Makes Requirements a Runtime Artifact
Tom Hollowell | | AI behavior, AI Governance, AI requirements, continuous verification, MLOps, model drift, production monitoring, requirements traceability, runtime constraintsIn traditional software, requirements are static design-time artifacts. In AI-enabled systems, they must be continuously observed and enforced in production. Learn how AI collapses the boundary between design-time and runtime, shifting requirements ...
What to do About AI’s Forced Rethink of Reliability in Modern DevOps
Leo Vasiliou | | Agentic Workflows, AI monitoring, AI observability, AI reliability, AI. analytics, business impact, CDNs, customer churn, devops, digital experience, experience-driven resilience, incident response, internet stack, KPIs, latency, LLM applications, model drift, monitoring tools, NPS, observability, performance, performance degradation, reliability, reliability strategy, revenue, SaaS, site reliability engineering, SLIs, SLOs, SRE Report 2026, Third-party Dependencies, trust, uptime, user experienceAs systems become more distributed and AI-driven, traditional uptime metrics are no longer enough. The 2026 SRE Report shows how reliability is shifting toward user experience, speed, and business impact, and how ...
Test Automation Strategy for Growing Software Teams
Build a scalable test automation strategy that improves release speed, reduces defects, and supports growing software teams ...
What a ‘Good Plan’ Really Means for AI Coding Agents
Michael Parker | | Agile methodologies, AI coding agents, application delivery, CI/CD pipelines, coding efficiency, context retention, continuous improvement, Engineering best practices, error management, modernization, planning in development, software development, task execution, validation processesExplore how AI coding agents are transforming software development. This article discusses the importance of clear objectives, runnable tasks, and continuous validation in planning to ensure that the transition from idea to ...
Tool Fragmentation is Breaking Delivery Context — Here’s What Teams are Learning
Arul Watson | | access control, application security, automation, CI/CD pipelines, Cloud Security, credential exposure, Cybersecurity, devsecops, incident response, risk management, secrets management, security best practices, supply chain security, token managementExplore the emerging crisis in application delivery caused by tool fragmentation in modern software development. This article discusses the need for semantic interoperability, context preservation, and a shift from linear pipelines to ...
Secrets Management Failures in CI/CD Pipelines
Johnbosco Ejiofor | | access control, application security, automation, CI/CD pipelines, Cloud Security, credential exposure, Cybersecurity, devsecops, incident response, risk management, secrets management, security best practices, supply chain security, token managementExplore the critical role of secrets management in CI/CD pipelines and its impact on cybersecurity. This article highlights the risks of credential exposure, the importance of implementing strong security practices, and how ...
Prompt Injection Isn’t Just a Chat Problem — It’s a DevOps Threat
Prompt injection is evolving into a serious DevOps threat, enabling AI agents to misuse tools, leak secrets and execute unauthorized actions unless governed with least privilege, sandboxing and human approval. ...
Forget the Vibe-Coders, We Need to Support Responsible AI-Assisted Development
Guillaume Moigneu | | AI in development, automated security, build pipelines, developer roles, Human Oversight, orchestration, responsible AI use, software design, Software infrastructure, spec codingWhile AI tools are increasingly used in development, they should enhance rather than replace human input. Developers must shift from merely writing code to orchestrating and validating AI-generated code. This 'spec coding' ...
SRE vs. DevOps is a False Choice: Here’s the Unified Model That Works
Michael Chukwube | | application performance, automation, collaboration, continuous integration, culture of learning, devops, incident response, platform engineering, reliability metrics, site reliability engineering, software development, SREDevOps and site reliability engineering (SRE) are complementary strategies that enhance both speed and reliability in software development. While DevOps focuses on collaboration and automation to break down silos between development and ...
Beyond Automation: How Generative AI in DevOps is Redefining Software Delivery
Albert Hilton | | AI risks management, automation, Code Generation, data privacy, DevOps transformation, DevOps workflows, GenAI in DevOps, generative AI, human-in-the-loop, productivity gains, software development, technical debtGenerative AI (GenAI) is revolutionizing DevOps by automating manual tasks, enhancing productivity, and reducing errors. By integrating GenAI, teams can streamline workflows and democratize expert knowledge. However, managing risks such as data ...
