Operations | Monitoring | ITSM | DevOps | Cloud
The Place Where Modern Operations & Technology Come Together
The latest News and Information on DevOps, CI/CD, Automation and related technologies.
Escape VMware lock-in for good
Leave the lock-in of VMware behind. Migrate legacy workloads to Kubernetes-native infrastructure with air-gapped security, GPU passthrough, and consistent Terraform APIs.
AI Asked Our General Counsel Anything. She Didn't Hold Back.
What happens when AI interviews a tech leader? You get unexpectedly honest answers. Harness General Counsel Hanna Steinbach sat down with ChatGPT — and skipped the corporate script. From the realities of parenting while leading a legal team at a high-growth startup, to the daily habits that keep her grounded, this is the kind of candid leadership perspective you rarely see. Oh, and she's definitely the person sprinting to the gate right as boarding starts.
Automated Release Management: From CABs to Continuous Delivery | Harness Blog
The thing with Change Advisory Boards is that the intent was always good. Get smart people in a room, look at the evidence, and make sure nothing catastrophic goes out the door. In theory, that's hard to argue with. It doesn't scale in practice. Things happen between meetings. Teams rush to hit the window. The CAB meeting may not catch every risky deployment, but at least everyone can feel good about the process before the incident happens. Automated release management asks a different question entirely.
LLM Observability: Lessons From MLOps w/ Maria Vechtomova (Cauchy)
For nine years, Maria Vechtomova was shouting about monitoring. Nobody cared, until LLMs arrived. As co-founder of Cauchy, Databricks MVP, and one of the most followed voices in MLOps, Maria has watched the field evolve from hand-built experiment trackers to today's flood of observability tools, and her central claim might surprise you: globally, nothing has changed. The fundamentals are the same: track your code, data, and models so you can roll back when something breaks.
What are the benefits of decentralized AI infrastructure?
Have you ever considered how you can utilize artificial intelligence (AI) without sacrificing control over your data and autonomy? As we continue to navigate the changes of AI in the 21st century, it is important to understand how decentralized AI infrastructure can empower individuals and organizations to harness the potential of AI while maintaining sovereignty over their data and decision-making processes.
The RAM Crunch: How UK Businesses Can Weather the Global Memory Shortage
Tech headlines are being dominated by the perfect storm that has led to a global shortage of Random Access Memory (RAM). As the short-term, temporary memory that handles data for processing and applications, RAM - and specifically Dynamic Random Access Memory (DRAM) - is a foundational business technology.
Claude Code Sandbox: The Complete Guide to Sandboxing AI Agents in Production
How to sandbox Claude Code, Codex, and other AI coding agents for production use. Compare local Docker, Daytona, E2B, and Qovery approaches - with architecture diagrams and real-world examples. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.
#058 - The Future of AI and Platform Engineering with Blake Sherwood (Smarsh)
In this episode, special guest Blake Sherwood joins the show to discuss his unique career trajectory from tourism and coal mining to leading massive-scale Kubernetes migrations. Blake shares insights from his experience managing petabytes of data in high-compliance environments, delving into the practical realities of integrating AI into enterprise workflows and observability systems.
Your Metrics Look Fine. Your Engineers Are About to Quit.
Developer experience predicts what's coming 3 to 6 months before it shows up in your delivery metrics. So why are most engineering leaders measuring it last? In this session, GitKraken VP of Developer Research Jeremy Castile breaks down what developer experience (DevX) actually is, how to measure it across 6 key dimensions, and how it connects to velocity, code quality, and AI impact data your team is already tracking.