Nathen Harvey: Scale Brilliance, Not Bottlenecks: Building Platforms for the AI-First World
Watch Nathen Harvey's full talk at O11yCon 2026, Honeycomb's observability conference, and enjoy Christine Yen's intro as well.
Operations | Monitoring | ITSM | DevOps | Cloud
The Place Where Modern Operations & Technology Come Together
The latest News and Information on APIs, Mobile, AI, Machine Learning, IoT, Open Source and more!
Mock your backend dependencies in 2 minutes
Stop letting broken downstream dependencies kill your workflow. Use proxymock to record backend data and inbound calls, then flip on a mock whenever a system goes offline. You can even replay traffic to test your code changes and ensure your endpoints are still working perfectly.
Stop Letting Bad Data Break Your App #speedscale #mocking #api #vibecoding #devops
Click the link below to mock your backend dependencies in under 2 minutes.
Five Principles of an Accountable AI Agent Network: How to Evaluate Any Governance Platform
The first post in this series argued that AI agent governance hasn’t kept pace with deployment. The second laid out the five pillars of accountability, and what is required. The third walked through why network policies, API gateways, MCP/A2A protocols, DIY security patterns, and Role-based Access Control (RBAC) each leave critical accountability gaps. So what does good look like? The five pillars define what AI agent accountability requires.
A field guide to the agents in your cluster
You know every service in your cluster by name. You know which team owns each one, what it talks to, how it scales, where its logs go. The agents are a different story. That’s not a criticism, it’s an observation, and it’s one we keep running into. Every company we talk to is shipping agents of some kind, from scales of 10s to 1000s. Customer service bots that field tier-one tickets. Internal copilots that draft emails and summarise meetings and write the boring half of every PR.
Balance AI innovation and governance with Sumo Logic AI and ML apps
AI is changing how teams work. Developers are generating code faster, security teams are automating investigations, and employees across the business are using AI tools to accelerate research, content creation, and decision-making. But this adoption comes with a catch. As usage explodes, it introduces a new set of security risks: a rapidly expanding attack surface, faster attack timelines, potential data exposure, and an alarming lack of visibility into how these tools are being used.
The Inference Paradox: How Split-Brain LLMs Are Killing Your GPU ROI
During the Toronto KCD (Kubernetes Community Days), I attended an insightful talk on AI resource optimization that highlighted a staggering Gartner study: “AI infrastructure is adding $401 billion in new spending this year alone. Yet, real-world audits tell a much darker story, revealing that average GPU utilization in the enterprise is stuck at a dismal 5%”. While many people in the audience were shocked by that number, the data didn’t come as a surprise to us.
Episode 12 - Human Choices in an AI Future (Part 2)
What does it actually take to thrive in an AI-driven world, not just survive it? In part two of his conversation with Karthik Ravindran, General Manager of Enterprise Data and AI at Microsoft, host Tom Stoneman digs into the human qualities that no model can replicate.
The Integration Era: Why Standalone SaaS Tools Are Losing Ground
For years, the standard playbook for building a corporate technology stack was simple. Managers bought the single best tool for every specific job. This created an environment filled with isolated applications that did one task perfectly but failed to communicate with anything else around them. Today, that model is breaking down because businesses can't afford the hidden costs of disconnected data.
Top Train Ticket Booking App Development Companies in the USA
Rail booking platforms have become one of the most demanding categories in modern software development. Across intercity service with Amtrak and Brightline, commuter rail across MTA, MBTA, SEPTA, Caltrain, and BART, and the broader shift to GTFS-driven mobile ticketing, US companies are launching products that must handle real-time schedule data, multi-leg journey planning, multi-operator integrations, and mobile ticketing through Apple Wallet and Google Wallet - all under federal ADA compliance requirements.