Netris raises $15M Series A from a16z to help AI neoclouds go live faster
Netris provides software that runs on network switches, and offers a platform that helps neocloud operators reduce the time it takes to go live.
InfoWorld AI·
Key takeaways Backstage solved the portal problem, not the platform problem. A portal organizes catalogs, documentation, and templates. A platform owns deployments, environments, policies, and runtime operations. Backstage assumes that the execution layer exists beneath it. Point-to-point integrations become a maintenance burden. Many organizations end up with a “messy middle” where Backstage is connected directly to CI/CD, GitOps, Kubernetes, and observability tools through custom wiring that’s fragile and hard to evolve. Abstractions are the interface between developers and infrastructure. Developers work with components, endpoints, and dependencies. Platform engineers work with environments, pipelines, and component types. The platform compiles both into Kubernetes resources. A control plane bridges the gap. It sits between the portal and runtime, compiling abstractions into infrastructure, enforcing policies consistently, reconciling drift, and aggregating runtime state back to the
Read full articleNetris provides software that runs on network switches, and offers a platform that helps neocloud operators reduce the time it takes to go live.
Binance's chat upgrade enhances user interaction, potentially transforming the platform into a comprehensive hub for social and financial activities. The post Binance upgrades chat with new features for easier user connectivity appeared first on Crypto Briefing.
By Katja Nikolaus, Co-Founder, JUNE. Two forecasts. Two opposing verdicts. Published within weeks of each other, each delivered with equal confidence. The first: the market ...
When Kubernetes first came onto the scene, it was a major turning point, a revision of the infrastructure and operations space that transformed the way developers and ops personnel build, deploy, and maintain applications in the cloud. It has since become the clear standard for how modern applications are built and operated. As the CNCF […]
In hardware, when you ship something broken, the consequences are severe and often irreversible. That’s the world I worked in for years, in verification roles at Mellanox and later at Alibaba. The stakes forced the industry to build a rigorous verification culture. You proved designs worked before they left the building. In software, verification disciplines look like CI/CD pipelines, static analysis, canary deployments, and observability. But those systems were built around code written at human speed, with human comprehension baked into the process. AI code generation has broken that assumption. The writing process can no longer be trusted to carry institutional knowledge and judgment into the codebase. The industry is being pushed toward the kind of rigorous verification culture that hardware engineers have practiced for decades. Enterprises are generating code faster than at any point in history. Google recently disclosed that 75% of the company’s new code is now AI-generated. Meta
You know the meeting. The board wants an AI agent strategy by end of quarter. Someone on the leadership team has read a McKinsey report. You’ve been voluntold to build the platform. The slide deck says “AI-native.” The acceptance criteria are vague. Somebody mentions LangGraph, and somebody else says, “We’ll just wrap it ourselves.” You […]
You know the meeting. The board wants an AI agent strategy by end of quarter. Someone on the leadership team has read a McKinsey report. You’ve been voluntold to build the platform. The slide deck says “AI-native.” The acceptance criteria are vague. Somebody mentions LangGraph, and somebody else says, “We’ll just wrap it ourselves.” You […]