Operations | Monitoring | ITSM | DevOps | Cloud

When a critical incident triggers, there’s no time to figure out who to call. That decision needs to be made well before the incident arrives. A dedicated escalation policy for critical incidents gives your team a clear path to follow the moment things go wrong, rather than leaving it to whoever happens to be around. This guide covers the key decisions involved in building that policy.

This is a guest post from James Hemson. For years, the test data management market has told smaller companies the same story. Test data is complex. You need consultants. Compliance is expensive. Expect a six-month implementation before you see any value. At Redgate we think that's wrong. And we think it's wrong by design. Complexity creates services revenue. It creates switching costs. Most vendors have built their businesses around this.

L1, L2, L3 is one of the most common ways to structure an escalation policy. The idea is simple: an incident triggers and lands with a first responder. If it needs more attention, it moves up the chain to someone with more expertise. This guide explains how each tier works, when this structure makes sense, and what to keep in mind when setting one up.

2025 was the year that RISC-V readiness gave way to RISC-V adoption. It’s been quite a journey. What began years ago as early architectural exploration and enablement has matured into real silicon, systems, and deployments. In particular, RVA23 provides a stable and predictable baseline we can align on with our wider ecosystem of partners. At Canonical, we’re committed to making RISC-V a viable option for anyone who wishes to adopt it.

Can you create an audit trail for what your AI agent actually did, and enforce rules about what it was allowed to do? Here’s what I found after spending a session wiring the two tools together.

Whether you’re in finance or engineering, you know keeping your customers happy is the key to success. That means, your SaaS product or service needs to be available, reliable, and cost-effective virtually all the time. On that note, you can determine how stable and high-performing your service is depending on whether you use On-Demand or Spot Instances. Pricing, capacity, and flexibility will also vary depending on which of the two instances you choose.

For a CTO, "four nines" represents a commitment to keeping production revenue live with less than 0.01% of total downtime per year. As AI workloads move from pilot projects into core production services, the reliability requirements for infrastructure have shifted. AI agents, RAG pipelines, and automated LLM workflows depend on a consistent platform state.