Operations | Monitoring | ITSM | DevOps | Cloud

For IT and SecOps teams, the challenge is not a lack of alerts. It is the sheer volume of noise coming from monitoring tools, security systems, and support channels. Trying to manage this volume manually is not just slow; it’s a recipe for mistakes, team burnout, and critical system failures.

Last month I focused on adding Telegram alerts to OnlineOrNot, making scripted browser checks generally available, and making it clearer to understand why checks fail.

TL;DR Picking the right log management platform in 2026 comes down to three things: how much operational overhead you can absorb, how much AI automation you need, and what you’re willing to spend.

HAProxy 3.4 is a milestone release that significantly advances HAProxy’s legendary flexibility, performance, security, reliability, and observability. Dynamic backend management simplifies integration with modern architectures, memory efficiency improves across a broader range of workloads, native cryptographic operations at the proxy layer open new possibilities for API security architectures, and OpenTelemetry support makes HAProxy a first-class participant in distributed tracing pipelines.

One of the important offerings of the RISC-V Instruction Set Architecture (ISA) is the ability to customize and extend the base instruction set. An initial reaction to hearing this is often to worry about software portability and compatibility, since if every RISC-V CPU offers a slightly different set of instructions, software won’t be portable.

Two things shipped this week. One is for the MSPs who manage certificates on behalf of other companies. The other lets you run the shorter 45-day renewal cycle today.

Enterprise AI has crossed an inflection point. The model problem is largely covered. What remains unsolved is the operational impact: how to run AI inference and agentic processes continuously, reliably, and at a cost that doesn’t cancel out the value. Most enterprises are discovering this the hard way. GPU utilization dashboards show 80%. Actual compute efficiency is half that. Token demand is compounding at 200-500% annually as agents multiply every action into dozens of model calls.

Repetitive work is what slows down most service desks, not a lack of people. Most IT teams spend their day handling repetitive work like password resets, ticket routing, access approvals, and standard service requests. This creates constant backlog pressure, slows resolution, and increases avoidable errors. Adding more people does not solve the underlying issue. ITSM automation addresses this by moving routine, rule-based tasks into automated workflows.