Operations | Monitoring | ITSM | DevOps | Cloud

You’ve almost certainly seen them… In the forest, rummaging through a dumpster, in poorly aging millennial memes. Raccoons are ubiquitous and endlessly entertaining creatures. YouTube and TikTok are full of videos documenting their clever antics and escapades. One such intrepid raccoon gained fame for making their way to the most unlikely places, from liquor stores to karate studios.

During high-priority incidents, SRE teams frequently lose critical time switching between monitoring platforms and ticketing systems. Context switching like this forces engineers to manually update incident states by copying and pasting data. The inevitable result is increased risk of information gaps and slower Mean Time to Recovery (MTTR).

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.

To succeed in the AI era, customers need fast, easy access to security solutions that can harness the power of agentic AI and deliver business outcomes. They need seamless access to their data for faster threat detection, simpler incident response, and reduced risk. They need technology vendors to work together and not in silos.

Achieving end-to-end observability for applications is a top priority for organizations today, but instrumenting for both frontend and backend monitoring can be a significant hurdle. What complicates matters is that the SREs and DevOps teams responsible for deploying monitoring tools typically don’t own frontend code or have the context needed to safely modify it.

Middleware is evolving beyond invisible plumbing into a strategic Command Center. The future demands unified management, predictive intelligence, and transaction-centric operations to move from reactive firefighting to operational mastery in 2026.

At incident.io we run a deliberately simple technology stack. Keeping things boring has allowed us to scale from a few hundred customers to several thousand, while having only two platform engineers. In this post I'll walk through the stack, explain some of the choices we've made, and touch on the challenges we're facing as we grow.

No one has time to watch dashboards all day. Alerts exist to tell us when something goes wrong or is starting to go wrong, so we can act early. In theory, it sounds simple. Define a rule, set a threshold, get notified when it is crossed. In practice, it rarely works that smoothly.

Bare-metal. Just reading that word might trigger a physical reaction for some of us. Dusty closets, old server rooms, and loud rigs that never seemed to work quite right. Remember waiting days for IT to provision a server, only to realize your ticket got lost in the shuffle? Or the classic "well, it worked on my machine" excuse right before a production push? Ah, the good old days.