Operations | Monitoring | ITSM | DevOps | Cloud

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.

An escalation policy is the route an incident takes after it triggers. It lays out who gets alerted first and sets a wait time. If nobody responds, it moves the incident forward to the next person. The word “escalation” is worth pausing on. When an incident triggers and the first person doesn’t respond, the incident doesn’t sit and wait. It moves to the next person and keeps moving until someone picks it up. That forward movement is the escalation.

The first time you sit down to design an escalation policy, it can feel a little like a crossroads. You know incidents need to reach the right people. You just aren’t sure which structure makes the most sense. Should you route by severity? By who’s available? Or by team? There’s no single right answer. Think of this guide as a compass. A compass doesn’t tell you exactly where to go. It helps you orient yourself based on where you already are.

SIGNL4 has been recognized by G2 as one of the Best German Software Companies and we couldn’t be more excited. Matthes Derdack, Founder of SIGNL4, emphasizes:“This recognition matters because it’s not based on marketing claims – it’s based on what our customers experience in real operations. Teams running mission-critical infrastructure rely on SIGNL4 when things go wrong, not when everything is fine.

If you’ve been eyeing chat-native incident tools and wondering whether PagerDuty can compete in Slack, this one’s for you. Are you still treating your incident management platform like a glorified pager? It’s time for an update. Over the past months, we’ve been evolving our Slack app from a notification tool into a full incident command center, and we’re coming for the chat-native tools (ahem, incident.io).

Every year, Honeycomb runs disaster recovery scenarios in multiple environments, including in production. Although each of our instances runs in a single region, on at least three Availability Zones (AZs), we have multiple plans for partial regional failures, and particularly, zonal failures. One of these tests was run on December 5th, and after its successful completion came its cleanup steps.

Picture this: it's 2am, your pager goes off, and you're staring at a production database that's on fire. You know exactly what's wrong. You know exactly how to fix it. But you can't touch anything because you're waiting on someone to approve your access request. Meanwhile, your customers are down, your SLAs are bleeding out, and you're refreshing Slack hoping someone in security is awake to click "approve." This is the incident response tax that too many teams pay.

AI-assisted coding has evolved from a novelty into an industry standard. At ilert, we started our adoption in mid-2023, quickly realizing that success depends heavily on proper context and workflows. This is particularly acute with Rust. While the language is central to our backend infrastructure, its strict compiler rules and distinct idiomatic approaches make it notoriously difficult for modern LLMs to master.