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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

On-Demand Vs. Spot Instances: What's The Difference?

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.

From Chaos Engineering to Resilience Testing: Why We're Expanding How Teams Validate Reliability | Harness Blog

At Harness, we’re committed to helping teams build and deliver software that doesn’t just work – it thrives under pressure, scales reliably, and recovers swiftly from the unexpected. Today, we’re taking the next step in that mission by evolving our Chaos Engineering module into Resilience Testing. This evolution reflects how reliability is tested in practice today.

Millions of Metrics. Zero Clarity.

Millions of metrics. Zero clarity. That’s the reality many IT teams are facing today. As environments grow more complex, telemetry explodes. Millions of records generated every hour. Dozens of specialized tools for network, storage, Kubernetes, cloud, AI workloads. Each tool is good at its domain. But none of them answers the real question: Where should I focus right now? Fragmented visibility creates predictable failure modes.

Keeping it boring: the incident.io technology stack

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.

Ghosts of Servers Past: The Bare-Metal Comeback Story

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.

What is an escalation policy? (And why every team needs one)

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.

[Webinar] Conquering the Complexity of Self-Hosted Apps with Agentic AI SRE

Most enterprise SaaS products, like Komodor’s Autonomous AI SRE Platform, require installing a remote agent on the customer’s infrastructure, which varies significantly from one organization to another, in terms of architecture, configurations, permissions, processes, and more. This “unmanaged” model creates major blind spots, making daily operations, observability, debugging, and incident response challenging. When failures occur, limited visibility and bespoke systems make root-cause analysis slow, incomplete, or impossible.

A compass for designing your escalation policy

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.