Operations | Monitoring | ITSM | DevOps | Cloud

IT operations have outgrown the model they were built on. Enterprises now monitor tens of thousands of metrics, ingest terabytes of logs, and generate thousands of alerts daily, all while managing increasingly complex infrastructures that span on-prem data centers, multiple cloud environments, and emerging AI workloads. Yet despite all this telemetry, too many teams still learn about outages from customers before they see them in their tools.

As application systems grow more complex, it becomes ever more important to understand how services interact across distributed systems. Observability sheds light on the behavior of instrumented applications and the infrastructure they run on. This enables engineering teams to gain better track system health and prevent critical failures. OpenTelemetry (OTel) has standardized how we generate and transmit telemetry, and the OpenTelemetry Collector is the engine that processes and export this data.

Harness FME continues its investment in OpenFeature, building on our early support and adoption of the CNCF standard since 2022. Evaluate flags consistently across languages and environments, and integrate them seamlessly into your applications without modifying your code. Feature flags are table stakes for modern software development. They allow teams to ship features safely, test new functionality, and iterate quickly, all without re-deploying their applications.

Slash Kubernetes provisioning time from days to minutes. Discover how Qovery’s self-service ephemeral environments automate infrastructure, eliminate bottlenecks, and accelerate developer velocity.

Modern SaaS companies aren’t reporting weaker margins because they forgot to rightsize instances or buy reservations. It’s more because cloud spend now moves at the speed of AI experiments, overnight shifts in customer usage, and automated systems that scale in seconds. That’s why the next generation of cloud cost optimization strategies looks fundamentally different from what worked even two years ago.

Happy New Year, everyone! 2025 was another exciting year filled with impressive AI advancements. As you might expect, some significant cost changes accompanied these new developments. Because reflecting on the past is one of the best ways to prepare for an even stronger future, here’s your end-of-2025 headline round-up, complete with what you can expect going forward into 2026: Get caught up on the details below.

A customer calls to place an urgent order. Your agent's VoIP line cuts out mid-sentence. Is it their home connection? Your network? The ISP? The phone system? You have no visibility, and by the time you figure it out, the customer's gone. This is the reality for modern call centers. Whether your agents work from a central office, from home, or split between both. Network issues don't just slow operations; they destroy customer experiences in real-time.

You’ve probably used AI earlier today. Maybe you asked it to debug a function, generate a test case, or explain a legacy codebase you just inherited. But here’s the thing: you didn’t just type a question and get an answer. You explained your problem, shared background context, pasted code snippets, clarified what you meant, then refined the output until it was actually useful. In other words, you were context engineering.

If you’ve ever stared at your observability bill and whispered “there’s no way this is real,” congratulations! Your instincts are working.

In the past, our yearly recaps were mostly about numbers. What we shipped, how much Spike grew, and a long list of stats. See past recaps: 2023, 2024. But 2025 felt different to me. It had many moments that shaped how Spike as a product and the company looks today. Some of them were exciting. Some were uncomfortable, and all of them changed how I think about building Spike. We’re still bootstrapped and operating lean, with a team of fewer than ten people.