Operations | Monitoring | ITSM | DevOps | Cloud

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.

If you have worked with observability tools in the last decade, you have likely managed, and been burnt by, a fragmented collection of tools and libraries. Each observability signal required its own tool, data formats were incompatible and had little or no correlation. For example, log records would not link to traces, meaning you had to guess which traces led to which events. The OpenTelemetry Protocol (OTLP) solves this by decoupling how telemetry is generated from where it is analyzed.

2025 was a tough year for businesses, with slow growth, high costs, cyber risks and geopolitical uncertainties all contributing to a challenging climate. More than ever, businesses must innovate to survive and grow, and digital infrastructure will play a key role in 2026. Last year I predicted a pivotal year for cloud strategy, with repatriation gaining momentum due to shifting legislative, geopolitical, and technological pressures. This trend has accelerated, with a growing focus on data sovereignty.

Here’s a paradox for the AI era: organizations are obsessed with the promise of AI as the key to unlocking productivity and enterprise transformation, and IT teams are all-in on the advantages AI and automation offer — yet those same organizations are the ones holding that transformation back. While the majority of IT workers advocate for AI adoption, operational, cultural and budgetary barriers stand in the way of enterprises implementing AI at scale.