Operations | Monitoring | ITSM | DevOps | Cloud

Read a few articles on artificial intelligence and financial operations, and you’re bound to run across a sentence like this: AI enables FinOps teams to reduce TCO and boost ROI. Or one like this: The future of FinOps uses agentic AI-powered systems to detect and remediate cost issues automatically. Keep reading and you’ll find piece after piece that say a lot about AI and FinOps … without really saying anything.

Since the publication of the inaugural AI Sector Study in 2022, the UK’s AI ecosystem has grown to include more than 5,800 companies – an 85% increase over the past two years. AI revenue is now £23.9 billion, and the sector employs more than 86,000 people. To put that in context, it’s bigger than the UK gambling sector – on both counts. Digital infrastructure is the foundation of this new economy.

FinOps continues to grow in importance as organizations balance cloud services with on-prem systems, legacy applications, and evolving business demands. Many teams want to manage their costs more effectively but are unsure how to apply a FinOps strategy for hybrid IT outside the cloud.

Every developer who’s worked with PostgreSQL knows the pain: testing against a real database slows everything down. You need the database running locally, loaded with the right data, and configured to match production as closely as possible. Every time you run a new test or build, you’re forced to repeat that setup migrate schemas, seed test data, and clean everything up again. It’s time-consuming, brittle, and hard to scale across a team.

As the year winds down, my inbox is overflowing with Black Friday offers and festive greetings. It’s that time when Thanksgiving and the run-up to December holidays remind us to pause and appreciate what truly matters. Yet, in my recent conversations with IT leaders in financial services, I’ve noticed something: the time and calm need to do this feels elusive.

This year’s KubeCon underscored a real shift: AI SRE has gone mainstream. Of course, it’s not a surprise. Teams from high-growth startups to Fortune 500s are running more complex, cloud-native systems, shipping more AI-generated code, and facing rising expectations. Downtime is absolutely not an option and the work for on-call SREs has become unsustainable. The question isn’t whether AI SRE helps. It’s which one you can trust in production.

You don’t have to choose between capturing every signal and keeping costs predictable. Modern observability stacks blend full-fidelity storage (time series or columnar systems like ClickHouse and Apache Druid), tail-based sampling for heavy traffic, and tiered storage (hot/warm/cold with S3-backed archives). This gives you full-fidelity incident forensics with the day-to-day cost profile of a sampled setup.

Open source software is known for its ability to lower IT costs. But in 2025, affordability is only part of the story. A new Linux Foundation report, The strategic evolution of open source, reveals that open source has evolved from a tactical cost-saving measure to a mission-critical infrastructure supporting enterprise-grade investments, and delivering stronger business outcomes as a result.

Outages are less common than they once were, but when they happen, the impact is severe. According to the Uptime Institute Global Data Center Survey 2025, half of data center operators reported at least one impactful outage in the past three years, and one in ten of those caused a serious or severe disruption. The financial risk is just as significant. 20% of operators said their most recent outage cost more than $1 million when accounting for downtime, recovery, and reputational damage.

The software world has spent the last two years obsessed with one question: “Will AI replace developers?” Wrong question. The right question is: “How do developers stay in control while AI becomes part of the toolchain?” Welcome to The Builders Era, where the craft of software development and AI’s computational power meet on developer terms. Not as a replacement narrative. Not as a threat to our profession.