Operations | Monitoring | ITSM | DevOps | Cloud

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.

This is a comparison of various different coding agents. We conducted this prior to the release of Google’s Gemini 3 and hope to update it soon with Google Gemini 3 inclusion.

Discover the basics of cloud efficiency as well as six advanced data-driven strategies you can use to make your cloud environment more efficient. With incredibly complex cloud architecture — that may even include Kubernetes and multi-tenant infrastructure — organizations are finding it hard to measure and monitor the performance and cost of their cloud environments.