Operations | Monitoring | ITSM | DevOps | Cloud

Welcome to December’s edition of CloudZero’s Cloud Economics Pulse — your monthly read on how cloud spend is shifting across providers, services, and AI workloads. No surprises here — November continued the quiet reshaping trend we’ve seen all year. Compute softened, data layers grew, and AI/ML hit its highest share yet. AWS extended its lead, Azure and GCP nudged upward, and the emerging “AI layer” of providers continued to take shape.

Icinga is designed to be a highly dynamic monitoring software that can monitor your setup, regardless of its architecture. While most setups are hierarchical and fit well into the master, satellites, and agents scheme with different zones, it is sometimes impractical or impossible to create one large Icinga 2 cluster. Imagine that you are responsible for only some hosts within another organization.

Students can now learn what they need within the Elastic stack anytime. The Elastic Training team has shifted its on-demand training strategy from paid to free! Yes, you heard that right — complimentary on-demand training is now readily available to everyone. The Elastic Training team is continuously developing and releasing bite-sized training modules designed to align with Elastic solutions and highlight key features.

Asset tracking software is becoming one of the highest return investments for organizations in 2026. With rising labor costs tightening budgets and increasing pressure for operational efficiency companies are searching for tools that reduce waste and maximize utilization. The demand for asset tracking management has grown rapidly because businesses are losing money through misplaced equipment delayed audits poor maintenance planning and underutilized resources.

Stop guessing on AI hardware. This DevOps guide details when to use TPUs vs. GPUs for optimal performance, cost, and framework compatibility in MLOps.

Every leap forward in technology begins with a question that feels almost human in its curiosity. In this series, we’re examining those questions, the ones that reveal where intelligence meets intention. If data was the foundation of understanding in our first conversation, automation is where that understanding begins to act.

At some point in the last few decades, every enterprise convinced itself that the humble FAQ page was going to save IT. If you could just document everything (every how-to, every troubleshooting step, every tribal data nugget living in someone’s head) you could finally stop the ticket flood. The idea was for employees to self-service and avoid escalating to engineers while freely sharing knowledge across a de-siloed ecosystem. But of course, that’s not what actually happened.

Healthcare contact centers spend an average of US$13.9M annually, with labor absorbing nearly half of this cost. Yet 7% of patients abandon interactions before reaching an agent, and most issues, coverage checks, refills, wayfinding, and status updates should never have reached a person in the first place. The core problem is structural. Every handoff between portals, call centers, apps, and clinical systems breaks context. Every break forces the patient to repeat information, wait longer, and lose trust.

SSL certificates are critical for securing websites, web applications, and APIs. They encrypt data in transit, verify server authenticity, and build user trust. However, SSL certificates have a limited lifespan, typically ranging from 90 days to one year. When a certificate expires, visitors encounter security warnings, some services stop working, and it can affect search engine rankings. Monitoring SSL certificate expiration is essential to maintain secure and uninterrupted online services.

APIs form the operational backbone of SaaS platforms. They authenticate users, deliver application data, process transactions, and connect multiple services into a cohesive ecosystem. When an API slows down or fails, the impact is immediate: login delays, frozen dashboards, broken customer workflows, and degraded user experience. For DevOps teams, this means monitoring must go far beyond checking status codes.