Operations | Monitoring | ITSM | DevOps | Cloud

Data will always be unclean. It's just a matter of degree. I internalized that on day one of my master's program in data science, when a professor warned us that roughly 80% of our time would go to preprocessing and cleaning, not building models. Years later, as Principal Product Manager for AI, ML and Analytics at Ivanti, I've found the guidance holds up remarkably well in practice.

According to Redgate’s 2026 State of the Database Landscape report, 91% of teams – no matter how experienced – still hit at least one significant challenge during their move to the cloud.

Here’s a story that plays out constantly in enterprise IT, and few people talk about afterward. A team runs an evaluation with multiple vendors using a structured scoring process. Then, they make their choice, but six months into deployment, the platform that excelled in every demo is now struggling with the actual environment. The IT leader who signed off is in a room with their CIO, trying to explain why the numbers fail to match the projections.

Enterprises are pouring billions into GPUs and AI compute, but most are overlooking the infrastructure that connects it all. Justin Ryburn, field CTO at Kentik, makes the case that the network is the most underestimated variable in whether AI initiatives succeed or fail.

Claude API pricing per million tokens: Haiku 4.5 at $1/$5, Sonnet 4.6 at $3/$15, Opus 4.7 at $5/$25. Plus caching, batch discounts, and how to optimize API spend at scale.

Claude on AWS now has two paths: Bedrock and the new Claude Platform. Compare pricing, billing mechanics, features, and cost visibility across both.

When we shipped TV mode, we heard almost immediately: “Great, but I have five dashboards and one screen.” A single dashboard on a wall display covers one view of your infrastructure. If you want to rotate between your network overview, database health, application metrics, and infrastructure summary, someone has to walk over and click, or you’re buying more screens. Dashboard playlists solve this.

How quickly can you restore service when an incident hits your system? Most IT teams are not slowed down by detecting incidents. The challenge starts after something breaks, when the goal is to bring services back online as quickly as possible. Modern systems are highly distributed. Alerts arrive from multiple tools, dependencies are complex, and it is often difficult to immediately understand what actually failed.

Modern operational environments are intricate ecosystems shaped by distributed architectures, accelerating change cycles, and a constant influx of telemetry. The complexity itself is not the issue. The issue is how teams construct understanding inside that complexity. After years of expansion across cloud, edge, third-party services, and internal modernization efforts, many organizations now have abundant data but limited confidence in the meanings behind it.