Operations | Monitoring | ITSM | DevOps | Cloud

Reduce alert noise by 70% through intelligent aggregation, clear ownership boundaries, and filtering metrics that don't map to user-facing issues. Monitoring starts with a straightforward goal: understand your system's health and identify issues before users notice them. You set up metrics, create dashboards, and configure some alerts. At first, it works well. Over time, your stack gets bigger and more complicated. New services get added.

When a monolithic app starts to hit its limits, microservices are often the next step forward. They let you scale only what’s under pressure, keep changes local, and give teams the freedom to deploy on their own schedule. It’s no wonder the market for microservices is growing fast, from $1.93 billion in 2024 to a projected $11.36 billion by 2033. So how do you build microservices? In.NET, the process is surprisingly straightforward.

AI should speed up innovation, not inflate your cloud bill. But today, the biggest GenAI challenge for SaaS teams isn’t model quality; it’s cost. And increasingly, that cost comes from AI cost sprawl. That’s not because anyone is doing something wrong, but because AI operates differently from the cloud services we’ve all spent a decade learning how to manage.

Since launching Harness in 2017, we’ve been on a mission to unlock faster innovation by removing the bottlenecks that slow software engineering teams down. From day one, we believed that the biggest obstacles in engineering weren’t in writing code — they were in everything that followed.

Engineering teams today manage infrastructure spread across multiple clouds and tools. Whether this happened through gradual accumulation or deliberate strategy, the result is the same: complexity that slows teams down. Managing each cloud separately with different tools and workflows is a bottleneck to delivery speed, operational efficiency, and platform reliability.

For most Central IT leaders, tech debt isn't a surprise. It's the silent tax on every roadmap, every quarterly plan, every conversation about why things take so long. Modern cloud application platforms (true PaaS environments) give IT leaders a path to unwind years of accumulated complexity while simultaneously accelerating innovation. You no longer have to tolerate the tax.

You've set up the Cortex MCP and connected it to your AI assistant and IDE. You ask about service ownership, check a Scorecard or two, and it works. You're impressed by how much faster this is than clicking through the web UI. Now you're wondering what else you can do with it. I'm willing to bet we've hit a nerve with that "hypothetical" scenario. The Cortex MCP works exactly as designed, but it's deceptively difficult to know which questions to ask and when to ask them.