Operations | Monitoring | ITSM | DevOps | Cloud

Splunk is built around a deceptively simple premise: get your data in, search it, and act on it. In practice, the gap between “get your data in” and “data that actually works in Splunk ES” is where most of the engineering effort goes. CIM normalization is non-trivial. Technology Add-on development is slow. Volume-based licensing penalizes growth. And the combination means that as environments expand, Splunk becomes harder to operate efficiently.

APIs sit at the center of modern digital infrastructure. Mobile applications, SaaS platforms, microservices, and third party integrations all depend on APIs to exchange data and execute business logic in real time. When an API becomes unavailable, slows down, or returns incorrect data, users feel it immediately. Transactions fail. Dashboards stop updating. Logins break. Revenue and trust are affected within minutes.

Modern software runs on APIs. Whether you are operating microservices, integrating third party services, or building customer facing platforms, APIs are the backbone of your architecture. As systems become more distributed, simply knowing whether an endpoint is up or down is no longer enough. Teams need deeper visibility into performance, reliability, latency, and behavior across environments. That is where API observability tools come in. API observability goes beyond basic health checks.

Modern applications are powered by APIs. Every login request, checkout transaction, mobile interaction, and third-party integration depends on APIs responding quickly and reliably. When an API slows down, the entire user experience suffers. Even a one-second delay in response time can: For ecommerce platforms, fintech systems, SaaS products, and real-time applications, slow APIs do not simply create inconvenience. They directly affect revenue, customer retention, and operational stability.

How platform and SRE teams are using Mezmo's open-core agent framework — with any LLM, any tools, any observability backend.

Elixir’s “let it crash” philosophy is one of the best ideas in modern software design. Supervisors restart failed processes, the system self-heals, and life goes on. It’s like having a really good immune system. The problem is that a really good immune system can also hide chronic conditions. A GenServer crashing and restarting is working as designed.

Seer is our AI agent that takes bugs and uses all of the context Sentry has to find the root cause and suggest a fix. We use it all the time to help us improve Sentry. Seer fixes Sentry. More recently, Seer has been helping us fix itself — Seer fixing Seer. An upstream outage triggered a bit of an avalanche, revealing a bug that had been hiding away for months. When it came time to fix it, Seer pointed us exactly where we needed to look.