Operations | Monitoring | ITSM | DevOps | Cloud

Modern observability platforms are great at explaining what’s happening in your apps and your infrastructure. However, all too often the observability platform itself remains a black box. As observability data and usage grow, governance almost always lags behind, and teams struggle to answer basic operational questions like: This valuable data is typically fragmented across admin UIs, billing pages, support tickets, and tribal knowledge.

API observability has become a go-to goal for modern engineering teams. As architectures shift to microservices and APIs become the backbone of products, teams need a reliable way to understand what’s happening across services, before issues turn into incidents. That’s where observability comes in: collect the right signals, connect the dots, and debug faster.

This is the final part of our 3-part series on SQL performance improvements. In part 1, we covered how to identify slow queries. In part 2, we explored how to fix them with indexes. In this post, we'll share how we prevent those performance issues from ever reaching production again. A few weeks ago, we massively improved the performance of the dashboard & website by optimizing our SQL queries.

We recently launched monitor groups, making it easier to organize monitors on your boards and status pages. Now that same functionality is available in the StatusGator API, so you can manage monitor groups programmatically. The API now supports listing, creating, updating, and deleting monitor groups on a board. You can also assign or remove monitors from groups when creating or updating a monitor.

DNS monitoring is the practice of continuously checking that your domain names resolve correctly (right records, right answers) and that DNS lookups are fast and reliable from multiple locations. Depending on the tool, it can also watch for unexpected DNS record changes (A/AAAA/CNAME/MX/NS/TXT, etc.), validate DNSSEC, and pinpoint where resolution breaks in the chain.

For many teams, API uptime monitoring still means one simple thing: checking whether an endpoint responds with a 200 OK. If the check passes, the API is marked as “up.” If it fails, an alert is triggered. On paper, that sounds reasonable. In practice, it’s one of the most common reasons API outages go unnoticed until users complain. The problem is that modern APIs are no longer simple, stateless endpoints.