5+ day, 8+ hour ago   (234+ words) There is a certain type of failure mode that keeps platform teams awake. Take, for example, this scenario that a platform engineering team in the insurance sector might face: A release goes out. Somewhere in a mapping layer, however, a…...

6+ day, 7+ hour ago   (1270+ words) At the end of Part 3, your monitors were live and routed, and we said something was going to fire. Well, something just did. Maybe it came in as a Slack message or an email, or maybe a new row at the…...

1+ week, 3+ day ago   (1376+ words) ETL and orchestration is one of the most varied integration categories our customers ask for. Alongside the mainstream tools we cover natively (Airflow, dbt, Fivetran, Azure Data Factory, and more), enterprises run dozens of others: commercial platforms, cloud-native services, and…...

1+ week, 4+ day ago   (1018+ words) Your test suite is a record of every failure you’ve faced. You wrote a test because something broke once, and you never wanted it to happen again. Which is great, except it means your tests are always backward-looking. The failures…...

3+ week, 3+ day ago   (534+ words) When a monitor fires on a data table or agent, Monte Carlo streamlines the investigation process for you via our Troubleshooting Agent. It gives you a root cause, the evidence behind it, and a verification checklist. The last step in…...

1+ mon, 2+ week ago   (1801+ words) Agent observability tools watch your AI agents in production and tell you what they’re really doing: the data they pull in, how fast and how expensively they run, the paths they take through a task, and whether their answers are…...

3+ mon, 18+ hour ago   (756+ words) So you built an AI agent. Great. You shipped it, your boss is impressed, and somewhere a CFO is staring at an Anthropic invoice with the kind of quiet horror usually reserved for medical bills. Welcome to the part of…...