Operations | Monitoring | ITSM | DevOps | Cloud

Blueprints launched as processor bundles, and that solved the repetitive middle of the problem. But the middle was never the whole job. You still had to know which source type to add, which parameters mattered, how to batch for your backend, and how to route it all together. That changes now. The first two cover the two requests we hear most.

By the time an IoT device shows up in an incident review, it has usually already done its damage. Not the dashboard-gap kind. These devices are load bearing. They sit in the control path of substations, haul trucks, pump stations and cold rooms, so when they go blind the blast radius gets measured in tripped relays, spoiled stock, and unplanned outages rather than in missing datapoints.

Originally written by Paul Stefanski, updated by Dylan Myers. Data costs fill a large column in many organizations' accounting sheets. Data pipeline setup and management is a significant time sink for DevOps, IT, and SRE. Setting up telemetry pipelines to reduce unwanted data often takes even more time, which could better be spent creating value rather than reducing costs. This post will show you how to quickly set up your data pipeline to filter unnecessary telemetry data.