Services, hosts, and deploys on one graph — error and latency movement linked to the change behind it, with the blast radius already drawn.
APM suites bolt data and AI on as afterthoughts. ByteShift starts from one graph, so a service regression connects to the deploy that shipped it and everything it touches downstream.
OTLP-native logs, traces, and metrics — no proprietary agent. Purpose-built views surface open incidents and the actions that matter, not a wall of charts you have to read.
A checkout-api error rate that jumps right after the 15:14 deploy shows up anchored to that deploy, with the error delta and a 30-minute window as evidence — and a rollback one step away.
The entity graph walks dependencies backwards, so an incident carries the services, tables, and agents it actually affects — severity scored by what’s downstream, not by the alert alone.
A service degradation, the data it stops feeding, the agent that starts failing, and the spend it runs up arrive as one incident with root cause at the top — not four alerts you stitch together at 3am.
Infrastructure is one domain on the shared graph. The others — data, AI, cost, security — connect to it automatically.
POST /v1/traces is the whole onboarding. Send OTLP and your services appear as entities — no pre-registration, no schema to design.