Flows
Pre-built collector pipelines
A Flow is a collector pipeline that already works: the components, the order, the settings, and the reasoning behind them. Every one here is published in Telflo, where you adapt it, test it against real data, and push it to your fleet over OpAMP.
Replace vendor agents on your VM fleet
Scrapes CPU, memory, load, disk, filesystem, and network metrics plus system and application logs on every VM.
Redact PII before telemetry leaves the network
Masks emails, card numbers, SSNs, bearer tokens, AWS keys, and IPs in log bodies and span attributes at a central gateway, before telemetry leaves your network.
Survive backend outages with a persistent queue
Replaces the default in-memory exporter queue with a disk-backed queue that survives collector restarts, sized in items instead of opaque requests.
Ship OTel data to ClickHouse
Parses JSON log bodies into queryable attributes, coalesces msg/log and lvl/level field variants, maps severity text onto the OTel severity fields, and masks PII in attributes and bodies.
Run a cluster gateway for Kubernetes
Cluster-level gateway that receives OTLP from apps and node agents, tails pod logs, stamps deployment.environment, deletes a PII attribute, and ships everything to your OTLP/HTTP backend with a debug tap on logs.
Collect per-node telemetry with a DaemonSet
Per-node DaemonSet that scrapes kubelet and host metrics, tails pod logs with the container parser and file_storage checkpoints, enriches everything with k8sattributes, and forwards to the in-cluster gateway.
Dual-ship to two backends during a migration
Fans every trace, metric, and log out to both the legacy agent and the new OTLP/HTTP backend so the two can be compared side by side during a migration.
Move from Datadog to Elastic without a monitoring gap
Accepts traffic from the Datadog Agents you already run and dual-ships every trace, metric, and log to both Datadog and Elastic, so the two can be compared on identical data before you cut over.
Running a setup you think should be a Flow? Tell us about it.
1
Open it in the editor
The flow arrives as a working pipeline on the canvas, every component configured and editable.
2
Adapt it, then test it
Change what's specific to you, then run the pipeline against recorded traffic and see exactly what comes out the other end.
3
Push it to the fleet
Roll it out over OpAMP, staged if you want, with one click back to the previous version if something looks wrong.
Start from a working pipeline
Free account, no card. Open a Flow, adapt it, and test it against sample data in a couple of minutes.