3 Minutes
Avg. self-heal time
when schema drift is detected
Fleak joins the Databricks startup accelerator. See the announcement
Know a pipeline broke before the dashboard does.
Fleak tracks throughput, errors, freshness, and field health for every pipeline, alerts your team the moment they move, and proposes the fix when a source drifts. Failover and replay keep data from being lost while you look.
- Throughput
- Error rate
- Freshness
- Volume anomalies
- Schema drift
- Slack & PagerDuty
Millions
Events per second, monitored
in real time, per pipeline and destination
0
AI inference at runtime
monitoring never slows the data path
Pipelines don't fail loudly.
They go quiet.
A source stops sending, a parser starts emitting nulls, a destination rejects a batch. The first alert is usually a detection that never fired.
Silent drops
A forwarder restarts, a token expires, a topic goes empty. Nothing errors. Events just stop.
Nulls look like data
A renamed field parses as null. Volume looks normal while every downstream rule reads nothing.
No single view
Health lives in five tools: the collector, the queue, the parser, the SIEM, and the lake. Nobody watches all of them.
Every pipeline reports its own health,
end to end.
From the source connector to the last destination, every step is measured, every failure is logged with its cause, and every anomaly can page someone.
Throughput in and out
Records and bytes per second into every pipeline and out to every destination, with per-node status and run history.
Errors with their cause
Error rates by node, with the failing records, error codes, and timestamps, so root cause starts from evidence.
Volume and freshness anomalies
Fleak learns each source's normal volume and arrival pattern and flags drops, spikes, and stale data before downstream tools notice.
Field health and drift
The Brain watches field match, null rate, and type coherence. When a source drifts, it flags the change and repairs the config, with your approval or automatically within guardrails you set.
Alerts where your team works
Set thresholds on errors, volume, freshness, or budget and route alerts to Slack, PagerDuty, email, a webhook, or your SIEM.
Failover without loss
Failed records go to a dead-letter queue, destinations fail over, and data replays once the fix is approved. Nothing is dropped while you investigate.
Source health scoring
Every source is scored as healthy, silent, whispering below its baseline, or noisy, and you hear within minutes when one goes dark.
Delivery verified end to end
Fleak checks that the event types your detections rely on, such as Windows logon codes, keep arriving at each destination, before a rule silently fails.
Lineage for every event
Trace any event from its source through parsing, transformation, and schema mapping to every destination it reached.
Hear about it from an alert.
Not from an incident review. Every pipeline and every destination in one view.
The Brain watches.
The Muscle keeps running.
The Brain monitors health signals on every pipeline: throughput, errors, freshness, field match, and nulls. When something slips, it alerts, diagnoses, and proposes a fix. The Muscle keeps processing deterministically while your team reviews.
Alerts to
- Slack
- PagerDuty
- Webhooks
- Your SIEM
A firewall vendor ships a firmware update at 2 a.m.
When does your team find out?
Without monitoring
DaysThe parser emits nulls. Detections stop firing. Someone notices the dashboard went flat on Monday.
With Fleak
MinutesField match drops, an alert fires in Slack, and a proposed fix is waiting for review before the morning standup.
Trust model
Your guardrailsFixes wait for approval, or deploy on their own within the guardrails you set. Failed records wait in the dead-letter queue and replay after.
Pipelines report their own health. Your team hears about drift from an alert, not from an incident review.
"A pipeline that can't report its own health is a pipeline you find out about during an incident."
Pipeline monitoring · Fleak Platform
Bring the pipeline that broke last quarter.
30-minute working session. We'll show how Fleak would have flagged it, and when.
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