Your monitoring says the stream is degrading
This says
why, while the event is still on
Detection was never the hard part. What costs you the event is everything after the alarm fires — and there is no later for a live event.
What changes when the first hour is already done
The alarm fires mid-event, and the clock keeps running. Most of the first hour goes into working out which of your vendors owns the problem, before anyone can start fixing it. The event ends whether that finishes or not.
The anomaly arrives already named, with its evidence attached. A cause your team has seen before comes back in seconds with the action beside it. Something genuinely new comes back as reasoning written out in plain language — what it points to, and what it ruled out — so the engineer on call can check it rather than take it on faith.
When an incident hits a live event, everyone loses
Paid for this event and watched a degraded one.
Sold a service that works. This event was not it.
Worked it out live, against the clock, at whatever hour it landed.
Answer for all of it. The next event can go the same way.
Three things stand between an incident and a resolution in minutes
That engineer is the hardest to hire
The judgement to call an incident correctly takes years, and everyone running live video is bidding for the same people.
Triage by hand runs out the clock
Your CDNs, players and ad servers each describe the same broken stream differently. Somebody lines them up by hand, on air.
Nobody is awake to apply what you wrote down
A cause you have already diagnosed costs you the second time exactly what it cost the first.
The event goes out degraded, and nobody gets that event back. The answer you reach after it ends protects the next one, and does nothing for the one that just aired.
One question decides everything: is this a cause you already know?
If it is, the answer is instant and no model is involved. If it is not, a model reasons over the evidence and hands your engineer a line of reasoning to check.
Everything above is what this does. Below is how it reaches a diagnosis, what one reads like, and which parts arrive ready. See how a diagnosis is reached
What it does, step by step
Every alert, every explanation and every recovery is recorded under one incident id.
Detect — worth waking somebody for
Sustained in both directions
A measure has to stay past its limit for a while before it fires, and look healthy for a while before the incident closes.
No flapping
A one-second blip wakes nobody up, and an incident never opens and shuts while a measure hovers at its limit.
Two kinds of data, one seam
A symptom in your quality data but not your delivery logs has already narrowed the possible causes, before anybody has looked.
A cause you know — answered in milliseconds
Deterministic match
Checked against the causes already written down. Instant, repeatable, and no model in the path.
The action comes with it
The message that wakes the on-call engineer already carries what to do, so nothing is worked out from scratch mid-event.
The postmortem is already written
One thread per incident in the channel your team is already in, from the alert to the recovery.
A cause that is new — reasoning you can check
Evidence, not audience size
A cause is identified by where the failures pile up. The CDN serving most of your viewers is not necessarily the one producing most of your errors.
A line of reasoning, not a verdict
Ranked hypotheses, each with the reasoning that produced it. Your engineer checks it rather than trusting it.
It says when it cannot tell
If the model cannot explain it either, it says so and hands over the evidence instead of filling the gap.
Learn it — your judgement, banked
A person approves it
When a cause recurs, the system proposes promoting it, with the evidence attached. It never adds one on its own.
Two things to declare, from the console
When a problem deserves attention, and what a cause you understand looks like. Live inside a minute — no code, no deploy.
It degrades without the model
Turn the model off, or lose it mid-event, and detection and your known causes carry on.
One judgement that arrives built rather than learned during an event: the same symptom with different evidence points at two different causes — and the system is built never to collapse them into one.
What arrives built, and what stays yours
- Arrives built
- The console you watch and configure it from, shared names for every source, the playbook mechanism, detection and diagnosis, and the record of what happened — recent and historical.
- Built for you
- One adapter per data source you want in, one notifier per channel you want the answer in, and one backend for whichever model you choose to run.
- Stays yours
- The quality tooling you already pay for, your delivery logs, and your chat channel. So do the causes in the playbook: a cause only enters it once a person on your team approves it.
Adding a second provider is one adapter — not a second system, and not a change to anything already written.
What did your last bad event cost you?
Tell us how an incident reaches your team today, and what they cross-reference to resolve one.
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