SREOps · Quiet reliability

Reliability before
the page fires.

The best incidents are the ones nobody has. Cindy watches the shape of your traffic, the behavior of your dependencies, and the small early signals that usually only mean something in hindsight. Cindy will mention them at the time, not the day after.

cindy · watching LIVE
01
Traffic looks normal
within the usual band
CALM
02
Latency is where it should be
no curves bending
CALM
03
Listening to the early signals
the small ones before the big
LISTENING
04
One service is starting to lean
not yet a problem; worth noting
NOTING
05
Headroom kept in reserve
in case the lean turns into more
READY

Reliability, handled before the page fires.

Cause, impact, and revenue — connected in one model, not scattered across dashboards.

Same hour
to root cause, while it still matters
Cindy correlates signals as the incident unfolds, so the cause is clear while you can still act on it — before customers, revenue, and the SLO take the hit.
“We knew why before we had to explain it to the board.”
0 min
of handoff on every incident
The right owner and the next action are attached to the alert the moment it fires — no twenty-minute hunt for who owns this while the SLA window drains.
“The page arrives knowing who owns it and what to do.”
Ranked by $
alerts, ordered by exposure
Alerts are prioritized by revenue at risk, not raw severity — so on-call spends every minute on what actually costs money.
“We saw it on the dashboard, not on Twitter.”

Reliability is the work you do before the incident.

Most reliability tools are good at telling you what just broke. The rare ones are good at telling you what is about to. Cindy is interested in the second kind of question.

The early signal

The kind of small change that usually only matters in hindsight, surfaced when there is still time to do something about it.

Correlated, before you ask

When something is wrong, the operational context is already connected: the neighbors, the recent changes, the dependencies, in one place.

Capacity, before the day

The question "will today hold up?" answered the day before. With the headroom needed, the cost of getting it, the time it takes.

Runbooks Cindy remembers

The runbooks your team wrote, and forgot they wrote. Cindy keeps them ready. When the moment arrives, the steps are at hand.

Postmortems half-written

When something does happen, the timeline is already laid out. The change that did it, what it touched, the response, assembled while everyone's adrenaline cools.

The quiet, all the time

The boring days, the ones nothing happens on, are also watched. Reliability is what shows up most when nothing else does.

Outcomes an SRE leader measures

60 min
RCA delivered before the incident fires
faster MTTR with business-impact triage
99.99%+
uptime achievable on the workloads that matter
0
tools ripped out; BYOT preserves your stack
Same observability tools you already trust. Predictive RCA layered on top. Revenue-aware triage built in.

"Are we going to survive today's traffic?" A forecast, not a guess.

A traffic event is approaching. Cindy compares what is coming to what you have, names the two places where the load will pinch, and proposes a measured response, far enough in advance that everyone can sleep.

cindy · in conversation LIVE
> will we survive today's peak?
[LOOKING] Comparing expected demand with available capacity. Most of it, comfortably yes.
> the parts where it's not comfortable?
Two services will lean before the rest. [FIRST] Checkout hits its scaling ceiling first. [SECOND] The data path behind it runs out of room before it runs out of compute.
> and the answer is?
[RECOMMENDED] Raise the ceiling on the first, add headroom on the second, forty-eight hours ahead. Staged for approval: a second set of eyes signs before anything moves, then it reverts on schedule once peak passes. Modest extra cost; everyone sleeps.
~22%
Today, would fail
<1%
After the change
48h
Lead time
Where the load would pinch
checkout · its scaling ceiling is the first wallfirst
the data path behind it · runs out of roomsecond
everything else · comfortablefine
cost guardrail intactin budget
Sovereignty by design
Our own purpose-built LLM, hosted in your data center.
Your data remains yours
Your telemetry, traces, and incident data never leave your perimeter.
Zero hallucination
Cindy answers operational questions from your own data, grounded in what is real.
Bring your own tools
Datadog, PagerDuty, New Relic, your APM stay in place. EveryOps sits on top.

What EveryOps gives back.

SREOps · headroom reclaimed

The capacity EveryOps right-sizes.

Move the dials. Cindy shows how much capacity EveryOps right-sizes, and how many on-call pages it prevents.

in your browser
Your shape
Services with SLOs 40
550200
Capacity buffer you carry 40%
10%40%80%
Pages per week 10
11050
Average incident duration
Cindy
waiting
RESTING
Monthly headroom you didn't need
$0
Move the dials and Cindy will tell you
Over-provisioned headroomcompute you're buying for "just in case"
$0
Avoidable page volumenoise that should've stayed quiet
0h
Incident time that could've been minutesthe cost of late context
0h
The cost of unpredictabilitycapacity bought to feel safe
$0
Runs entirely in your browser Private to this session Directional estimate, not a quote

See EveryOps run on your operations.

You just watched the scenario. Book a demo and we will point Cindy at a slice of your real stack. You decide nothing until you have seen exactly what Cindy recommends.