Environment operations

The accounts your engineers depend on.Kept running without your engineers running them.

Incidents diagnosed and resolved, requests fulfilled, patches applied, all under an authority model your team writes.

Scope a pilot →

AWS, Azure and Google Cloud

Your authority model

Read-only first phase

Root cause, not restart

Destructive actions always pause

Any tool that sends a webhook

The problem

Development and test accounts are where operational debt accumulates first.

They are also where an engineer's day disappears. A CPU alarm, a stuck queue, a patch window, a request for a bigger disk.

The IT Operations Engine takes the running of those accounts. Incidents are diagnosed and resolved, requests are fulfilled, patches are applied, and the accounts are kept in the state they should be in, all under an authority model your team writes.

What operating these accounts actually requires

Diagnosis that reaches the cause rather than restarting the host and hoping
An authority model your team writes, so what can run unattended is your decision
Destructive actions that pause for a named approver, every time, without exception
Deliberate test workloads recognised as deliberate and left alone
Ambiguous requests clarified with the requester before anything executes

What we operate

Incidents, requests, patching and the state the accounts should be in.

Live operational signal is read on top of the estate model from discovery, and the engine acts on it under the authority model your team writes. It reads the logs rather than restarting the host. Service requests, provisioning, resizing, restores and decommissioning run the same way, with dependency-aware cleanup.

CloudWatch

Security Hub and GuardDuty

AWS Config and Inspector

Azure Monitor

Webhooks

Find, fix, keep green

- Find - Live operational signal from CloudWatch, Security Hub, GuardDuty, AWS Config and Inspector, from Azure Monitor, and from any tool that can send a webhook, on top of the estate model from discovery.
- Fix - The engine reads the logs rather than restarting the host. A CPU alarm is traced to the process causing it. A queue that has stopped draining is traced to the consumer that was disabled, and the engine notes that the disable looked deliberate and suggests checking who did it. A container that reports healthy but has stopped processing is traced to the parameter that changed. Rolling patches on clustered systems check replication before each node is taken down. When the root cause is a deliberate test workload, the engine says so and leaves it alone. Service requests, provisioning, resizing, restores and decommissioning run the same way, with dependency-aware cleanup.
- Keep green - Standing checks that act when they find something, such as a daily check that restarts any instance the cloud provider stopped for maintenance, distinguishing that from an instance an operator stopped on purpose. Native recurring controls configured in your own cloud, such as scheduled patch deployments and backup plans, verified live after creation. Fixes that needed approval the first time, promoted to run on their own the next time.

Ready to hand over one non-production account?

Read-only for the first phase, then the first low-risk actions under approval.

Scope a pilot →

How it starts

One non-production account. Read-only first.

Everything in that account is in scope, but nothing acts until you have seen how the engine diagnoses.

1
One account, read-only
A single non-production account, with everything in it in scope. The engine reads the signal and diagnoses, and takes no action at all.
- Live signal on top of the estate model from discovery
- Diagnosis you can check against what you already know
- No changes in the first phase
2
First low-risk actions under approval
The authority model your team writes decides what the engine may do. The first actions are low-risk and each one pauses for approval.
- Your team writes the authority model
- Ambiguous requests clarified with the requester first
- Destructive actions pause for a named approver
3
Promotion, once it has earned it
A fix that needed approval the first time is promoted to run on its own the next time. Standing checks act when they find something, and native recurring controls are configured in your own cloud and verified live.
- Approval promoted to standing action, per fix
- Scheduled patch deployments and backup plans, verified after creation
- Destructive actions never promoted

What stays with you

Destructive actions never run unattended.

Anything that could lose data pauses for a named approver, every time.

You gain:

The authority model is written by your team, and it decides what may run without asking.
When the engine is not sure, it asks. Ambiguous requests are clarified with the requester before execution.
Where a chosen option is broader than the likely intent, the engine says so rather than proceeding quietly.

FAQ

Questions.

Which clouds?

AWS, Azure and Google Cloud.

What happens when the engine is not sure?

It asks. Ambiguous requests are clarified with the requester before execution, and where a chosen option is broader than the likely intent, the engine says so.

Start with one non-production account.

Everything in it in scope, read-only for the first phase, then the first low-risk actions under an authority model your team writes.

Your benefits:

Your authority model - your team writes what may run unattended.
Root cause - the engine reads the logs, not the restart button.
Read-only first - diagnosis before any action.
Data-loss actions pause - for a named approver, every time.

What happens next?

Talk.

A focused discussion about which accounts are costing your engineers their day.

Observe.

One non-production account, read-only, so you can check the diagnosis.

Operate.

First low-risk actions under approval, promoted as they earn it.

No obligation. Just a focused discussion about your development and test accounts.