Cloud Cost Optimization Across AWS, GCP and Azure

Pick the lever that fits the resource

No single tactic fits a whole estate. ZopNight sorts its findings into categories that each map to a different action:

• Schedule: a resource that runs around the clock but is used on a pattern. The fix is a recurring start/stop window.
• Idle: running but unused, such as a load balancer with no traffic.
• Rightsizing: used, but provisioned larger than its measured load.
• Orphan: left behind by something that no longer exists, such as a detached disk.
• Discount: steady usage that a reservation, committed-use discount, Spot capacity or an owned licence would make cheaper.
• Compliance, security and reliability: findings that are about risk rather than money but sit in the same queue.

Each finding carries its current cost, the optimized cost and the evidence that triggered it.

Savings that do not double count

Two levers on the same resource cannot both be claimed in full. Stopping an instance at night and moving it to a smaller type overlap, so rollups count savings once per resource. The recommendations export states this, so a leadership summary is not inflated.

Commitment recommendations are priced from the resource’s real on-demand and committed rates, for one-year and three-year terms, and use measured uptime. If uptime cannot be measured, the saving is reported as unknown rather than assumed, and a commitment that would barely break even is not recommended.

Schedule recommendations are priced from the hours the schedule would remove, at the resource’s effective rate, including negotiated discounts for billing-connected accounts.

Apply, then verify

A finding can be acted on in the app through a remediation workflow, sent to Jira, or fixed by hand and marked applied. ZopNight keeps what you said (the status) apart from what it measured (the resolution). A recommendation marked applied is checked against a snapshot taken when it was raised; if the estate says otherwise, that is visible instead of silently trusted.

Scheduling savings are measured the same way: the 24/7 cost of a resource minus what it actually cost with its schedule.

Where to start

The category pages go deeper: scheduling, idle detection, rightsizing and orphan cleanup. Commitment trade-offs are covered in scheduling vs reserved instances, and every rule family is listed under recommendations.