Product · Cloud waste

Cloud waste, found automatically. Fixed as code.

The Analyzer Agent continuously scans compute, databases, and storage across every connected account and turns what it finds into a ranked, dollar-quantified action, delivered as a PR-ready Terraform diff or a guided ClickOps runbook.

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Rightsizing & Spot Storage lifecycle Idle & non-prod cleanup

Why waste keeps coming back

A cleanup resets the meter. It doesn't stop it.

Waste isn't a one-time mistake. It's the default state of a growing cloud estate. Without continuous monitoring, it always finds a way back in.

Overprovisioning is the default

Compute, databases, and Kubernetes requests get sized for a peak that rarely comes, then never revisited. Every new workload starts oversized and stays that way.

Idle resources run around the clock

Dev environments on weekends, unattached storage, forgotten endpoints: invisible until someone goes looking, and nobody's job is to look.

Cleanups don't stick

A point-in-time cleanup resets the meter, but new workloads launch oversized and defaults regress. Without continuous monitoring, waste drifts back within a year.

What gets found

Recommendations that say exactly what to do, and what it's worth.

The Analyzer Agent continuously scans compute, databases, and storage across every connected account and turns what it finds into a ranked action, not just a chart.

Rightsize, migrate, or delete: with the dollar figure attached

Every resource gets a concrete recommended action: rightsize, migrate to Graviton, move to Spot, scale in, or delete, each with a dollar-savings estimate attached, so prioritization is a sort, not a guess.

Tracked from discovered to done

Every recommendation moves through a status pipeline: Discovered, In Progress, Completed, so your team can see what's been actioned versus what's still open, instead of losing findings in a spreadsheet.

Remediation guidance, not just a suggestion

Each recommendation states the implementation effort, whether a restart is required, whether it's rollback-safe, the exact affected resource IDs, and the evidence behind it: the detail an engineer actually needs before touching production.

Explained in plain language

Recommendations are written in natural language: why a database migration saves money, current vs. target instance specs, remaining capacity headroom, not just a raw metrics dump.

Two of those recommendations, end to end:

pull/482 · rightsize-analytics-cluster.tf

resource "aws_instance" "analytics_worker" {-  instance_type = "m5.4xlarge"+  instance_type = "m5.2xlarge"   ami           = data.aws_ami.worker.id   subnet_id     = aws_subnet.private_a.id}
            

Reviewed & merged by your team ▼ $281/mo illustrative

OptimizeSpot · eviction-risk simulation

workloadbatch-etl / us-east-1

simulation30d usage replayed against Spot pools

eviction risk

low

Safe to migrate: On-Demand → Spot

Savings proof