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 & SpotStorage lifecycleIdle & 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