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Cloud, IT & Telecom · Money back · Hours back · sample run · 1 ms

Kubernetes Pod Right-Sizing Allocator

$5,065.50 in monthly cloud node spend recovered through Kubernetes pod right-sizing across across 4 items.

Evidence · Kubernetes Pod Request vs Actual
prod,inventory-search-indexer,8000,1450,16384,3800,2850.00
Working

Requested 8,000m CPU vs 1,450m p95 usage (81.8% phantom reservation). Right-sizing reduces cost by $2,137.50/mo.

Method

1Calculated 95th-percentile utilization buffers against cluster request allocations.

2Generated production-ready Kubernetes deployment resource patch YAML.

$5,065.50
Total Discrepancy · Audited balance impact
ReferenceDescriptionMonthly_Savings
prodOverprovisioned Search Indexer Deployment$2,137.50
stagingOverprovisioned Staging Mock Backend$1,278.00
prodCheckout API Service Sizing$1,065.00
1 to 3 of 4
Reads

Prometheus container resource usage telemetry, plus Kubernetes deployment pod manifest requests

Produces

Pod right-sizing patch YAML and cloud node cluster consolidation plan (Resolution Dossier, Findings Schedule)

Price

Run Kubernetes Pod Right-Sizing Allocator free on the last 12 months of files. If it finds money, the fee is 15 percent of what is actually recovered, nothing on what is not. After that, ongoing monitoring is $1,250 a month. 30% goes to the referring partner.

Your files

Read in memory for the session, never stored, never used to train a model.

Outputs are computed from your inputs and the tool's rules. Check them before you rely on them.

The offer

Free scan. Pay only on cash recovered.

Run Kubernetes Pod Right-Sizing Allocator free on the last 12 months of files. If it finds money, the fee is 15 percent of what is actually recovered, nothing on what is not. After that, ongoing monitoring is $1,250 a month.

On a sample file: $5,065.50 in monthly cloud node spend recovered through Kubernetes pod right-sizing across across 4 items.

Why not just use ChatGPT?

Rules that stay current: the rate cards, tariffs, code sets and regulations it checks against are kept up to date for you; a one-off prompt starts from nothing each time. Evidence that stands up: every finding cites the line, the file and the rule, so it holds up with a vendor, a payer or an auditor. The same answer every time: the checks are written rules, not a fresh guess, so this month's result can be compared with last month's. Nobody has to own it: no one inside has to build, test and maintain a home-made tool, and files are not pasted into a public chatbot.

Get a free scan

Your files are read in memory and never stored.

If you would rather talk it through, write to dev.sathya@baseloom.app; that reaches Dev Sathya, founder.