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Solution · Cloud cost reduction

The cloud bill, broken down. Then sequenced.

Compute rightsizing, commitment correction, idle cleanup, S3 tiering, egress optimization, Kubernetes spot, warehouse query rewrites. The output is a top-20 lever list with INR / USD impact per lever, sequenced as a 30/60/90-day plan.

What this engagement produces

A structured 10-day audit ending in a top-20 cost-reduction lever list, each lever with an impact estimate (INR + USD), an effort estimate, a risk rating, and a named owner — sequenced as a 30/60/90-day plan that separates quick wins from architectural changes. The deck is yours. The savings model is yours. If you want execution, that is a separate fixed-fee scope.

What gets surfaced

  • Compute rightsizing. EC2, GCE, Azure VMs running at sub-30% utilization for 30+ days. Typical recovery: 15-30% of compute spend.
  • Commitment correction. Reserved Instances, Savings Plans, Compute Commit, and Snowflake / Databricks credit commits that have drifted from actual usage. Typical recovery: 10-25% of committed spend.
  • Idle assets. Unattached EBS volumes, orphaned snapshots, abandoned Elastic IPs, idle load balancers, unused NAT gateways. Typical recovery: 40-70% of idle-asset spend.
  • Storage tiering. S3 / GCS / Azure Blob objects sitting in the wrong tier (Standard when they should be Intelligent-Tier, Glacier candidates left in Standard). Typical recovery: 30-60% of misallocated storage.
  • Egress. Cross-AZ traffic, cross-region replication, cross-cloud transfers, public-internet egress that could route through private interconnect. Typical recovery: 20-50% of egress spend.
  • Kubernetes. Spot adoption, bin-packing improvements, node-pool rationalization, HPA / VPA tuning, requests-vs-limits hygiene. Typical recovery: 30-60% of Kubernetes spend.
  • Warehouse. Query-pattern teardown at a lighter cut than the full X-Ray. Surfaces 10-25% on warehouse spend; the X-Ray goes deeper if warranted.

What you receive on day 10

  • Top-20 lever list, ranked by impact, with INR + USD savings estimate and effort + risk rating per lever.
  • Sensitivity model showing total savings under conservative / base / aggressive execution assumptions.
  • 30/60/90-day plan separating quick wins (week 1) from commitment corrections (month 1-2) from architectural changes (month 2-6).
  • Per-lever execution brief: the specific changes, who owns them, what risk to manage during execution.
  • Monitoring blueprint: alerts and dashboards to prevent the savings from regressing after the work ships.

Related reading

How to start

If your presenting problem is warehouse cost specifically, start with the Cloud Cost X-Ray — currently free 90-min review (through Q3 2026). If your presenting problem is the full cloud bill, this 10-day Audit is the right shape. Book a 30-minute call and we will pick the cleaner path against your situation.

Questions buyers actually ask

Before you book a call.

How is this different from the FinOps service line? ▾
Same engine, sharper framing. The FinOps service line is the full audit shape (compute + storage + networking + Kubernetes + warehouse). The cost reduction solution page is for buyers whose presenting problem is "the cloud bill is too high" without a more specific frame yet. Both end in the same deliverable: a top-20 lever list with INR / USD impact per lever, sequenced as a 30/60/90-day plan.
What is a realistic savings range? ▾
Patterns from published industry research (Flexera State of the Cloud, FinOps Foundation) and the founder's prior engagements: 15-30% on commodity compute via rightsizing and commitment correction, 40-70% on idle / orphaned assets, 10-25% on warehouse spend via query and tier rewrites, 30-60% on Kubernetes via spot and bin-packing — net of effort. Your specific number is built bottom-up: every lever in the top-20 carries an impact estimate with the reasoning shown. We do not publish a headline percentage because starting state varies too widely.
How fast can the easy wins ship? ▾
Quick-win levers (idle cleanup, snapshot retention, untagged-resource cleanup, low-risk rightsizing) ship inside 30 days. Commitment correction (RI / SP rebalance) typically ships in 30-60 days because finance signoff and provider contract timing matter. Architectural changes (warehouse rewrites, Kubernetes spot adoption, multi-region rationalization) sit in the 60-180 day band. The 30/60/90-day plan separates these explicitly.
Do you require a FinOps tool like CloudHealth, Vantage, or Apptio? ▾
No. The engagement runs against your existing billing exports and cloud-account telemetry. If you already use a FinOps SaaS we read from it; if you do not, we do not require you to procure one. The deliverable is a deck, a sheet, and a meeting — not a dashboard subscription. If ongoing tooling would pay for itself, that recommendation lands in the 90-day plan with named vendor options — but the buying decision is yours.
Will you actually execute the rightsizing changes, or just produce the deck? ▾
Both options exist. Some teams take the deck and ship the changes themselves — that is the cleanest path when there is engineering capacity. Others want execution as a follow-on engagement; that scopes separately as fixed-fee work, with a 90-day savings warranty (we credit fee against any lever that does not deliver within the stated impact range, net of effort).
What about warehouse cost specifically — is that in scope? ▾
Warehouse waste is included in the broader audit at a lighter cut. For deep warehouse cost work, the better path is the dedicated <a href="/tools/cost-x-ray">Cloud Cost X-Ray</a> — currently free 90-min review (through Q3 2026) of query patterns, slot / warehouse sizing, and dbt model fan-out. The two engagements compose: X-Ray on the warehouse + Audit on the broader cloud spend, in either order.