The bill grows faster than usage
Cost rises every month, but no one can tie the increase to traffic, users, or product growth.
Cloud Cost Optimization
Lower the cloud bill without making the stack fragile.
Most cloud waste is not dramatic. It is old test machines, oversized databases, idle disks, and environments that never sleep. We find the waste, explain the trade-offs, and make the changes in small, reversible steps.
The plain version
A useful cost review does not start with random shutdowns. It starts by making the bill readable: which workload owns the spend, which resources are idle, which services are oversized, and which commitments are safe. After that, the work is mostly careful engineering, not guesswork.
20-50%
typical savings range
1 day
initial estimate
AWS + GCP
certified engineers
When this is worth fixing
If these signs are familiar, it is time to clean it up
Idle resources keep billing
Old test instances, orphaned disks, snapshots, and staging environments quietly keep charging you.
Everything is over-provisioned
Databases, nodes, and virtual machines were sized for a peak that rarely happens anymore.
No owner for cloud spend
Finance sees the invoice, engineering owns the resources, and nobody owns the operating model.
What actually gets done
Not a slide deck that stops at recommendations.
We keep the work practical: enough analysis to avoid reckless changes, then implementation you can review, roll back, and hand over.
Cloud bill and usage review across AWS, Google Cloud, DigitalOcean, or self-managed infrastructure
Resource right-sizing plan for compute, databases, storage, Kubernetes nodes, and managed services
Autoscaling and scheduling plan for dev, staging, and production workloads
Reserved Instance, Savings Plan, committed use, and spot usage recommendations
Cost dashboards, budget alerts, tagging policy, and owner visibility
Implementation support so savings do not break reliability
Process
Small steps. Clear rollback.
01
Map spend
We group cost by workload, team, service, and environment so the waste becomes visible.
02
Model savings
We calculate what can be safely cut now, what needs engineering work, and what should be left alone.
03
Apply changes
We implement right-sizing, autoscaling, schedules, and commitment discounts with rollback paths.
04
Keep it controlled
We leave dashboards, alerts, and ownership rules so costs do not creep back.
Related work
This usually connects to cloud cost work.
Frequently asked questions.
How much can cloud cost optimization save?
Most teams find 20-50% savings when they have not reviewed cloud spend recently. The exact number depends on usage patterns, uptime requirements, commitment coverage, and how much unused infrastructure exists.
Will optimization cause downtime?
It should not. The work starts with analysis and then changes are applied in controlled steps, with rollback paths and monitoring for production workloads.
Do you need admin access?
For the first estimate, a bill export and usage summary are enough. For exact recommendations, read-only billing and monitoring access is better. Implementation access is only needed if you want 8grams to apply changes.
Can you optimize Kubernetes costs?
Yes. Kubernetes savings usually come from node right-sizing, requests and limits, autoscaling, workload scheduling, storage cleanup, and better observability around namespace or team usage.
Bring the setup you have. It does not need to be tidy.
Send a short brief: provider, app shape, bill or release pain, and what you want to fix. We will reply with sensible first steps.