AWS Cost Optimization

Reduce AWS spend without losing performance.

Logiciel helps engineering and finance teams cut AWS spend without sacrificing performance or scalability.

We improve cost visibility, eliminate infrastructure waste, and implement measurable optimization across compute, storage, and databases - so your cloud stays efficient as your product scales.

Hire AWS Developers Common Questions

6 outcomes

A cost operating model your teams run on

6 levers

Cost areas across the enterprise workload

3 models

Ways to engage FinOps support

1 practice

A documented FinOps blueprint that lasts

The problem

Why AWS bills grow faster than the business.

No clear cost story

Engineers spin up resources with no one owning the bill.

OwnershipVisibility

Split metrics

Finance and engineering measure the same workload differently.

FinanceEngineering

Noisy allocation

Inconsistent tagging turns allocation reports into guesswork.

TaggingAllocation

Data & automation sprawl

Workloads scale both quality and cost right across the org.

ScaleSprawl

Quarterly reviews

Cost gets looked at once a quarter - after the spike has crested.

CadenceReactive

No ownership in between

Nobody owns spend between the big reviews, so it drifts.

DriftAccountability

What you get

A cost model your teams can run themselves.

Six concrete things you keep - the baseline, the models, the reports, and the practice that makes the savings stick.

Tagging & allocation baseline

Clean and consistent across every AWS account.

Foundation

Right-sizing recommendations

Validated against real performance data.

Compute

A commitment strategy

Savings plans & reserved instances, modeled from real usage.

Commitments

Kubernetes & data cost reporting

Mapped to teams, products, and tenants.

Reporting

Reports finance & engineering trust

Weekly and monthly - one shared truth.

Governance

A documented FinOps practice

That survives team changes.

Operating model

The levers

Where the savings actually are.

Cost visibility & allocation

Tagging & CUR that map to reality.

Compute right-sizing

EC2, containers & Lambda to real load.

Storage optimization

Lifecycle policies & the right tiers.

Database cost optimization

RDS, Aurora & DynamoDB, tuned.

Savings plans & reserved instances

Commitments modeled from real usage.

Kubernetes cost reduction

EKS allocation that scales down.

Engagement models

Three ways to work together.

Pick the model that fits how your team wants to own cost.

Dedicated FinOps engineering squad

A standing team owning AWS cost optimization end to end.

FinOps advisory & staff augmentation

Senior FinOps expertise embedded alongside your engineers.

Outcome-based cost reduction

A fixed-scope engagement measured against a defined savings target.

How we work

Our AWS cost optimization framework.

Step · 01 · See it

Cost diagnostics & baseline

We map spend, tagging, and waste across your accounts, and agree a baseline everyone trusts.

DiagnosticWeek 1-2

Step · 02 · Bank wins

Quick wins

Idle resources, storage classes, and obvious over-provisioning - banked fast, no rework.

Quick winsWeeks 2-4

Step · 03 · Fix structure

Structural optimization

Right-sizing, auto-scaling, architecture tuning, and Kubernetes cost reduction.

StructuralOngoing

Step · 04 · Commit

Commitment strategy

Savings plans and reserved instances modeled from real usage - coverage without lock-in risk.

CommitmentsModeled

Step · 05 · Last

FinOps operating model

Reporting, review cadence, and clear ownership - a practice your team can run without us.

Operating modelContinuous

Insights & frameworks

The thinking behind the practice.

Enterprise AWS FinOps operating model

How structure, roles, reviews, and reporting keep spend under control at scale.

Kubernetes & AI cost allocation framework

A practical way to allocate shared infrastructure cost across teams and products.

What we tune

Across the AWS cost surface.

Cost ExplorerCost Optimization HubCompute OptimizerBudgets & AlertsSavings PlansEC2S3RDS & AuroraDynamoDBEKSAWS GlueKMS

FAQ

Frequently asked questions.

What are the best practices for reducing cloud infrastructure costs?

Start by understanding your spend drivers. Use Cost Explorer to find underutilized services, right-size EC2 against real CPU and memory usage, apply Savings Plans or Reserved Instances for steady workloads, and use Auto Scaling and Spot for variable or fault-tolerant ones.

Which tools do you use to manage and optimize AWS costs?

AWS-native tooling - Cost Explorer, Budgets and alerts, the Cost Optimization Hub, and Compute Optimizer for right-sizing across EC2, containers, and Lambda - plus monitoring dashboards for ongoing governance.

How do automated alerts help control spending?

Alerts notify teams when spend nears a threshold by account, service, or project - so anomalies get investigated fast, not at the end of the month.

How do you find and eliminate unused AWS resources?

Regular audits for idle EC2, unattached EBS volumes, unused load balancers, and orphaned snapshots - the quiet waste that adds up.

What are the most common AWS cost-saving features?

Savings Plans, Reserved Instances, Spot, Auto Scaling, serverless pay-per-use, tiered storage, and budgets with alerts.

How do you optimize EC2 and compute costs?

Measure real utilization - CPU, memory, network - and right-size to a better-fit instance type, then use Auto Scaling instead of always-on capacity.

How do you save on object and data storage?

Match tiers to access patterns: keep hot data in standard tiers and move cold data down with lifecycle policies.

How does right-sizing improve efficiency?

Right-sizing uses performance metrics to recommend better-fit instance types and sizes - often delivering immediate savings with no impact on the workload.