“Distil Stack understood the operational demands of managing restaurant employees and developed a solution focused on the details that matter—attendance, shift allocation, working hours, and salary administration. Their approach connected technology with practical workforce management.”
FinOps & Cost Optimisation
FinOps & cost optimization
We find the waste in your cloud bill, fix it, and set up the tagging, budgets and reviews that stop it coming back.
A custom engineering engagement
We scope this service around your workflow, existing systems and acceptance criteria. The work starts with the problem and its constraints, then a written scope and price. A packaged solution is a different buying route: choose it when its defined deliverables already fit the job.
01The problem
Where things usually stall
Cloud spend made visible, owned and steadily reduced.
- 01
A bill nobody can explain
Spend grows every month and no team knows which share is theirs.
- 02
Over-provisioned everything
Instances sized for launch-day panic, running at ten percent utilisation.
- 03
AI costs out of control
Model API spend jumps the week a new feature ships.
02Capabilities
What we deliver
- 01
Cost assessment
A line-by-line review of spend with savings ranked by effort.
- 02
Rightsizing and scheduling
Compute, storage and databases sized to real usage, with non-production shut down out of hours.
- 03
Commitment planning
Savings plans and reserved capacity bought on data, not guesswork.
- 04
Tagging and allocation
Every resource tagged to a team and product, with showback reports.
- 05
AI and LLM cost control
Model routing, caching and quotas that keep inference spend predictable.
- 06
Budgets and alerts
Forecasts and anomaly alerts that reach the owner before the invoice does.
03Outcomes
What changes once it’s live
- 01
Spend that has an owner
Cloud and model costs attributed to products, environments or workloads wherever the billing data supports it.
- 02
Decisions based on unit cost
Usage and business context help distinguish necessary capacity from idle or misconfigured resources.
- 03
A cost-control routine
Budgets, alerts and review responsibilities make optimization an ongoing operating practice.
04Approach
How we deliver it
- 01
Establish the cost baseline
Review billing exports, tags, utilization and model usage, recording where attribution is incomplete.
- 02
Identify the actual cost drivers
Compare capacity, architecture and usage patterns, including retries, token consumption and idle environments.
- 03
Test changes against service needs
Evaluate rightsizing, scheduling, caching or model routing without assuming that a cheaper configuration is acceptable.
- 04
Track the effect
Compare spend and service behaviour after changes, hand over dashboards and set owners for the next review.
05Stack
Tools we use most
- Google Cloud
- Kubernetes
- Terraform
- Grafana
- Datadog
- Prometheus
- AWS
- Azure
- BigQuery
- Pulumi
- Helm
- Snowflake
06Case studies
Featured success stories
How much can we save?
It depends on where you start. We share a savings estimate after the assessment, before any implementation work.
Will optimisation affect performance?
We test changes against your performance targets and roll them out gradually.
Is this a one-off project?
The first pass usually is. Most clients keep a monthly review so the savings hold as the platform grows.
How is the engagement priced?
We agree a fixed scope and price after reviewing the work, system dependencies and acceptance criteria. The pricing guide explains approved ranges for the engagement types it covers. A written proposal confirms what is included before a build starts.
How should the first delivery decision be made?
Review billing exports, tags, utilization and model usage, recording where attribution is incomplete. Compare capacity, architecture and usage patterns, including retries, token consumption and idle environments.
What should the acceptance criteria cover?
Cloud and model costs attributed to products, environments or workloads wherever the billing data supports it. Usage and business context help distinguish necessary capacity from idle or misconfigured resources. Budgets, alerts and review responsibilities make optimization an ongoing operating practice.






