Service
Cloud Cost Optimisation
In short: we cut AWS cloud costs for life-sciences organisations by 30–45% using AI-assisted analysis and Graviton migration, without breaking change control. It is for biotech, pharma and CRO teams with a growing cloud bill and validated systems to protect.
Reduce your cloud spend by typically 30–45% without compromising performance, reliability, or security. Pay only for what you actually need.
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Is Your Cloud Spend Out of Control?
Many organisations find themselves paying far more than necessary for cloud services. Common culprits include:
Our Cost Optimisation Strategies
Proven techniques that deliver immediate and sustainable savings
Right-Sizing Resources
Eliminate over-provisioned instances and match compute resources to actual workload requirements.
Reserved & Spot Instances
Strategically use reserved capacity and spot instances to reduce compute costs by up to 70%.
Storage Optimisation
Implement lifecycle policies and tiering strategies to minimise storage costs without sacrificing performance.
Auto-Scaling Configuration
Dynamically scale resources based on demand to avoid paying for idle capacity.
Graviton & Sustainable Compute
ARM migration typically cuts compute cost 20–40% and reduces energy per workload; we report the Scope 3 impact alongside the savings.
How We Work
AI-assisted spend audit across Cost Explorer, CUR and tagging
Identify quick wins and long-term optimization opportunities
Implement cost-saving measures with zero downtime
Set up monitoring and alerts for budget control
Provide ongoing recommendations and support
Monthly cost optimization reports
It's Not Just About Saving Money
Better Visibility
Gain clear insights into where your money goes and why
Improved Performance
Often, optimisation leads to better system performance
Predictable Budgets
No more surprise bills—know what to expect each month
Frequently Asked Questions
Expert answers to common questions about cloud cost optimisation in life sciences.
What is FinOps and how does it apply to life sciences?
FinOps (Financial Operations) is a cloud financial management framework bringing engineering, finance, and operations teams together to make data-driven spending decisions. In life sciences, where compute costs spike during drug discovery ML workloads, genomics processing, or clinical trial data analysis, FinOps discipline is critical to maintaining sustainable cloud costs without constraining research or violating change control requirements.
How much can a biotech company realistically save through cloud cost optimisation?
Based on experience with life sciences clients, typical savings range from 30–45% of current cloud spend. Quick wins — right-sizing, eliminating zombie resources, enabling S3 Intelligent-Tiering — often deliver 10-20% savings within the first 30 days. Reserved Instances and Savings Plans can lock in an additional 20-30% reduction on committed workloads.
What are Reserved Instances and should life sciences companies use them?
AWS Reserved Instances allow you to commit to using specific instance types for 1 or 3 years in exchange for discounts up to 72% versus on-demand pricing. For life sciences organisations with predictable baseline workloads such as databases, LIMS systems, and ELN platforms, RIs provide significant savings. For variable research compute, Savings Plans or Spot Instances may be more appropriate. skyPurple helps you identify the right mix.
What is cloud right-sizing and why is it important?
Right-sizing is the process of matching the compute, memory, and storage of cloud instances to your actual workload requirements. Many life sciences organisations provision conservatively, resulting in instances running at 10-20% utilisation. skyPurple uses AWS Cost Explorer and Compute Optimiser to identify and remediate over-provisioned resources without impacting performance or validated system state.
How do you manage cloud costs without compromising compliance in regulated environments?
Cost optimisation in regulated environments requires a validation-aware approach. All infrastructure changes — even cost-saving modifications like resizing instances — must be documented, go through change control where required, and be tested in non-production environments first. skyPurple generates change control documentation, preserves audit trails, and ensures optimisation activities do not invalidate previously validated configurations.
How does Graviton migration affect our sustainability reporting?
AWS Graviton processors deliver better performance per watt than equivalent x86 instances, so moving suitable workloads to ARM lowers both cost and energy consumption. We measure the change in compute hours, instance types and estimated energy per workload, then translate the reduction into a Scope 3 (purchased cloud services) figure you can include in carbon reporting. The savings report and the emissions estimate are delivered together.
Stop Overpaying for Cloud Services
Schedule a free cloud cost audit and discover how much you could be saving.
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