As more organisations embrace digitalisation, optimising cloud services, managing costs and choosing the right platforms to support business operations becomes crucial.
Here, Adam Weldon Ming, Cloud Solution Architect and team lead at OryxAlign, discusses the different methods businesses can use to optimise their cloud usage for cost efficiency.
Cloud optimisation falls under FinOps (financial operations) and focuses on managing and optimising the costs associated with using cloud computing resources. With a little analysis, healthcare companies can gain insight on the cloud costs for each department or cost centre.
FinOps also explores strategies to reduce costs, such as identifying servers that can be turned off during non-operational hours or leveraging Microsoft Azure cost-saving plans.
Tagging and resource allocation: Applying proper tagging and categorisation to cloud resources — such as compute instances, storage and databases — can help to allocate costs to different departments, projects or teams.
This allows for better cost control, accountability and optimisation based on specific business needs. For example, compute instances can be split by department to provide insights into area-specific costs. Usage patterns can then be analysed to optimise resources. If certain compute instances consistently experience low utilisation, they can be rightsized to match actual demand and eliminate unnecessary expenses.
Demand-based flexibility: Certain cloud platforms include options such as auto- and flexible scaling sets to ensure that servers are only used when needed.
Autoscaling in Azure, for example, refers to the automatic adjustment of compute resources based on workload demand. It allows organisations to dynamically scale their applications and infrastructure up or down to match the system’s changing needs.
Flexible scaling sets enable the deployment and management of a group of identical virtual machines (VMs) as a single entity. These support autoscaling, allowing organisations to scale the number of VM instances within the set and ensure that the required capacity is available during high-demand periods (and reduce costs during low-demand ones).
Similarly, Amazon’s AWS offers Elastic Load Balancing (ELB), which automatically distributes incoming traffic across multiple instances or resources, ensuring that the load is evenly distributed.
It helps improve your applications' availability and fault tolerance by automatically scaling the number of instances behind the load balancer based on traffic patterns.
Platform-as-a-Service (PaaS): PaaS is a cloud computing model that provides a ready-to-use platform to develop, deploy and managing applications without the need to worry about underlying infrastructure. With PaaS, developers can focus on writing code and building applications, while the cloud provider takes care of the servers, storage, networking and operating systems.
Pricing model analysis: Although the names for pricing models might differ, cloud service providers offer options such as pay-as-you-go, reserved instances or spot instances.
Reserved instances, for example, allow users to reserve cloud computing capacity in advance. Reserving a server for 3 years can cut the running cost by up to 40% compared with on-demand usage.
Having successfully migrated a prominent life science company to Azure, OryxAlign monitored the infrastructure and implemented scale sets, allowing the client to automatically provision new servers when capacity reached 75%.
Combining this with purchasing reserved instances for a 3-year term resulted in significant cost savings, reducing the client’s annual cloud expenses from between £200,000–£300,000 to approximately £100,000.
By partnering with a trusted adviser that can help to navigate the cloud landscape, healthcare companies can avoid wasting money on their cloud costs by analysing resource usage, implementing cost reduction strategies and leveraging features such as autoscaling and load balancing.