Rising cloud service costs often come as a surprise to businesses actively migrating to the cloud. Without proper management and optimization, cloud bills can quickly spiral out of control, negating all the benefits of scalability and flexibility. FinOps is not just about financial control; it’s a cultural transformation that unites financial, engineering, and operations teams to effectively manage cloud infrastructure costs. Implementing FinOps practices allows businesses not only to understand where their money is going but also to actively influence these expenses, achieving savings of up to 30%.
Understanding and transparency of cloud costs
The first step to optimization is a complete understanding of the cost structure. Cloud providers like Microsoft Azure, AWS, and Google Cloud offer detailed reports, but analyzing them requires specialized knowledge. It’s crucial to identify which resources consume the most funds, which are used inefficiently, and which are completely idle. This includes analyzing virtual machines (VMs), storage, databases, network resources, and serverless functions.
Monitoring tools such as Azure Monitor, AWS Cost Explorer, Google Cloud Billing Reports, Prometheus, Grafana, and Datadog allow for cost visualization and anomaly detection. For example, cost spikes can be linked to incorrectly configured autoscaling, resources left running after testing, or excessive provisioning.
Resource optimization and utilization
After identifying areas of excessive spending, specific optimization measures must be implemented. This includes several key areas:
- Right-sizing: Selecting the optimal size of virtual machines and other resources based on actual workload needs. Businesses often provision excess resources “just in case,” leading to overspending.
- Resource lifecycle management: Automatically shutting down or deleting unused resources (e.g., test environments outside working hours).
- Using Reserved Instances and Savings Plans: Cloud providers offer significant discounts (up to 75%) for committing to use a certain volume of resources for 1 or 3 years. This is particularly effective for stable workloads.
- Serverless computing services: Migrating part of the workload to Lambda (AWS), Cloud Run (Google Cloud), or Azure Functions allows you to pay only for actual usage, not for idle infrastructure.
- Efficient data storage: Utilizing different storage classes (e.g., S3 Standard, S3 Infrequent Access, S3 Glacier in AWS or Azure Blob Storage Hot, Cool, Archive) according to data access frequency.
| Optimization practice | Description | Typical savings |
|---|---|---|
| Right-sizing VM/DB | Matching resource size to actual workload. | 10-20% |
| Reserved Instances/Savings Plans | Long-term commitments for resource usage. | 20-75% |
| Inactive resource management | Automatic deletion or stopping of unused resources. | 5-15% |
| Storage optimization | Using appropriate data storage classes. | 5-10% |
Automation and FinOps culture
Manual cost optimization is ineffective in the long run. Automating FinOps practices using DevOps tools such as Terraform, Ansible, Pulumi, GitHub Actions, and Azure DevOps allows for integrating optimization into CI/CD pipelines. This includes automatically applying tags for cost tracking, automatically shutting down test environments, implementing right-sizing policies, and managing resource lifecycles.
A key aspect of FinOps is changing corporate culture. This means engineers and developers must understand the financial impact of their decisions. Implementing a system of accountability, where teams are responsible for their cloud costs, encourages them to seek efficient solutions. Regular reports, dashboards, and training help foster this culture.
How SL Global Service solves this
The SL Global Service team approaches FinOps comprehensively, integrating its services with cloud architecture, DevOps, and 24/7 managed cloud. SGS engineers begin with a detailed IT audit of the client’s current cloud infrastructure on Microsoft Azure, AWS, or Google Cloud platforms. This allows for identifying all sources of overspending, using tools like Azure Monitor, AWS Cost Explorer, and Google Cloud Billing Reports.
Based on the audit, SL Global Service experts develop a customized cloud architecture that ensures optimal resource utilization. This may include migrating to Reserved Instances or Savings Plans, reconfiguring virtual machines (Azure Virtual Machines, AWS EC2), optimizing databases (Azure SQL, AWS RDS, Oracle Autonomous DB), and storage (Azure Blob Storage, AWS S3). To automate these processes, DevOps tools such as Terraform and Ansible are used, integrated with GitHub Actions or Azure DevOps, enabling the implementation of right-sizing policies and automated resource lifecycle management.
As part of the 24/7 managed cloud service, the SGS team continuously monitors cloud costs using Prometheus, Grafana, and Datadog, promptly responding to any anomalies. This includes not only technical management but also regular FinOps reports for the client, demonstrating cost dynamics and achieved savings. The company also leverages its partnership agreements (Microsoft CSP/EA, VMware VPP, Veeam VCSP, Oracle ULA) to provide clients with optimal licensing terms, which also significantly impacts overall costs. The typical result of this approach is a 20-30% reduction in the cloud bill within the first 3-6 months of cooperation, while maintaining or even improving infrastructure performance and reliability.
Cloud cost optimization is a continuous process that requires constant monitoring, analysis, and improvement. Implementing FinOps practices allows not only for reducing current costs but also for creating a sustainable culture of efficient cloud resource utilization, which is critically important for long-term business success in the cloud environment.