Service Cost Prediction
Cost Estimation feature is designed to help users understand the financial implications of their service deployments before they go live. This enhancement empowers users to make informed decisions regarding resource allocation and budget management, ensuring a more optimised approach to deploying applications on Kubernetes.
How It Works
Deployment Preparation:
When users decide to deploy a service, they can input their deployment specifications, including the resources (CPU and memory) required for their application.
Cost Prediction:
Scoutflo utilizes the Kubecost Predict API to analyse these specifications. This API anticipates the costs associated with your workloads by evaluating the resource requests you provide. It generates estimates that reflect both current and projected costs, allowing you to see how your deployment will impact your budget.
User-Friendly Interface:
Upon filling in all the details in template, a modal window shows a clear table of costs related to CPU and memory usage. This visual representation helps users easily comprehend the financial impact of their choices.
Confirmation Step:
Before finalizing the deployment, users receive a confirmation prompt. This step ensures that they have reviewed all costs and details, allowing for any last-minute adjustments or considerations.
Benefits for Users
Informed Decision-Making: By providing cost estimates upfront, users can evaluate whether their planned resource allocations fit within their budget. This foresight allows for adjustments before incurring expenses.
Optimized Resource Allocation: Understanding projected costs helps users allocate resources more effectively, ensuring they only deploy what is necessary for their applications without overspending.
Budget Management: With clear visibility into current and projected costs, users can better manage their budgets and financial planning, reducing the risk of unexpected expenses.
Using Cost Estimates for Decision Making
When you input your deployment details, Scoutflo processes this information through the Kubecost Predict API. The API evaluates how changes in resource requests will affect your overall costs.
The output includes three key components:
Current Costs: What you are currently spending.
Projected Costs: What you can expect to spend after the new deployment.
Cost Difference: The change in your monthly costs due to the new deployment.
This allows you to make strategic decisions about how much CPU and memory to allocate based on financial implications rather than just technical requirements.
Conclusion
The Cost Estimation feature in Scoutflo is designed to enhance your deployment experience by providing valuable insights into potential costs associated with your Kubernetes deployments. By leveraging this feature, you can make better-informed decisions about resource allocation and budget management, ultimately leading to more successful deployments on our platform.
Last updated