[Power BI] Workload optimization report

📝 Scenario

As a FinOps practitioner, I need to identify and track workload optimization opportunities in order to maximize the efficiency of my cloud resources

💎 Solution

Create a Workload optimization report that includes the following KPIs:

• Cost of unused resources
  • Formula: Total cost of unused resources (idle VMs + unused storage)
  • Objective: To measure the total cost of already paid but unused resources.
  • Value: This metric provides insights into the value of resources that are being paid although they are not in use. It helps organizations assess the purchase process and to enhance its effectiveness on the purchase process and assignation to existing or available resources.
• Utilization rate of compute instances
  • Formula: Sum of running instances vs. Sum of instances purchased, included reserved instances, multiplied by 100
  • Objective: To measure the percentage of running instances vs. the total instances purchased, included reserved instances
  • This metric provides insights into the effectiveness of purchase process. It helps organizations assess the purchase process and to enhance its effectiveness.
    • Running instances: This represents the total count of instances in execution in the Public Cloud environment.
    • Purchased instances: This is the count of purchased instances in the Public Cloud environment, included the reserved instances.
• Total number of recommendations (created/executed/rejected)
  • Formula: Sum of recommendations (created/executed/rejected)
  • Objective: To measure the number of suggestions for optimize the cloud consumption is generating by the system and FinOps teams
  • Value: This metric provides insights into the effectiveness of recommendation systems and their impact on decision-making and actions. It helps organizations assess the value of data-driven advice and make data-driven improvements to enhance the effectiveness of recommendations.
    • Recommendations Created: This represents the total count of recommendations generated by the recommendation system and processes. Those are typically derived from data analysis and algorithms to guide decision-making.
    • Recommendations Executed: Count recommendations that were not only created but also implemented or acted upon. Executed recommendations represent actions taken for optimized the cloud consumption.
    • Recommendations Rejected: This is the count of recommendations that were generated but were not accepted or acted upon by the intended recipients or decision-makers.
• Savings from rightsizing
  • Formula: Total amount of saving from rightsizing actions executed (YTD)
  • Assumption: A cloud resource rightsizing is executed after a recommendation. The savings will always compare with the last monthly spend before the Rightsizing has been applied.
  • Objective: To measure the total optimization obtained by the rightsizing actions.
  • Value
    • A higher value: indicates that the organization has effectively implemented rightsizing actions, resulting in substantial cost savings and a more efficient use of cloud resources. It's essential to continue monitoring and optimizing the cloud resources, ensuring that rightsizing practices remain effective and aligned with changing resource requirements.
    • A lower value: suggests that there may be opportunities to improve rightsizing efforts and capture additional cost savings. If the savings are relatively low, consider evaluating the rightsizing strategies and ensuring that they align with the actual resource utilization patterns. Explore opportunities for more comprehensive rightsizing practices.
• Savings from relocation
  • Formula: Total amount of saving from relocation actions executed (YTD)
  • Assumption: A cloud resource relocation is executed and will run for a same period as prior its movement. The savings will always compare with the last monthly spend before the relocation has been applied.
  • Objective: To measure the total optimization obtained by the relocation actions.
  • Value
    • A higher value: indicates that the organization has effectively implemented relocation actions, resulting in substantial cost savings and a more efficient use of cloud resources. It's essential to continue monitoring and optimizing the cloud resources, ensuring that relocation practices remain effective and aligned with changing resource requirements.
    • A lower value: suggests that there may be opportunities to improve relocation efforts and capture additional cost savings. If the savings are relatively low, consider evaluating the relocation strategies and ensuring that they align with the actual resource utilization patterns. Explore opportunities for more comprehensive relocation practices.
• Reverted cloud deployments
  • Formula: Number of Cloud Deployments Reverted/Total Number of Cloud Deployments
  • Objective: To measure the proportion of reverted cloud deployments
  • Value: This metric provides insights into the financial impact of deployments that have been rolled back within a year. It offers an opportunity to assess the effectiveness of the change management and deployment processes, ultimately contributing to cost control and operational efficiency.
    • A higher value: indicates a greater financial impact of deployments that were initiated but later reverted during the year. This may suggest a higher risk of deployment issues or changes in requirements. It's important to assess the root causes of these rollbacks.
    • A lower value: means that the financial impact of reverted deployments is relatively low, suggesting that the organization is effectively managing deployments with fewer rollbacks.
• Utilization rate of storage capacity
  • Formula: Sum of used storage capacity vs. Sum of total storage capacity purchased, multiplied by 100
  • Objective: To measure the utilization of storage capacity purchased.
  • This metric provides insights into the effectiveness of purchase process and allocation of existing capacity. It helps organizations assess the purchase process and to enhance its effectiveness into the resource governance.
    • Used storage capacity: This represents the total size of data located in the Public Cloud environment.
    • Purchased storage capacity: This is the count of purchased storage capacity the Public Cloud environment, in any format, type or category that allows services to storage data.
• Rightsizing opportunity coverage
  • Formula: Percentage of the total number of rightsizing opportunities suggested by the tool that are finally applied.
    • Ʃ (# rightsizing opportunities applied) / Ʃ (# total rightsizing opportunities)
  • Objective: To measure the percentage of applied rightsizing suggestions
  • Value: With this KPI we obtain information about the alignment between tool recommendations and the existing Architecture and about the efficiency in the definition of the Cloud architecture.
    • Rightsizing opportunities applied: number of rightsizing opportunities suggested by the platform, that has been applied.
    • Total Rightsizing opportunities: total number of rightsizing opportunities suggested by the platform.

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2. Leave comments to help us solidify the vision.

No files, tests, or entry points are identified in the issue, so begin by locating the existing reporting and KPI implementation. Done would require a Workload optimization report covering the eight listed KPI areas, with their stated formulas and definitions validated against the project's existing data model.