Everything comes at a cost – no doubt about it. But in the cloud computing arena, the saying reinforces itself, leaving organizations to critically understand and take ownership of cloud usage expenses through shared allocation models for optimized financial operations. To illustrate this concept, let’s draw an analogy with a party’s cost distribution and then delve into the methodologies that align with our business needs.
Imagine a pizza party hosted by Rajesh, Susan, and Marcus. Marcus, responsible for booking the venue at Palatable Pizza for $1,500, secures various perks, including music, a private room, free drinks, and a 90% discount on mini pizzas. The rest of the attendees, Rajesh, Susan, and Marcus, pay individually for their mini pizzas, each priced at $5. Rajesh buys 3 pizzas for $15, Susan purchases 2 for $10, and Marcus gets one for $5.
The “Pizza” Situation
After the party, Rajesh and Susan happily exclaim that the per-person cost for the entire party was less than $15, while unbeknownst to them, poor Marcus incurred a total of $1,505. The discrepancy arose from their failure to grasp that the cost of the venue was foundational to their enjoyable event, leading them to grossly overpay their pizza bills.
Simply put, the absence of transparent cost distribution and visibility can lead to a disconnect between engineering (user) and the financial impact of their decisions. When costs are readily visible, consumption and ownership responsibility become aligned. Engineers are then equipped with the necessary feedback loop to make informed and cost-effective choices.
Shared Allocation Methodologies for Cloud Cost Intelligence
- Usage-based Allocation (UBA): This method allocates costs based on the actual consumption of shared resources or services. For instance, if multiple teams share a compute instance, the costs are distributed proportionately according to the percentage of time each team uses the instance. Accurate tracking of usage metrics is essential for this method.
- Fixed Allocation (FA): Here, costs are allocated based on predetermined fixed percentages or ratios. In a scenario where three teams share a resource, costs can be evenly distributed among them (33.33% each) or according to a predefined ratio (e.g., 50%, 30%, 20%). This method simplifies allocation but may not precisely reflect actual resource usage.
- Custom Allocation (CA): Organizations can devise their own unique cost allocation methods tailored to their specific needs. This may involve employing complex formulas or algorithms considering factors such as resource usage, business priorities, and other relevant parameters. Custom allocation allows for flexibility and customization.
- Tag-based Allocation (TBA): Cloud service providers like AWS, Azure, Oracle, and GCP offer tagging mechanisms to label resources with metadata. Costs can be allocated based on these tags, representing different departments, projects, or business units. Accurate tagging and cost tracking are essential for this method.
- Hierarchical Allocation (HA): HA involves allocating costs hierarchically based on a predefined cost allocation hierarchy. Costs can be initially assigned to higher-level organizational units such as departments or business units, and then further allocated to lower-level units or projects within those units. Hierarchical allocation provides flexibility in establishing cost allocation rules based on the organizational structure.
Final Thoughts
Selecting the most suitable method for shared cost allocation in the cloud depends on the specific requirements, complexity, and organizational structure of the company. It is crucial to establish transparent and clear cost allocation mechanisms to ensure financial accountability and optimal cost management in the cloud computing environment. Regular reviews and adjustments may be necessary to maintain the relevance and accuracy of the chosen method over time. Collaboration with finance and IT teams, as well as consultation with cloud service provider documentation, can offer valuable insights for implementing shared cost allocation effectively.
Ready to take a demo of Heeddata? Please write to us:
