Cloud Cost Efficiency: Strategies to Optimize Rate and Usage

In the modern digital era, cloud computing has become an integral component of business operations, offering scalability, flexibility, and cost-efficiency. However, managing cloud costs effectively remains a challenge for many organizations. In this blog post, we dive into the dual approach of balancing rate optimization and usage optimization to achieve cloud cost efficiency. By understanding the nuances of these strategies and how they complement each other, businesses can unlock significant savings while ensuring their cloud infrastructure aligns with operational demands.

Why rate and usage?

Despite the complexities surrounding cloud costs, at their core lie two primary drivers: rate and usage. These optimization levers not only intersect but also impact other capabilities, truly enhancing savings when well-balanced, thus driving cloud cost efficiency.

A thorough understanding of usage is especially essential, since mechanisms like showback or chargeback drive accountability across teams, encouraging proactive cost management. Moreover, both rate and usage optimization play a crucial role in supporting effective forecasting and budget management, ensuring a strategic approach to cloud cost efficiency.

Rate optimization 

Rate optimization focuses on the commercial aspects of cloud services, aiming to reduce the effective unit price for services offered by cloud providers. It involves strategic efforts to secure the best possible pricing through negotiation and procurement strategies. Ideally, this process is centrally coordinated by the FinOps team in collaboration with sourcing and procurement departments. Together, they work to ensure the organization benefits from optimized cloud service rates, leveraging their collective expertise to navigate contracts and pricing models effectively, thus enhancing cloud cost efficiency.

Optimization Strategy 

1. Employ effective contract negotiations to get the most percentage discount over pay-as-you-go pricing.  

2. Set a benchmark for coverage level, for example, how much of my workload should be covered by Cost Savings Plans (CSP) and Reserved Instances (RI).

3. Aim for at least 90% utilization of CSP/RI.

Pros 

• Quick win – no operational change as no changes required to cloud resources. 
• Organizational wide benefit – negotiated discount applies to almost all cloud services. 
• Substantial savings – CSP and RI can generally deliver 20 to 40% savings on top of enterprise discount. 

Cons 

• Underutilization – if cloud resources usage changes it could result in CSP or RI not been fully utilised and lower the effective discount. 
• Hinders usage optimization– Can lead to the mentality that usage optimization is not required or needed. 

Consideration 

There is generally a trade-off between rate discount to commitment, manifested in both spend and time.  

Example – Why rate optimization alone isn’t enough

Let’s consider the analogy of a gym membership. A gym has advertised a $3 per visit membership, but upon further investigation, we realize that their calculations are based on using the gym 4 times per week and that there is a 1-year contract required.  

The gym also offers an option where there is no yearly contract, but you would pay $6 per visit. We view commitment here as a good thing, an incentive to keep us going back to the gym, with a nice 50% discount, so we sign up for this good deal.  

Committed funds $3x4x52 = $624 

Following are three potential scenarios that could result from our gym membership:  

Scenario 1: Consistent attendance 

• Description: Attend the gym 3 times per week throughout the year, except for a 6-week period of no attendance due to travel and work commitments. 
• Weekly frequency:
  • 3 times/week (46 weeks)
  • 0 times/week (6 weeks)

Scenario 2: Fluctuating momentum 

• Description: Gym attendance varies throughout the year, influenced by motivation and new fitness goals. 
• Quarterly breakdown: 
  • Q1: 4 times/week for 12 weeks (Total: 48 visits). 
  • Q2: 2 times/week for 12 weeks (Total: 24 visits). 
  • Q3: 1 time/week for 12 weeks (Total: 12 visits). 
  • Q4: 2.5 times/week for 8 weeks (Total: 20 visits). 

Scenario 3: Relocation impact 

• Description: Consistent gym attendance for the first 6 months; thereafter, relocation leads to sparse attendance. 
• Half-yearly frequency: 
  • First Half: 3 times/week for 24 weeks (Total: 72 visits). 
  • Second Half: 1 time/week for 24 weeks (Total: 24 visits). 

The following table’s comparison across scenarios highlights key insights: consistent attendance maximizes total visits, fluctuating motivation leads to varied usage over time, and significant lifestyle changes can notably decrease overall usage. This illustrates the importance of consistency for maximizing utility, the impact of motivational changes on attendance patterns, and the potential for external factors to significantly alter usage habits. 

	Q1 Visits	Q2 Visits	Q3 Visits	Q4 Visits	Total Visits
Scenario 1	34.5	34.5	34.5	34.5	138
Scenario 2	48	24	12	20	104
Scenario 3	36	36	12	12	96

Now if we apply our total visits to the contracted cost for the gym membership, we can see consistent attendance maximizes ROI through significant savings, fluctuating attendance leads to a neutral ROI with no gains, and reduced attendance decreases ROI, incurring a cost above the standard rate. These insights demonstrate the direct correlation between consistent usage and financial return on investment. 

	Total Cost	Cost per Visit	Per visit cost	% Saved
Scenario 1	$ 624.00	$ 4.52	$ 6.00	24.64 %
Scenario 2	$ 624.00	$ 6.00	$ 6.00	0.00 %
Scenario 3	$ 624.00	$ 6.50	$ 6.00	– 8.33 %

The gym membership analogy succinctly illustrates the principles of cloud cost rate optimization, emphasizing the importance of aligning financial commitments with usage patterns. Just as gym-goers choose between a contract with discounted visits or a flexible pay-per-visit plan based on their anticipated attendance, businesses must forecast their cloud usage accurately to benefit from committed use discounts without risking underutilization. Consistent usage can lead to significant savings, much like regular gym visits make a discounted membership worthwhile. However, unpredictable or fluctuating demand can diminish these benefits, underscoring the necessity for careful planning and understanding of usage patterns in cloud cost efficiency strategies. 

Usage optimization  

Usage optimization aims to align resource availability with actual demand, ensuring efficient service delivery and minimizing waste. This involves two key strategies:  

Workload optimization:  

Workload optimization entails adjusting resources to fit usage needs, implementing scheduled activations and deactivations, and managing the lifecycle of storage, among other practices. These measures require ongoing analysis of usage trends and adjustments to cloud resources to maintain optimal efficiency. 

Architect for cost efficiency:  

Designing architectures for cloud cost efficiency entails configuring cloud services to balance operational demands with minimal expenses, leveraging auto-scaling, optimal resource selection, and cost-effective redundancy strategies. 

Pros 

• Benefit ripple – the benefit of optimization extends beyond cost. 
• Shapes FinOps culture – success in usage optimization comes from line of business and engineering teams taking ownership, this is essential to building an effective and successful FinOps culture. 
• A virtuous cycle – change made can be accentuated by visualization and creates a sense of accomplishment for those involved, propelling further action. 

Cons 

• Longer lead time to realize savings – actions to optimize take time, especially when first starting.  

Consideration 

As an organization’s FinOps culture impacts usage optimization’s efficiency, the more mature FinOps is, the less lead time to action is required, and more automation can be embedded in the process. The process and teams that are part of usage optimization in turn shapes and models the FinOps culture.  

Pro tip 

While aggressively negotiating enterprise discounts is advisable, approach commitment-based discounts like CSPs and RIs with caution, emphasizing the importance of regular usage to maximize benefits, as illustrated by the gym analogy. The optimal commitment level varies depending on factors such as your stage in cloud migration, workload importance, and application requirements. For instance, in previous roles, we set CSP coverage at 25% for secondary workloads and 75% for critical production tasks.

Before committing to long-term RIs, consider the rapid pace of technological evolution and determine what percentage of cloud resources you’re willing to lock in, aiming to keep the cloud’s inherent flexibility and innovation potential rather than restricting it. 

Conclusion:  

By leveraging the principles of rate optimization to secure the best possible pricing while committing to usage optimization to align cloud services with actual needs, companies can maximize their cloud cost efficiency.

While the journey toward cloud cost efficiency is nuanced, requiring a deep understanding of cloud services and a commitment to ongoing management, with the right strategies in place, businesses can achieve a cost-effective, efficient, and flexible cloud infrastructure that supports their goals and drives growth.

To learn more about how you can get the most out of your FinOps practice click here to read our whitepaper, Truth About Cloud Value, where we expose the myths surrounding cloud cost management and dive into how you can move beyond simplistic narratives and embrace a nuanced, value-driven approach to cloud cost efficiency.