Earlier this year we promised a new way of approaching FinOps, and today we deliver on that promise. Hear from Craig Hinkley, CEO of CloudBolt, as he discusses the new CloudBolt Platform and how it is the bedrock of the vision for Augmented FinOps we set out in January.
Join Craig Hinkley (CEO, CloudBolt) as he discusses why cloud waste and cloud value should be a key focus for organizations, and how the new CloudBolt Platform can help you maximize your cloud ROI.
CloudBolt’s Augmented FinOps platform addresses these challenges head-on. CloudBolt makes complete cloud lifecycle optimization a reality by leveraging intelligent automation and enhanced insights. Our solution closes the “insight to action” gap, enabling users to make better decisions in the cloud.
Forrester names CloudBolt a Strong Performer for Cloud Cost Management and Optimization
Key Forrester Insights
The Forrester report states that CloudBolt is superior in access and permissions, usage policies, and capacity planning — an area that is normally a gap for most CCMO solutions.
Read the report to learn more about:
- The three areas driving the CCMO market’s meteoric growth.
- Why we’ve received the highest score possible in the “Vision” criterion.
- Why we received the highest scores possible in seven criteria, including capacity planning and assessment, integrations and APIs, access and permissions, usage policies, and more.
- Forrester’s take on why CloudBolt has become a strong competitor in the CCMO space.
Fill out the form and download the full report now to see Forrester’s comprehensive evaluation.
Join Will Norton (Sr Director Product Marketing), Kyle Campos (CTO), and Ryan Wrenn (VP of AI/ML), as they recap what they saw and heard and FinOps X 2024.
Introduction
For years, VMware has been the unquestioned leader in enterprise virtualization and a core part of many organizations’ IT infrastructures. However, Broadcom’s $61 billion acquisition of VMware in late 2023 has sent shockwaves through the industry and left many VMware customers reevaluating their hypervisor strategy going forward.
While Broadcom has pledged to be a good steward of VMware’s products and continue innovating, the move has understandably made some customers nervous about cost increases or lack of support under the new ownership. This uncertainty has driven many to begin exploring alternative hypervisor solutions should they decide to leave the VMware ecosystem.
In this article we will be sharing some of the insights we have gathered from discussions within our customer base surrounding what their evaluation criteria and considerations are when evaluating alternatives for VMware solutions – specifically at the hypervisor layer.
Considerations When Evaluating Other Hypervisors
Switching hypervisors can significantly impact an organization’s IT infrastructure, performance, and operational workflows. VMware customers contemplating a switch to a new hypervisor should carefully consider the following factors:
Cost Implications
Analyze the total cost of ownership (TCO) of the new hypervisor, including licensing fees, hardware requirements, operational costs, estimated migration costs, enablement costs, and potential savings. Some hypervisors may offer lower upfront costs but require additional investments in hardware or have higher operational expenses. Consider both CapEx and OpEx implications, as well as potential savings from features that improve efficiency or reduce downtime. Ensure that you are factoring the learning curve that your team will have ahead of them with a new solution.
Hardware Realities
Beyond pure software costs, the suitability of existing hardware can significantly impact the decision. For example, some alternate hypervisors are tightly coupled with their appliance hardware, so adopters lacking compatible infrastructure would face costly rip-and-replace scenarios. Other more open solutions tend to have wider hardware support.
Ecosystem Dependencies
For most enterprises, the hypervisor is just one piece of a broader IT ecosystem. Solutions for backup, disaster recovery, monitoring, security and more may have built-in VMware dependencies and a lack of support for other in-market hypervisors. A wholesale hypervisor swap could disrupt operations if those ecosystem products don’t extend support. Evaluating integration efforts and working with third party vendors will be vital.
Migration Paths
Although the effort of migrating hundreds or thousands of workloads is daunting, some alternatives offer paths to reduce friction. Nutanix touts mobility between AHV and VMware via their hybrid solution. Open-source projects often have tools as well. But for complex multi-tier applications, considerable re-platforming work may still remain.
Feature Set and Capabilities
Compare the features and capabilities of the new hypervisor against VMware’s offerings. Consider whether the new hypervisor meets your requirements for performance, scalability, and reliability. Also, assess its ability to support future growth and technological advancements. Pay attention to features like live migration, storage and network virtualization, high availability, disaster recovery, and support for containers and cloud-native applications.
How CloudBolt Can Help
With so many technical, operational and financial factors to balance, VMware customers face a complex decision-making process as they ponder their future hypervisor strategy. Acting prudently, understanding requirements, and viewing the hypervisor through an ecosystem lens will be critical for organizations looking to evade Broadcom-induced turbulence.
For VMware customers utilizing CloudBolt as their self-service platform, the transition to a new hypervisor can be seamless and transparent to end users, thanks to CloudBolt’s robust support for multiple hypervisors. This unique capability means that even during a backend migration, users experience no disruption in accessing and managing their resources. CloudBolt acts as an intermediary layer that abstracts the complexities of the underlying infrastructure, allowing end users to interact with their resources as if nothing has changed from when they were managed in VMware. This approach not only enhances operational efficiency by reducing the learning curve and minimizing potential disruptions but also ensures continuity of service. By leveraging CloudBolt, organizations can undertake hypervisor migrations confidently, knowing that the end-user experience remains consistent and high-quality, thereby facilitating a smoother transition and adoption of new technologies.
Evaluating your options beyond VMware
Learn more
VMware Acquisition Aftermath
Real-world insights
We surveyed 300 enterprise IT decision-makers across various industries from companies of all sizes that use VMware to uncover their real-world responses and strategies as they grapple with the acquisition’s implications. Key topics include:
- The primary concerns IT leaders have about the acquisition and how these concerns are influencing their strategies
- The potential disruptions to IT strategies and what it means for future planning
- The anticipated financial changes and how businesses are preparing for them
- The urgency and timelines IT leaders are working with to adapt to these changes
- How companies are balancing their current VMware usage with potential new solutions and strategies
Don’t miss out on the opportunity to gain strategic guidance. Fill out the form and download the full report now to access all the insights you need to stay ahead.
Download the full report
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
- Employ effective contract negotiations to get the most percentage discount over pay-as-you-go pricing.
- 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).
- 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.