March 17, 2025
March 13, 2025
March 17, 2025
March 13, 2025
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Many cloud teams follow the same logical approach: focus on the few resources with big savings potential and ignore the rest. But what happens to all those small optimization opportunities? The answer lies in understanding the "long tail" of cloud optimization—a concept that could be revolutionizing how organizations approach their cloud cost management.
Manual optimization is economically viable only for high-value changes when the opportunity cost of senior engineers is considered. These are the "low-hanging fruits" of cloud optimization—the instances that are clearly oversized or resources that have been forgotten and left running.
However, there's a clear economic threshold: when the cost of a human making the optimization exceeds the savings, it simply doesn't make sense to continue. Your talented engineers have better ways to spend their time than hunting down every small inefficiency.
Automation takes us a step further, reaching medium-value opportunities by removing the continuous human element from the equation. But this approach still comes with limitations:
The key challenge with rule-based automation is that it often lacks the wider view of the application. Rules cannot easily account for complex interdependencies or unexpected edge cases that might impact performance or availability.
This is where the true innovation happens. Autonomous optimization unlocks the entire long tail as AI agents can:
The result? Organizations are capturing previously inaccessible savings through autonomous optimization.
How big is the uncaptured long tail in your organization? Consider:
Leading companies like Palo Alto Networks, HP, and Experian are already seeing these impressive results by leveraging autonomous optimization to capture the long tail of cloud savings.
The traditional focus on only the highest-value optimization opportunities makes sense in a world of limited resources. But with the advancement of AI-driven autonomous optimization, this approach is no longer the only option.
Organizations can now effectively address the entire spectrum of optimization opportunities—from the high-value, obvious changes to the thousands of small optimizations that collectively represent significant savings.
Reach out to us to see how your cloud environment could benefit from autonomous optimization. Our team can help you identify the untapped potential in your cloud infrastructure and develop a strategy to capture those savings without burdening your engineering team.
Don't leave money on the table. The long tail of cloud optimization is waiting to be captured.
March 13, 2025
March 17, 2025
Many cloud teams follow the same logical approach: focus on the few resources with big savings potential and ignore the rest. But what happens to all those small optimization opportunities? The answer lies in understanding the "long tail" of cloud optimization—a concept that could be revolutionizing how organizations approach their cloud cost management.
Manual optimization is economically viable only for high-value changes when the opportunity cost of senior engineers is considered. These are the "low-hanging fruits" of cloud optimization—the instances that are clearly oversized or resources that have been forgotten and left running.
However, there's a clear economic threshold: when the cost of a human making the optimization exceeds the savings, it simply doesn't make sense to continue. Your talented engineers have better ways to spend their time than hunting down every small inefficiency.
Automation takes us a step further, reaching medium-value opportunities by removing the continuous human element from the equation. But this approach still comes with limitations:
The key challenge with rule-based automation is that it often lacks the wider view of the application. Rules cannot easily account for complex interdependencies or unexpected edge cases that might impact performance or availability.
This is where the true innovation happens. Autonomous optimization unlocks the entire long tail as AI agents can:
The result? Organizations are capturing previously inaccessible savings through autonomous optimization.
How big is the uncaptured long tail in your organization? Consider:
Leading companies like Palo Alto Networks, HP, and Experian are already seeing these impressive results by leveraging autonomous optimization to capture the long tail of cloud savings.
The traditional focus on only the highest-value optimization opportunities makes sense in a world of limited resources. But with the advancement of AI-driven autonomous optimization, this approach is no longer the only option.
Organizations can now effectively address the entire spectrum of optimization opportunities—from the high-value, obvious changes to the thousands of small optimizations that collectively represent significant savings.
Reach out to us to see how your cloud environment could benefit from autonomous optimization. Our team can help you identify the untapped potential in your cloud infrastructure and develop a strategy to capture those savings without burdening your engineering team.
Don't leave money on the table. The long tail of cloud optimization is waiting to be captured.