The promise of cloud computing’s flexibility, scalability, and cost-efficiency is often undermined by the widespread issue of overprovisioning. A study by CAST AI highlights that a significant portion of provisioned resources in Kubernetes clusters remain unused, leading to substantial waste. My experience aligns with these findings, showing that poorly controlled cloud sprawl is a common problem. While CAST AI and other providers offer solutions for optimization, cloud providers themselves are beginning to offer similar tools, despite it being in their financial interest to encourage overprovisioning. Effective cloud resource management requires a shift from cautious overprovisioning to proactive optimization to truly realize the benefits of cloud computing.

Introduction

The promise of the cloud—flexibility, scalability, and cost-efficiency—has been widely embraced by businesses looking to modernize their IT infrastructure. However, recent insights suggest that many companies are failing to fully capitalize on these benefits. A study by CAST AI highlights a significant issue: rampant overprovisioning in Kubernetes clusters, leading to a substantial waste of cloud resources. My own experience in cloud management corroborates these findings, underscoring the prevalence of poorly controlled cloud sprawl. This article was inspired by the Register article “Companies flush money down the drain with overfed Kubernetes cloud clusters”.

Contents

The Register Article on Cloud Sprawl

The Register article highlights the prevalent issue of overprovisioning in Kubernetes clusters, revealing that only a small fraction of allocated resources is utilised. A study by CAST AI found that only 13% of provisioned CPUs and 20% of memory are typically used, leading to significant waste. The study attributes this to an excess of caution among DevOps teams and the complexity of predicting resource needs. It also points out the reluctance to use more cost-effective spot instances due to their unpredictability. The article underscores the need for better management and optimization of cloud resources to avoid unnecessary expenditure.

The Study: A Snapshot of Waste

According to CAST AI, an alarming 87% of provisioned CPUs and 80% of allocated memory in Kubernetes clusters are typically unused. This statistic is drawn from an analysis of over 4,000 clusters, revealing a pervasive trend across major cloud platforms like AWS, Azure, and Google Cloud. The study attributes this to an overabundance of caution among DevOps teams and the complexities involved in predicting resource needs accurately.

The Flexibility Myth

One of the fundamental selling points of cloud computing is its flexibility. Theoretically, businesses should be able to dynamically adjust their resource allocation to meet demand, scaling up during peak times and down during lulls. However, the reality appears to diverge sharply from this ideal. The comment sections of articles on this topic are rife with anecdotes and insights from industry professionals who point out the practical difficulties of achieving true flexibility.

Many companies overprovision as a safeguard against potential surges in traffic that might never materialize. The irony is not lost on commentators who highlight that the very systems designed to provide flexibility and efficiency end up being overstocked out of fear of the unknown.

The Paradox of Choice

Another issue contributing to overprovisioning is the overwhelming number of options available. With AWS alone offering over 600 different EC2 instances, the sheer variety can lead to decision paralysis. When faced with too many choices, businesses often err on the side of caution, selecting more resources than necessary to avoid the risk of underprovisioning. This paradox of choice means that instead of optimizing resources, companies are bogged down by the complexity and end up overspending.

A Cultural Shift: From Sysadmins to DevOps

The shift from traditional sysadmin roles to DevOps practices has also played a role in this overprovisioning trend. Kubernetes, while powerful, introduces its own complexities. As noted by a commenter, the drive to eliminate the need for sysadmins has led to the adoption of Kubernetes, which requires significant expertise to manage efficiently. In many cases, this expertise is lacking, leading to overprovisioning as a form of insurance.

The Real Culprit: Poorly Controlled Sprawl

While overprovisioning is a visible symptom, the underlying disease is poorly controlled cloud sprawl. Without rigorous management and continuous optimization, cloud environments can quickly become bloated with unused and unnecessary resources. This is particularly true for smaller companies that may lack the dedicated personnel to continuously monitor and adjust resource allocation based on actual usage patterns.

The Cost of Convenience

There’s also the matter of convenience. Companies often leave auto-scaling features disabled to avoid unpredictable billing spikes, opting instead for a predictable, albeit higher, monthly cost. This preference for predictability over efficiency further exacerbates the problem of over-provisioning.

Beyond Kubernetes: A Universal Cloud Challenge

The issue of overprovisioning and underutilization extends beyond Kubernetes and containers. While these technologies are often highlighted due to their complexity and the ease with which resources can be over-allocated, the problem is pervasive across various cloud services. Virtual machines (VMs), storage solutions, databases, and network bandwidth can all suffer from similar inefficiencies. Companies often provision excess capacity as a safeguard against potential spikes in demand or due to uncertainties in initial resource requirements. This cautious approach, while understandable, leads to significant waste across the entire cloud infrastructure. Whether it’s oversized VMs running at a fraction of their capacity, underutilized storage volumes, or redundant database instances, the challenge of efficient cloud resource management is universal. Addressing these inefficiencies requires a holistic approach that encompasses all aspects of cloud usage, not just the orchestration of containers and microservices.

The True Incentives of Cloud Providers

While major cloud providers publicly advocate for resource optimization and provide tools to help manage cloud environments, a more nuanced reality exists. It is in their interest to be seen as doing the “right” thing by offering these solutions, enhancing their reputation for customer support and efficiency. However, there is a subtle conflict of interest at play. These providers generate revenue based on the resources consumed—virtual machines (VMs), containers, and other services—regardless of whether they are fully utilized. Consequently, while cloud providers may offer tools to aid in optimization, there is no strong incentive for them to ensure customers achieve high utilization rates. The complexity and moral ambiguity lie in balancing the appearance of promoting efficiency with the underlying business model that benefits from overprovisioning and underutilization. Thus, it often falls to the customers to actively manage and optimize their cloud resources to avoid unnecessary costs.

Automation and Optimization: The Way Forward?

CAST AI offers solutions to these problems through automation and continuous optimization. Their platform can analyze resource usage and automatically adjust allocations to better match actual needs. However, CAST AI is not alone in this space. There are other providers offering similar services, and increasingly, cloud providers themselves are beginning to offer these optimization tools. While it might seem counterintuitive for cloud providers to help customers reduce their spending, they recognize the value in long-term customer retention and satisfaction over short-term profits from overprovisioning.

Conclusion: A Call for Better Management

The findings from CAST AI underscore a critical need for better management of cloud resources. Overprovisioning is not merely a technical issue but a cultural and organizational one. To truly harness the benefits of the cloud, companies must move beyond a mindset of cautious overprovisioning to one of proactive optimization. This requires investing in the right tools, fostering a culture of continuous improvement, and perhaps most importantly, understanding that the flexibility promised by the cloud must be actively managed and not taken for granted. In the end, it’s not just about cutting costs but about leveraging the cloud to its fullest potential. Only then can businesses truly achieve the efficiency and agility that cloud computing promises.