22.06.23 11 Min read
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Cloud infrastructure comprises vast swathes of interconnected components. Offering unparalleled scalability and resources, businesses have spent the last decade exploring the cloud’s hyper-agile tools – to great innovation. Between 2010 and 2023, the global cloud computing market grew from $24.63 billion to $600 billion; cloud migration has upended industries and, on the surface, shows no sign of slowing down.
However, business management consultants McKinsey & Company note that digital transformation projects have – across the board – captured much less value than initially expected. Only 25% of survey respondents reported to have reaped the maximum cost benefits that their recent transformations could have achieved.
As organizations dig to uncover the missed opportunities hidden within their growing cloud spend, there is growing frustration at the often complex and opaque cloud architecture. The elastic scaling of resources – once seen as advantageous – are placing similarly skyrocketing demands on budgets. As a result, some organizations are swearing off the cloud for good.
Cloud Spend Management (CSM) offers a way to peel back the layers, lending new insight into resource optimization opportunities. By procuring strategies, processes and tools, organizations are empowered to break down their complex web of cloud spend into a cohesive and accessible map of moving parts.
Cloud budget busters very rarely have a singular cause. While cloud vendors’ depths of resources certainly facilitate widespread overprovisioning, cloud spend management must look deeper than surface expenses. FinOps is another term for CSM, and highlights the process’ explicit focus on removing blockers. CSM is not about saving money. Instead, it identifies the best ways in which your organization can foster cross-functional collaborations about where to invest and when. To get started, it’s vital that your organization identifies the root causes of its cloud cost disconnect.
Here are the 4 major areas of friction highlighted and combated by GlobalDots’ decades of industry experience.
Cultural challenges to cloud spend management are some of the hardest to overcome. Heavily siloed organizations struggle the most here, as cloud overspend is often a joint effort. Without any form of shared cloud optimization language, organizations are left at the mercy of old school, pre-cloud attitudes. For instance, the bane of many modern cost control attempts are cloud architects that overlook cost considerations. They may make poor design choices, leading to pre-selected application features that unexpectedly accrue costs down the line. Additionally, developers may write code that performs poorly, consuming excessive infrastructure resources.
This is a habit that can be traced back to static on-premises setups, which often prioritized availability over financial efficiency: 30% utilization was commonplace, as any IT budget was simply treated as a necessary evil. However, when this attitude is transferred to the cloud, such excess resources rapidly incur monthly charges.
In these situations, relying solely on cloud cost management tools is unlikely to be effective. Instead, a focus on performance engineering is necessary. Weighing the business impact of investing time and resources against the cost of such inefficiencies is the first step. A two-pronged process that allowed an eCommerce giant to save $1.4 million annually started with a third party (us) lending thorough analysis of every resource and provisioning decision. With a handful of bad habits identified, we were then able to get the ball rolling. Automation played a heavy role in the immediate cost-savings, while bad habit busting paved the long term path toward a major reduction in cloud spend – even while the organization grew by 30%.
Rather than focusing solely on the flat metric of total cost, FinOps campaigns drive value via a unit economics model. When looking at cloud expenditures, total spending may increase one quarter. However, if that cloud spending enables the organization to deliver products or services to a larger customer base, the cost per customer decreases, leading to increased profitability.
While unit cost metrics promise a new approach to cloud spend, they require deeper visibility than ever before. Complicating this process is the fact that cloud vendors don’t always offer the in-depth tagging that organizations require – amplified over multiple cloud vendors, campaigns to drive visibility can quickly find themselves foggy and uncoordinated.
Amplifying these difficulties even further is the fact that cloud complexity is self-perpetuating. Infrastructural complexity often leads to a hodgepodge of multiple siloed teams, further hampering cohesive visibility and exacerbating the costs of FinOps implementation. Without shared views of goals and initiatives among teams, increased spending might trigger concerns and be prematurely halted, even though it plays a pivotal role in optimizing cloud costs and driving enhanced business value.
While those at the top battle severe cloud blindspots, the disconnect between budget issuers and on-the-ground engineers remains a chasm. Resource allocation represents one of the biggest disconnects in today’s cloud infrastructure. When engineers wind up projects, many fall into the trap of leaving resources and workloads untagged in the false assumption that it’ll save time. Only now are teams starting to pick at the tangled mess of unallocated and unstructured workflows. Industry fears around cloud visibility are well-documented, with significant impacts on both cost and security.
The Enterprise Strategy Group’s 2022 report on The State of Security highlights this challenge particularly well. Respondents were asked to rank the overall challenges they face as a result of their cloud setups, almost all of which centered around cloud blindness. 39% of organizations identified the discovery of misconfigured workloads as their leading challenge, while 22% of respondents named (and shamed) their loose and outdated inventory of cloud-based assets. Such lack of granular cloud understanding leads to an overarching instability in cloud confidence, resulting in the following challenge.
Another habit that lingers long after an application’s pilot phase is the refusal to commit to long-term resource provisioning. Scared and uncertain about future usage – alongside concerns around overcommitting – many organizations choose not to make any long-term commitments. This approach leads to unnecessarily high expenditures as cloud vendors charge extra fees for last-minute resource purchases. In reality, organizations that have progressed beyond the early pilot stage typically hold longer-term experience of their in-production applications. With this data comes a certain level of usage predictability. Knowing which resources to purchase reserved instances for is its own struggle, however – the same challenge around cloud visibility fogs up many attempts to identify resource commitment savings.
While instance commitments offer greater cloud budgeting opportunities, another form of commitment threatens such savings: vendor lock-in. Specific cloud services and technologies often have multi-year contract lengths, which can drastically limit any chance to leverage more cost-effective options and increase cloud spend efficiency.
The sheer range of challenges facing FinOps attempts – across both small organizations and their more mature peers – offer a bright rainbow of potential pitfalls. Each issue requires its own response, ranging from employee empowerment to resource resizing that matches real-time usage. If all this necessitated manual intervention, then the cost of cloud spend management would vastly outstrip the potential economic benefits. Thankfully, however, automation offers some of the highest degree of cloud costs management.
The identification of cloud inefficiencies – and subsequent attempts to tackle them – must be cohesive. It’s not as simple as just dropping generic cost data into engineers’ workflows – or winding up a project to prune back pre-existing workloads. After all, analysts and engineers are busy with their already-established projects. Taking time out of this accrues its own financial cost.
At GlobalDots, we’re proud of our innovation hunting expertise. With our assistance, increasing numbers of organizations are discovering the benefits of cloud spend automation. Its real-time rightsizing across large swathes of business resources helps relinquish the cost of expensive human hours – freeing up your team to focus on their wider cloud stance. By scouring the rapidly-evolving industry of cloud optimization solutions, GlobalDots gives organizations the keys to unlock their cloud potential.
The cornerstone of cloud spend management is visibility. However, the native tagging capabilities offered by cloud vendors often leave a lot to be desired. Furthermore, for hybrid environments, even highly-tagged layouts can be a nightmare to consolidate and track cross-platform. Automation offers a significant advantage for organizations seeking true cloud visibility.
By utilizing a tool that gathers data from various cloud providers and software platforms like AWS, Azure, New Relic, MongoDB, and Snowflake, all infrastructural costs can be consolidated into a unified format. This comprehensive visibility enables businesses to reveal significant blind spots.
Supercharging your cloud infrastructure in a way that breaks down costs per customer, team, and even product feature enhances financial transparency and accountability. Understanding the cost implications of each operational unit enables strategic decision-making, pinpointing profitable or costly aspects and facilitating resource allocation.
Moreover, the integration of cost and data visibility, tagging, and allocation significantly enhances budgeting and forecasting capabilities. Clear visibility into past and current expenses empowers companies to accurately predict future costs, leading to improved budget planning and control.
Insufficient block storage exposes services to application failures, data loss, and performance degradation. Conversely, provisioning excess storage leads to unnecessary costs, resulting in organizations paying two to three times more than necessary. This creates a challenging cost-performance dilemma where organizations tend to lose out. Complicating things further is the fact that native systems also lack the ability to manually decrease volume allocation – conveniently locking customers into such overspend.
The root cause of this chronic over-allocation comes down to one thing: a lack of clarity surrounding an application’s real requirements. The first step to solving this conundrum is a clear understanding of required volume size – but that’s not the whole story. Attempting to manually change resource commitments in response to real-time changes would be intensely costly – and time-draining – perhaps even negating any potential cost savings in the first place.
One tool that promises immense savings is an auto-scaler that eliminates the trade-off between performance and cost. It automatically adjusts volume capacity based on changing application demand, leading to a significant performance boost. Thanks to this, throughput and IOPS are improved by approximately 300%. Manual adjustments also become almost obsolete, enabling the team to focus on critical maintenance tasks.
AWS Reserved Instances (RI) were introduced by the hyperscaler in an effort to address the high costs of on-demand resources. For a set amount of instance usage across specific time periods, RIs offer discounted rates. This makes them an accessible option for organizations adopting a FinOps culture. Despite their accessibility for FinOps amateurs, organizations with even a deep understanding of RIs still struggle with over-attribution. For instance, developing cloud spend management attempts will cut out some on-demand instances – but retain some in case of a sudden demand surge.
A new tool now helps reduce on-demand expenses by dynamically buying and selling AWS RIs based on changing infrastructure needs. Automatically aligning resource purchases with actual usage, this tool provides the flexibility of on-demand instances while benefiting from the discounted pricing structure of RIs. With near real-time adjustments to EC2 commitments, organizations can achieve cost reductions of around 60% compared to equivalent on-demand prices. Furthermore, cloud engineers save time as they no longer need to constantly review and adjust discount commitments. Through a machine learning-driven purchasing process, the tool becomes increasingly optimized the longer it operates in proximity to your organization’s resources.
Finally, demonstrating its commitment to FinOps maturity, the tool offers a buy-back guarantee for unused RIs at the end of each month. These credits contribute to lowering the cost of the next month’s bill, ensuring continued cost savings and efficiency.
Open-source containerization has revolutionized application development. However, tuning resources within Kubernetes has proven to be cumbersome and frustrating, eating up limited time and resources.
An automated approach has emerged as a K8s cost conqueror by fitting containers into pods based on real-time resource demands. Applications require fewer running pods – resulting in immediate cost savings. What sets this solution apart is its continuous learning capability, adapting to the evolving nature of your application. It fine-tunes resource allocation to match precise usage levels. The long-term maturation of Kubernetes is further supported by the solution’s transparency, as it breaks down once-complex cost structure workload-by-workload, providing valuable insights into the financial impact of each improvement.
This automated approach not only delivers instant savings but also ensures ongoing optimization as applications evolve over time. The transparent cost breakdown empowers organizations to make informed decisions and drive continuous financial improvement within their Kubernetes environments.
Kubernetes management is precisely how GlobalDots helped save one fintech firm 90% of their annual K8s cost. The dynamic nature of their workloads, alongside the opaque complexity of many Kubernetes clusters, had sidelined many previous optimization attempts. By the time they reached out to us, their annual K8s management spend had reached a daunting $816,000. However, by partnering with GlobalDots, they were guided to an automated optimization solution that granted brand new insight into their Kubernetes environment.
As the complexity of such resource management was the primary cause of such overhead, GlobalDots prioritized an insight-driven solution that would sit adjacent to their preexisting architecture. This way, real-time data into resource usage could be collected and streamlined – with no pre-requirement to blindly reconfigure mission-critical infrastructure. The solution was able to see exactly which workloads were lacking intelligent configuration and hence consuming too many resources. The advanced algorithm and performance capacity management of the autonomous optimization solution then made it incredibly quick and simple to assign the correct number of resources for each workload.
By streamlining idle resources, the organization was able to drastically decrease the number of worker nodes that required management. Post-optimization, the annual K8s cost fell to just $72,000 with no compromise on performance or scalability. Furthermore, the automation aspect of the solution significantly reduced manual efforts, allowing the IT team to focus on more strategic tasks. The solution provided ongoing monitoring and optimization, ensuring that the fintech firm continued to benefit from cost savings over time.
Bring Out the Best in Your Cloud Budget
Many organizations identify different areas for cost savings but struggle to implement these savings, leading to uncertainty about which department drives costs upwards.
A case study by GlobalDots reveals how we managed to reduce a client’s cloud bill by $1.5 million annually. This client, a giant eCommerce group, had migrated its operations to the cloud without any proper architectural preplanning, which led to a disproportionate cloud bill and minimal insight into usage and spending on resources.
Despite the mounting costs, the group sought a cost-reduction solution from their cloud consultancy firm, which referred them to GlobalDots due to their expertise in FinOps methodologies and tools. Through excessive monitoring of Cloud costs and interviewing several key officials in the company, GlobalDots was able to map the main costs and identify multiple savings opportunities. Their proposed savings of $1.5 million annually not only included cost optimization solutions but also an end-to-end service for the company, leading to greater shared responsibility on cloud cost management.
Don’t let your organization fall into cloud stagnation or regression – GlobalDots are innovation hunters that couple forward-thinking organizations with the cloud solutions that bring out the best in your cloud budget. GlobalDots’ multi-vendor approach has granted leaders such as SentinelOne, Gong, and Playtika the chance to optimize and evolve their approach to cloud costs. To discuss how your cloud architecture can benefit from GlobalDots‘ solutions, get in touch today.
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