Over the last decade, the cloud has moved from a competitive advantage to a necessity. Its agility, flexibility, and scalability are essential to keep up with today’s dynamic markets and increasingly remote and hybrid workforces.
But as cloud adoption rates have soared, so has the complexity. There’s a public cloud and SaaS app to fill your every need, and according to Oracle, 98% of organizations today use or plan to use multiple public clouds (i.e., a multi-cloud architecture hybrid system architecture).
But complexity has a price. A recent study found that 82% of organizations rank managing cloud optimization as their top business challenge.
We’re here to help you understand the ins and outs of cloud cost optimization. With the right cloud optimization strategy, you can reduce your editures and enhance performance at the same time.
What is cloud optimization?
Cloud cost optimization means actively monitoring, managing, and controlling expenses to be more efficient and reduce waste. It involves analyzing usage and spending, setting budgets, monitoring expenditures, and modifying configurations and resource allocations accordingly.
Cloud resource optimization is crucial for modern organizations due to the pay-as-you-go approach to pricing and resource allocation. As businesses adopt multi-cloud environments across public, private, and hybrid models, the complexity rises exponentially. Without optimization, costs can quickly spiral out of control.
Recent studies suggest a typical organization wastes 30–35% of its public cloud spending due to inefficiency and waste. Proper optimization can eliminate this waste and enable more efficient use of budgets.
Some key benefits of cloud cost optimization include:
- Maximizing performance and capacity while minimizing expenses
- Avoiding overprovisioning of resources that go unused
- Right-sizing cloud workloads based on usage metrics
- Leveraging discounts for reserved instances and spot pricing
- Enforcing budgets, tracking costs, and allocating expenses
As cloud computing adoption snowballs, expense optimization is essential for fiscal responsibility and sustainable adoption. The highly variable nature of the technology makes cost management an ongoing priority.
Understanding cloud costs
Understanding what contributes to expenses in this domain provides a foundation for our discussion. Most service providers’ charges fall into three major categories:
- Compute costs are based on the processing power consumed by your instances, VMs, and other components. These costs depend on the RAM, storage capacity, and processing cores your cloud applications consume. For example, machine learning tasks use more processing power, so they cost more.
- Networking costs within cloud infrastructure optimization are influenced by bandwidth usage and data transfer within your cloud application environment. Most providers offer tiered pricing structures to cater to businesses with higher usage levels.
- Storage costs are based on the type and quantity of storage used over a specific timeframe. Storage types include block, file, and object storage, which have different ease of access, performance, and redundancy levels.
Other costs include maintenance and system upgrades, patches, and support.
The evolution of cloud computing and its costs
Cloud computing has come a long way over the past two decades. What started as a novel concept in the 1990s has become a cornerstone for modern companies’ operations. However, with its flexibility and convenience came new challenges around managing expenses and budgets.
In the Beginning
While the ideas behind cloud computing had been around for years, it truly entered the mainstream in the mid-2000s. In 2006, Amazon started EC2, a platform where companies can rent computing power instead of owning physical servers. This pay-as-you-go model was revolutionary and enabled far greater flexibility. Other tech giants like Microsoft and Google quickly followed suit with their own services.
Growing pains
As adoption grew through the late 2000s, many organizations encountered unforeseen challenges regarding expenses in the virtual environment. The ever-changing nature of this technology made it difficult to anticipate and budget for. Companies would overprovision resources, which led to paying for excess capacity. Cloud providers also charged for network egress bandwidth, which added up quickly with large data transfer volumes. Vendor lock-in was another concern, where customers could get stuck paying higher and higher rates after committing to a single provider.
Modern cloud cost management
Today, cost-related challenges persist, but new techniques have emerged to enhance expense optimization and control. Auto-scaling automatically adjusts resource capacity based on demand. Reserved instances allow upfront commitments to secure lower rates. Spot instances enable purchasing unused capacity at deep discounts. The workload optimization and rightsizing analyze usage and requirements to eliminate waste.
However, cross-cloud cost management across multiple vendors and services continues to be difficult. As cloud services expand with AI, containers, edge computing, and more, businesses must continuously improve their cloud cost efficiency and reduce waste. Mastering expenses requires a combination of strategy, tools, and organizational culture.
The importance of cloud optimization strategy
Effective strategic planning is imperative for aligning business expenditures with its goals and ensuring investment efficiency. It enables cross-functional collaboration so technology best practices are implemented organization-wide. Planning can also help you identify skill gaps, training needs, and structural changes needed to optimize cloud usage.
Strategic planning for cloud computing optimization is essential for several other reasons, too:
- Resource efficiency: Cloud cost optimization helps identify underused or unused resources that you can downscale or eliminate to save costs.
- Budget forecasting: With optimized spending, businesses can gain a clearer understanding of their expenditures, which is crucial for precise budget forecasting and allocation.
- Competitive advantage: Cost savings from cloud optimization solutions can be reinvested in other areas, providing a competitive advantage. Lower operational costs might result in lower customer prices or more funds available for innovation.
- Improved customer experience: Efficient resource allocation can lead to better performance, improving user experience and, potentially, the bottom line.
How cloud spending goes haywire
As important as optimization is, it’s not easy. There are a huge number of challenges that lead to business overspending, making optimization difficult.
Lack of planning and governance
Many organizations manage expenses reactively. With the average organization having hundreds of applications and utilizing multiple platforms, it’s almost certain that spending will spiral out of control without a documented optimization strategy and governance. Lack of visibility into usage and spending patterns across the organization leads to unexpected costs. It also leaves no way to reliably identify and shut down idle resources or unused services. And as data accumulates across cloud apps over time, unchecked storage costs can occur. Lack of proper governance and policies also allows users or departments to provision resources independently of IT, leading to uncontrolled growth in spending.
Overprovisioning
Organizations often overestimate resource needs and overprovision their infrastructure. With no strategic plan or visibility, they can’t take advantage of better pricing options like reserved instances or rightsize their instances when needed.
Multicloud mishaps
Disjointed billing and dashboards across multiple cloud providers reduce visibility into overall usage and spending trends. For example, a company using AWS, Microsoft Azure, and GCP must manually compile reports to gain a complete view, leading to unexpected costs as needs change. Likewise, unplanned sprawl occurs when business units independently procure services without IT oversight.
Organizational challenges
Effective cloud optimization solutions require goal alignment between IT, Finance, and business units. Without shared objectives, suboptimal decisions occur. For example, IT seeks to maximize efficiency and reduce waste, while business units want flexibility and speed. Mismatched goals lead to overprovisioning, shadow IT, and poor cost visibility.
An inability to accurately allocate expenses across business units also hinders optimization efforts. Often, organizations lack expertise in using native cloud tools and cloud optimization best practices. Finally, reliance on manual processes makes optimization and governance difficult to scale. Luckily, best practices and technology exist to help you overcome these challenges. We’ll discuss these soon. But in case it’s not already clear, let’s look at the benefits of optimizing your spending.
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Cloud optimization best practices and tools
Tackling cloud overspending requires a careful mix of tools and best practices. In our experience, the top four are:
1. Utilization tracking
Cloud utilization tracking involves monitoring and analyzing the usage of resources like computing, storage, and networks. It provides visibility into how efficiently cloud environments are leveraging these resources. Key metrics tracked include CPU, memory, storage, network usage, and the number of virtual machine instances, usually tracked over time to identify trends and patterns.
Tracking utilization over time helps make sure workloads are correctly sized, identifies opportunities to optimize costs, and highlights where additional resources may be required. Cloud platforms provide native tools like AWS CloudWatch, Azure Monitor, and GCP Stackdriver for tracking utilization. Analyzing utilization data helps avoid over-provisioning to lower costs and ensures there is enough capacity to meet workload demands. Efficient utilization tracking is essential for effectively managing environments.
2. Rightsizing resources
Rightsizing involves provisioning an optimal amount of resources to run applications and workloads cost-effectively. It requires analyzing utilization data to determine the right mix of cloud services and the appropriate size of resources to support workloads and eliminate any overprovisioning.
Rightsizing also ensures resources are not under-provisioned, which can lead to performance issues. Usage patterns should be studied to rightsize resources and scale them based on demand. Tools like Azure Cost Management and AWS Cost Explorer can help model and assess size options.
As application usage changes, capacities must be re-evaluated and resized periodically for continued optimization. Rightsizing takes continuous effort but helps avoid wasting resources and reduces cloud costs significantly.
3. Reserved instances
Cloud service providers offer prepaid reserved instances of discounted compute capacity. Committing to a cloud resource optimization for 1-3 years instead of paying as you go can save 10-30% — and sometimes significantly more. They are recommended for steady-state workloads that require a predictable amount of compute over time.
With this model, you reserve capacity by instance type, region, tenancy, and term, and it’s always available to you when needed. If usage exceeds reserved capacity, you pay on-demand rates for the excess. The good news is you may be able to change your reservations even in flight — the bigger your company, the more flexible your agreement will likely be.
Choosing optimal reserved instance terms and categories requires analyzing historical usage trends and optimizations to minimize costs. Reservations provide budget predictability and reduce overall computing costs substantially for stable workloads. But they require planning and commitment to realize the benefits.
4. Automation of resource provisioning and de-provisioning
Manual provisioning and de-provisioning can be time-consuming and error-prone, especially for large environments. Automating these processes improves efficiency and agility in deploying and scaling cloud-based resources.
That’s especially true for services that don’t need to be active all the time, like development environments. Say your company uses 5000 CPUs, of which your dev environment comprises 2%. By shutting down (i.e., de-provisioning) the dev environment at night, you’ll save 10% of your total costs! In a large company, that can equate to millions of dollars.
Automation can be achieved through infrastructure-as-code tools like Terraform, CloudFormation, and Ansible, which allow declaratively defining and deploying resources. Scripts can also automate provisioning using CLI tools and APIs of the cloud platforms. And auto-scaling tools allow the automatic launching and termination of resources based on metrics like utilization, time, costs, and so on. Automated de-provisioning should include built-in approvals, alerts, and processes for governance.
Automation makes cloud infrastructure agile and optimizes resource usage and costs by only keeping active resources running.
If you find this article interesting, we recommend taking a closer look at
Bridging strategy with action: testing before investing
Even with the right strategies, many organizations hesitate to experiment with new services due to cost risks. This is where proof-of-concept (PoC) projects come in. With AWS, you can try new cloud services for free, validate their value, and see measurable impact before committing resources at scale.
We’ve covered this approach in detail in our article: AWS Proof of Concept: How to Try New Cloud Services for Free. Leveraging PoCs not only reduces financial uncertainty but also accelerates innovation by helping your teams adopt, test, and optimize cloud solutions with confidence.
After you implement these first four, there are several other ways to tackle budget overspending and efficiency. Here are a few of them:
Spot instances
Leveraging spot instances for non-critical workloads and short, batched jobs gives you access to a cloud provider’s unused compute capacity at massively reduced prices — up to 90% off on-demand pricing. Once you’ve done your strategic planning, you’ll know which workloads qualify.
Cost allocation
Cost allocation assigns cloud costs to departments and business units based on resource tags and usage. It enables chargeback and accountability by tracking spending per team. Allocated costs can integrate with billing and budgeting to optimize cloud usage and tie to business drivers. Well-defined allocation rules and automating the process are key for effective chargeback. Cost allocation provides visibility into spendings and drives optimization through accountability.
Governance policies
Governance policies establish a set of rules guiding resource allocation in your cloud environment while ensuring compliance with regulations and data security. These policies may also include setting spending limits, tagging for better resource management, and workflow for budget approvals.
Optimization tools
Optimization tools can help you monitor, analyze, and optimize your expenditures. Common features include cost reporting, right-sizing recommendations, usage analytics, budget alerts, and reserved instance planning. Your provider will have native cloud optimization solutions, and there are plenty of third-party options, too — CloudZero, DataDog, Cloud Checker, Granulate, and the list goes on!
Look for one that tracks multiple cloud accounts and provides consolidated views across hybrid/multi-cloud environments. Integrations with billing, DevOps, monitoring, and financial systems will allow seamless workflows. Optimization tools are key for unlocking substantial cost savings and driving efficiency in dynamic environments. But remember, they’re not a replacement for everything else we’ve discussed up to this point!
