How Can You Optimize Cloud Resources for Cost Savings?
As businesses increasingly move to the cloud, managing cloud expenses has become a top priority. The challenge isn’t just about harnessing the power of cloud resources—it’s about doing so in a way that maximizes efficiency and minimizes costs. With cloud bills quickly adding up, the key to long-term savings lies in strategic optimization. To help you navigate this complex landscape, we turned to ten cloud computing specialists, from managing directors to Senior Technical Managers, who have honed their expertise in cost-efficient cloud solutions. Their strategies, ranging from implementing auto-scaling and scheduling to locking in long-term cloud contracts, provide a comprehensive guide to keeping your cloud infrastructure lean and budget-friendly.
- Implement Auto-Scaling and Scheduling
- Tailor Strategies to Client Needs
- Utilize Auto-Scaling and Reserved Instances
- Explore Various Cost Optimization Tactics
- Centralize Data for Efficiency
- Align Storage Type with Needs
- Monitor Usage and Adjust Plans
- Schedule Periodic Data Clean-Ups
- Capitalize on Spot Instance Savings
- Commit to Long-Term Cloud Contracts
Implement Auto-Scaling and Scheduling
Optimizing cloud resources for cost savings involves a strategic combination of right-sizing, automation, and continuous monitoring. One of the most effective methods we use is auto-scaling and resource scheduling.
By implementing auto-scaling, we ensure that our cloud resources dynamically adjust to the actual workload—scaling up during peak times and down during low-usage periods. This prevents over-provisioning and ensures we only pay for what we actually use.
Additionally, we employ resource scheduling to automatically shut down non-essential instances during off-hours, such as development or testing environments that aren’t needed 24/7. This simple practice can lead to significant savings over time.
Coupled with continuous monitoring and regular cost reviews, this approach allows us to maintain optimal performance while minimizing unnecessary cloud expenditures. This focus on efficiency not only reduces costs but also frees up resources to reinvest in further innovation and growth.
Sergiy Fitsak, Managing Director, Fintech Expert, Softjourn
Tailor Strategies to Client Needs
We optimize cloud resources for cost savings by implementing a strategic approach tailored to each client’s specific needs. We begin by right-sizing resources, ensuring that our clients only pay for what they use, whether that involves scaling down underutilized services or selecting more cost-effective cloud plans.
Additionally, we leverage automation to manage workloads efficiently, deploying auto-scaling solutions and automated shutdowns for non-essential services during off-peak hours. By continuously monitoring usage and conducting regular audits, we can further refine these resources, ensuring our clients benefit from the most economical and efficient cloud solutions available.
Steve Robinson, Senior Technical Manager, Go Technology Group
Utilize Auto-Scaling and Reserved Instances
As cloud computing specialists, we optimize cloud resources for cost savings through several key strategies. First, we implement auto-scaling to adjust resources dynamically based on demand, ensuring we only pay for what we use. We also leverage reserved or spot instances for predictable workloads, which offer significant discounts compared to on-demand pricing.
Next, we regularly review our resource utilization using tools like AWS Cost Explorer or Azure Advisor to identify and eliminate underutilized or idle resources. Rightsizing instances based on actual performance needs helps us avoid over-provisioning. Additionally, we use multi-cloud strategies to take advantage of competitive pricing from different vendors.
We implement storage lifecycle policies to automatically move data to lower-cost storage tiers when it becomes less frequently accessed. Furthermore, leveraging serverless computing options, such as AWS Lambda, can reduce costs by eliminating the need to manage and pay for idle server time.
By continuously monitoring and analyzing our cloud usage, and optimizing configurations accordingly, we manage to achieve substantial cost savings without compromising performance or scalability.
Nikita Baksheev, Manager, Marketing, Ronas IT
Explore Various Cost Optimization Tactics
To optimize cloud resources for cost savings, consider:
- Right-sizing: Match instance sizes to workload requirements.
- Reserved Instances: Commit to long-term usage for discounted rates.
- Auto-Scaling: Scale resources up or down based on demand.
- Idle Resource Elimination: Remove unused resources.
- Storage Optimization: Use cost-effective storage options.
- Cloud Native Services: Leverage serverless and managed services.
- Monitoring and Analytics: Track usage and costs with tools like Middleware.
- Consolidation and Standardization: Streamline resources and workflows.
- Discounted Pricing Models: Explore spot instances, scheduled reserved instances, and volume discounts.
- Regular Cost Audits: Continuously review and optimize cloud spend.
Ashwini Dave, Product Marketer, Middleware
Centralize Data for Efficiency
To optimize cloud resources for cost savings, it’s best to eliminate data silos. Designing a central hub of information, rather than having each of your teams maintain their own database, will not only help you minimize costs but also enable you to ensure data hygiene. With everyone accessing relevant insights from a single source, you’ll consume much less cloud storage, which leads to cost savings and enhanced collaboration among teams.
Jared Atchison, Co-Founder, WPForms
Align Storage Type with Needs
The best way to optimize cloud resources to save costs is to pick a storage type that aligns with your needs. You don’t necessarily have to go with high-tier data storage and management options if you don’t need them. So, it’s best that you carefully assess your needs prior to selecting the cloud solutions you leverage. You can scale as your data access and management needs change over time. You can then opt for premium subscription options, unlocking your access to advanced storage, management, and analytics capabilities.
Stephanie Wells, Co-founder and CTO, Formidable Forms
Monitor Usage and Adjust Plans
In my experience, monitoring your resources and how you use them can help you save on your cloud costs. Tracking and analyzing this information will help you figure out if you’re paying for a feature or space that you’re not using. We use the native analytics tool of our program to figure this out; odds are, your tool has a similar feature. The next step is to downsize where appropriate or bundle with a different, more flexible option if you find you’re paying to buy extra storage each month. Either way, keeping an eye on your cloud resources and picking the right plan for your needs is an excellent way to cut unnecessary costs.
Daman Jeet Singh, CEO, FunnelKit
Schedule Periodic Data Clean-Ups
You can optimize cloud resources for cost savings by planning periodic clean-ups to remove unnecessary data. You may not end up using all the data you collect over time. This unused data often goes unnoticed and occupies unnecessary space on the cloud. The size of the data keeps growing, costing you a significant amount of money in the long run. Scheduling periodic clean-ups to delete unnecessary data helps you free up space that you can use to store useful information and reduce storage costs in the process.
Andrew Munro, Founder & President, AffiliateWP
Capitalize on Spot Instance Savings
Cost-effectiveness can be achieved by utilizing excess capacity that cloud providers make available at a lower price. Unlike reserved or on-demand instances, Spot Instances can be up to 90 percent cheaper. I begin by analyzing the pattern of our workload and usually find those tasks that are flexible and can tolerate interruptions. These, in theory, would be the best candidates for Spot Instances.
Batch processing jobs or non-critical development environments have often been changed without denting overall productivity using Spot Instances. This interruption risk is mitigated by selecting a mix of Spot Instances and On-Demand Instances. In this way, a hybrid model ensures that no critical operations are interrupted, while tasks whose timing is not as crucial benefit from the lower costs of Spot Instances.
I have also introduced automation that takes care of the provisioning and management of the Spot Instances. This includes tooling, such as auto-scaling groups with Spot Fleet or Spot Instances, that automatically replace interrupted instances and maintain the required capacity without human intervention. Furthermore, I was able to integrate Spot Instances into our cloud strategy to realize cost-effectiveness, leveraging the resources optimally for considerable cost savings with no compromise on the flexibility or performance of the cloud infrastructure.
Yogesh Kumar, Digital Marketing Head, eResource Scheduler
Commit to Long-Term Cloud Contracts
Cloud Computing services are offered as pay-as-you-go services. While this is great for flexibility, it is also more expensive. When you become a long-term Cloud customer, you can optimize your cloud resources by committing longer term, often one or three years. Applying these cost savings can be done easily without having to make any technical changes.
Any other cost optimizations will most likely include technical changes. One strategy we keep discussing with our customers is ensuring that all cloud resources are used efficiently. For example, you might have assigned more CPU and memory resources to an application than it needs. Rather than allocating more resources upfront, it’s better to allocate them only when needed. When you use the pay-as-you-go model correctly, you dynamically assign more resources when you need them and remove resources when you don’t need them. This is the biggest benefit of running on the cloud, but it also needs to be correctly implemented.
Recently, another interesting cost-saving strategy has emerged. As more cloud providers started offering ARM64-based CPUs, it became apparent that the cost of CPU time is much lower on ARM64 than on Intel and AMD architectures. If the application can be adapted to run on ARM64, you can make good price/performance gains.
Edward Viaene, Managing Director, IN4IT LLC
