Cloud Infrastructure Optimization for Efficiency and Scalability

Are you sure that you use your cloud infrastructure efficiently? Many companies fail to leverage the potential of cloud technologies properly. Here it goes about overspending or failure to ensure proper system performance.

The key to dealing with such issues is cloud infrastructure optimization. However, this concept is pretty broad. What activities and practices does it actually imply?

Keep reading to get insights into cloud infrastructure optimization and its most critical aspects.

Cloud inefficiency is a significant problem, leading companies to significant losses. In particular, 78% of firms report significant losses associated with cloud waste. The lack of control over cloud infrastructures makes companies pay for idle resources or overprovisioning.

We at AppRecode have worked with many customers facing such issues. Typically, companies need cloud cost optimization due to the following reasons:

• Overprovisioned compute instances
• Idle resources that run without active workloads
• Redundant storage backups
• Siloed operations and a lack of responsibility for inefficient use of cloud resources
• Lack of automation workflows for resource allocation.

With such problems, organizations often face excessively high cloud bills. However, this is not the only problem associated with poor cloud infrastructure optimization. Other common issues include bad scalability and performance issues.

Cloud infrastructure optimization techniques may be challenging to implement. The point is that there are many technically complex aspects that you should consider. The table below summarizes these challenges.

Here are some strategic steps you should take in order to optimize your cloud infrastructure expenses.

It is important to assess usage metrics regularly. With such an approach, you will understand how to adjust instance types, sizes, and storage tiers to align with actual performance needs. Chances are high that some of your workloads require much fewer resources than you allocate to them.

By optimizing them, you can save up to 50% of cloud costs.

Sometimes, it may be very challenging to keep up with changing workloads in your cloud system. That’s where automation can be truly decisive. Make sure to implement built-in or custom auto-scaling policies so that your capacity will match real-time demand.

As a result, you will prevent waste during low-traffic periods, which is a common problem in many cloud infrastructures.

To optimize your cloud spending, rely on reserved instances and provider-specific discounts. This will help you reduce the cost of your cloud computing operations. You can also apply spot instances.

They enhance cloud infrastructure cost optimization by allowing organizations to use unused cloud capacity at discounts of up to 90% compared to on-demand pricing.

It is one of the most important cloud infrastructure cost optimization strategies. You can automate data archiving and deletion with efficient lifecycle management policies.

Sometimes, there is no need to delete unfrequently accessed data completely. You can always move it to cold storage like AWS Glacier or Azure Archive. This can help you reduce costs significantly.

It is important to ensure continuous monitoring for cloud resource allocation. In addition, efficient tagging policies are necessary for tracking ownership and usage of cloud resources. As a result, once any issue occurs, there will be a possibility to track the problem, its outcomes, and those responsible for it.

FinOps is, currently, the most efficient approach to cloud cost optimization. It combines many practices and blends cloud cost monitoring with DevOps to ensure efficient operational control.

In addition, it facilitates cross-department collaboration. Both engineers and representatives of various company departments work together in order to continuously optimize cloud spend.

Cloud infrastructure optimization techniques should focus not only on making the system more cost-efficient, but also on modernizing the architecture. Therefore, it is important to apply a cross-departmental approach to this goal. Cloud engineers should focus on ensuring excellent performance and manageability of the cloud architecture, while business departments should work with them to ensure system efficiency.

“Cloud optimization is not only about cutting your cloud costs. The real efficiency comes from combining architectural improvements, automated governance, and continuous financial visibility. The ultimate goal is to make your cloud architecture efficient across all the major parameters.”

Volodymyr Shynkar, Founder at AppRecode

LinkedIn

This cross-disciplinary approach to optimization and modernization lies at the core of the cloud infrastructure management services we provide at AppRecode.

While strategies define the “what,” techniques describe the “how.” Optimization techniques can be grouped into three categories: cost, performance, and architecture.

With containerization and container orchestration tools like Docker and Kubernetes, respectively, you can ensure more efficient resource utilization and portability. We also suggest applying a microservices architecture. The point is that this approach decouples workloads to ensure faster scaling and updates.

With serverless platforms like AWS Lambda or Azure Functions, you can reduce operational overhead and cost. Such solutions align with cost optimization tips for cloud infrastructure thanks to their core principles, such as charging only for executed code. This property makes serverless solutions ideal for event-driven workloads.

You can also achieve cloud cost optimization with IaC solutions, such as Terraform, Pulumi, or Azure Bicep. They help teams automate provisioning and enforce best practices consistently. Their use will help you establish workflows for repeatable and auditable cloud optimization.

Now, let’s take a look at the major cloud infrastructure optimization tools. The table below summarizes the critical information on such solutions.

At AppRecode, optimization is built into every stage of cloud lifecycle management. The company’s approach combines FinOps methodology, DevOps automation, and AI-powered analytics to deliver measurable results.

The key aspects of our cloud optimization framework are:

• A comprehensive infrastructure audit that provides full visibility into workloads, costs, and performance metrics
• AI-driven algorithms for efficient anomaly detection
• Modern architectural patterns, such as microservices, containers, or container architecture
• FinOps integration for transparent cost accountability and automated reporting
• Continuous optimization of your cloud infrastructure.

We have applied this approach across multiple projects. In particular, when the AppRecode team helped a global e-commerce platform optimize its infrastructure by implementing infrastructure as a code (IaC) with Terraform. You can check out our Clutch page for more successful project examples.

There are many cost optimization tips for cloud infrastructure, but the main challenge is to find the right expertise for such an initiative. 

To handle everything properly, rely on the best IT infrastructure management solutions and a team with significant experience in cloud infrastructure optimization. Contact AppRecode and see how we can help you.

The difference here lies in primary focus areas. Cloud cost optimization is aimed at making the system more cost-effective. Meanwhile, performance optimization is an approach focused on making the system operate efficiently.

We suggest using technologies like:

• Datadog
• CloudHealth
• Kubecost
• AppRecode Cloud Analyzer.

Yes, we have strong hands-on experience with both AWS and Azure and are ready to help you with our knowledge.

Organizations typically experience a 25–45% reduction in cloud costs after cloud infrastructure optimization.