What is cloud optimization?

It involves creating an efficient cloud infrastructure that aligns resource provisioning with the demands of applications and workloads in real time to strike a balance between performance, compliance and cost-efficiency needs. Cloud optimization falls under the purview of CloudOps, a practice modeled after DevOps that is designed to manage and optimize the delivery and performance of cloud services.

As IT resources are increasingly spread across private and public clouds, multicloud and hybrid cloud infrastructures, CloudOps and DevOps teams must place a greater focus on managing cloud resources. The challenge is keeping cloud costs under control while ensuring the availability and optimal performance of cloud applications.

An effective cloud optimization strategy uses cost management tools and other optimization tools that increase visibility into cloud environments. Enhanced visibility enables DevOps teams to get a more accurate picture of resource usage, along with cloud and application performance. This data informs the reduction or elimination of overprovisioned resources and helps create a more efficient, better performing cloud environment.

Teams also use automation and machine learning tools to manage and allocate workloads and resources. For example, automation tools can adjust resource allocation during peak usage, move workloads between instances based on instance health, or shift workflows between public and private clouds based on demand.

Teams often use machine learning tools to analyze large datasets and deliver insights on how to improve cloud operations. These tools enable experts to spend less time managing and more time innovating.

It is important to understand what aspects of cloud services are fit for optimization, and how to implement a cost-effective approach to optimizing cloud resources.

Cloud environments offer many enterprise benefits, including the ability to scale on demand. Cloud migration—moving on-premises data, applications and workloads to the cloud, or from cloud to cloud)—can offer flexibility, visibility and increased data security. This flexibility enables enterprises to better meet customers’ needs and achieve business objectives. However, with cloud adoption, many businesses have found that they are spending more than expected on cloud computing to access these benefits.

Cloud environments are dynamic, with ever-shifting resource demands. Idle resources and unmanaged cloud environments can quickly lead to overspending and security issues. Without the proper tools, IT departments are largely guessing which cloud resources they need and which ones undercut cost savings measures and other benefits of the cloud.

Cloud optimization brings cloud expenditures under control, making the cloud the cost-effective solution it was designed to be. An optimized cloud environment moves resources to meet workload demand, reducing bottlenecks and unexpected service outages. It also helps create a more secure cloud environment.

The performance of cloud services is a primary concern for business and IT teams. Their challenge is balancing the need for high performance and availability while maintaining cost-effectiveness and staying within budget. Cloud optimization offers a pathway for transformation that reduces waste and maintains performance.

Organizations often focus their optimization efforts on cloud cost optimization, monitoring and reporting, performance and security.

Cost reduction is often a top goal in cloud optimization; however, a cloud cost optimization strategy isn’t just about reducing your cloud usage. It’s about making sure you are paying for what you need and minimizing wasted resources. Cloud cost management must prioritize the performance, security and scalability of cloud services. Spending less is meaningless if it puts a business at risk or otherwise damages the business.

Managing a cloud budget is a dynamic process because application and workloads demand changes all the time due to factors such as traffic fluctuations and organizational growth. Expenditures such as compute costs (costs associated with instances, virtual machines (VMs), and the level of automation an organization is implementing), cloud storage and support services all contribute to the overall bill. When approaching optimization, organizations should be sure to understand their cloud bill, what services they are paying for and why. For example, is a high-performance cloud plan or a low-cost plan more appropriate for an organization’s needs?

Automated tools can help with provisioning resources from cloud service providers. These tools automatically match resources with application demand and adjust resource allocation accordingly. The practice of overprovisioning resources (provisioning resources that cover application needs at peak usage but might be unnecessary at times of lesser demand) as a safety net can quickly increase costs and cut into profitability.

A better solution—achieved through cloud optimization—is to remove silos between business, IT and DevOps teams to find pricing structures and resourcing tools that meet the needs of the entire enterprise. Through the implementation of a cloud optimization strategy, enterprises can increase the ROI on their cloud investment and drive business value.

Gartner estimates that by 2027, 70% of enterprises will use cloud platforms to optimize their business initiatives, a 55% increase from 2023.¹ With this type of expansion, visibility into cloud infrastructure is key to understanding and optimizing application performance.

Cloud management tools help IT departments monitor key metrics related to application performance such as network traffic, error rates, CPU usage and latency. Monitoring these metrics in real time can help IT teams uncover inefficiencies and unused resources through detailed reports that correlate resource usage with cloud costs.

Enterprises should seek out monitoring tools that offer reporting with context into the broader cloud architecture. Without this context, data can remain siloed, making it more difficult to understand how the organization uses cloud resources.

Overprovisioning resources to safeguard application performance is not a viable long-term solution. Organizations should aim to pay for the cloud services they need and nothing more. A streamlined cloud infrastructure enables IT departments to better understand application performance and how users are interacting with applications.
Without a performance optimization strategy, cloud applications can be subject to downtime and high latency rates, which lead to unsatisfactory user experiences.

Performance optimization techniques include:

• Load balancing: This technique distributes workloads and traffic across servers. There are several load balancing techniques—some distribute traffic evenly across servers, some direct traffic to the highest functioning servers or the nearest servers—but all techniques aim to optimize performance. Load balancing can help minimize bottlenecks during peak usage and accelerate application performance.
  
  
• Use content delivery networks (CDNs): A geographically disperse group of servers (CDNs) can provide faster service for web-based applications. CDNs host applications and data on servers closer to users, reducing latency and improving service delivery.
  
  
• Caching: Unused or unnecessary cloud storage drives up your cloud bill as does data retrieval. For frequently accessed data, caching or temporarily holding key data, helps increase the speed of data retrieval. Reducing the amount of data retrieved from storage also reduces computing resources and speeds service delivery.

Securing cloud environments means proactively detecting possible threats and anomalies before they occur. If an enterprise is reacting to security issues after they occur, service interruptions and data breaches are more likely to occur.

Organizations that fail to properly secure data run the risk of exposing both enterprise and user data and experiencing compliance and regulatory issues. A strong DevSecOps practice places application and infrastructure security at the forefront throughout the entire application lifecycle. Through visibility, traceability and auditability, DevSecOps teams can monitor every aspect of a cloud environment. Cloud optimization helps put these capabilities in place.

Organizations can implement several strategies to optimize resource usage and services purchased from cloud providers. Cloud optimization strategies include:

Rightsizing is the process of aligning the type and size of cloud computing instances with workloads. Rightsizing can help improve cost efficiency by making sure an organization purchases the necessary cloud instances.

Rightsizing does not automatically mean downsizing resources. If cloud-based apps and services require increased computing resources, rightsizing helps ensure they are acquired from cloud vendors. Effective rightsizing requires the analysis of workflows, application performance requirements and an understanding of usage patterns to align instance type and volume.

Automation plays an important role in cloud optimization. With the increased use of hybrid and multicloud environments, it is impossible for IT teams to manually monitor and allocate the proper resources for each workload across disparate environments.

Auto scaling automates the provisioning and deprovisioning of cloud resources, including storage and virtual machine instances, to align resources and demand in real time. This helps achieve consistent application performance while reducing cloud costs.

Containerization packages software code with the operating system, configuration files, libraries and dependencies needed to run the code into a single “container,” enabling it to run on any platform or cloud. These containers are more efficient than virtual machines (VMs) and require less start-up time.

Many containers can run on the same computing capacity as a single virtual machine, which reduces cloud usage and cost. Orchestration platforms such as Kubernetes can help automate the deployment, management and scaling of containerized applications.

Reserved instances are long-term commitments to use specific services, typically ranging from one to three years. This commitment often comes with a favorable pricing model from cloud service providers and is ideal for consistent workflows.

Spot instances are last-minute resource purchases that are often offered at a reduced cost. These instance types are not available on demand and must occasionally be bid on. When purchased, they can be subject to service interruptions with limited notice. Spot instances are not consistently reliable and are often used for workloads that are not time-sensitive or critical to operations.

Data is often moved between clouds. Each transfer has an associated cost, and unnecessary transfers can cause an increase in cloud spend. Cloud management tools can automate the process of efficiently moving data between clouds and help keep this cost to a minimum.

Cloud-native applications are programs made up of reusable components known as microservices. A microservices architecture consists of small building blocks that control different aspects of an application’s function. Microservices are deployed and scaled independently of each other, making them flexible and useful for continuous integration (CI) and continuous delivery (CD) practices.

CI enables developers to automate the process of integrating new code throughout the development cycle. CD lets DevOps teams automate the various processes of software development, including testing and code deployment. These DevOps practices, along with infrastructure as code (IaC), a high-level descriptive coding language that automates the provisioning of IT infrastructure, facilitate the efficient development, testing and deployment of new applications. They also make the process of updating applications more efficient.

To make the most of cloud optimization efforts, many organizations choose to:

• Focus on visibility: Understanding what is happening within cloud environments is the first step to optimization. Solutions that offer reporting with context that is accessible across various teams help stakeholders make informed decisions.
  
  
• Sharpen performance analysis: Consistently monitoring applications by using clearly defined metrics set to evaluate operational needs is a key facet of optimization. Monitoring performance gives IT teams an understanding of what is working and what is not, and if applications are receiving necessary resources.
  
  
• Use application resource management tools: Manually allocating resources is a time-consuming process that often leads to overprovisioning. Application resource management tools offer visibility into cloud infrastructure, monitoring and reporting options, and automated tools to reallocate resources based on real-time demand.
  
  
• Break down silos: Business and DevOps teams should communicate and have dedicated information sharing processes. DevOps teams should be familiar with business needs and objectives, and business leaders should understand the DevOps process and the technical requirements that enable enhanced service delivery.