How to Optimize Cloud Computing Costs with Cloud Bursting

December 19, 2020

Organizations across all industries have appreciated and benefited from the significance that data plays in their decision making and business development. They are now running more data workloads and analytics than ever before.

Yet an overload of these activities may cause a system crash, workload freeze, and ultimately downtime. This happens mainly when an organization’s cloud computing resources such as its storage, memory, and CPU exceed the available system capacity.

Many organizations have resulted to cloud bursting to address this issue of system overload while saving on costs. With cloud bursting, organizations offload private cloud and on-premises traffic into the public cloud, which helps in meeting peak demand.

This article will discuss the challenges and benefits of cloud bursting and show you how to optimize costs and improve cloud burst platforms’ effectiveness.

What is cloud bursting?

Businesses usually experience peak and off-peak seasons. They need to expand their capacity during peak seasons to handle the high demand at the time. Cloud bursting comes to handle peak demands and meet the expanding capacity requirement when private cloud resources are overwhelmed. Cloud bursting deploys applications normally running on a private cloud into the public cloud dynamically.

Third-party providers offer computing services over the public internet, known as the public cloud. Public cloud computing services are either free or sold on-demand and thus readily available at low costs.

On the other hand, the private cloud refers to computing services offered on a private internal network or over the internet to only selected users rather than the general public. Private clouds provide benefits such as self-service, elasticity, and scalability.

Usually, you would need to overbuild physical infrastructure to increase your capacity and to meet fluctuating demand peaks. Luckily, cloud bursting eliminates the need for all this by ensuring that private clouds are affordable. It does this by rightsizing private clouds in terms of storage and computes to accommodate rising demands and ensuring that the public cloud handles the peaks through a pay-as-you-use subscription.

Benefits of cloud bursting

Capacity boosting

Cloud bursting ensures these operations go uninterrupted even in times of high demand. During peak periods, organizations can run at a higher capacity, sometimes nearing 100 percent on the private cloud.

This situation causes a strain on the systems and may result in slower speeds or a complete crash. Cloud bursting reduces the strain on your private cloud by redirecting traffic to your public cloud, thus ensuring that systems continue to work at the recommended rate and capacity.

When you need some extra space on your private cloud to, for example, run applications, you can always cloud burst to free up space. In this scenario, cloud bursting helps transfer data from your private cloud to the public cloud for a period.

Flexible scaling

Organizations with either a fluctuating customer base or up and coming startups wanting to scale their operations can rely on cloud bursting for rapid and convenient scaling. Cloud bursting offers an added convenience in that organizations do not need to predict demand usage manually. On top of that, organizations can cloud burst to free up local resources and use them for other purposes.

Business continuity

Cloud bursting prevents critical applications from crashing; otherwise, operations could come to a complete standstill. Application crash prevention is very beneficial to organizations. It ensures organizations maintain their functions during high demand times.

Challenges of cloud bursting

Managing configurations

Organizations that cloud burst run the same resource types, for example, they may have application servers in multiple clouds. But choosing multiple cloud providers may bring some challenges in terms of different resource offerings. For instance, it may require an organization to manage and configure its applications and technology stacks across two environments.

Differences may come in terms of cloud network configurations. Some cloud providers offer the concept of availability zones, while others do not. Still, some have security groups, others have Access Control Lists (ACLs) and Subnets, and others have both.

ACLs are used to filter network data. This is done by configuring ACLs on network devices with packet filtering capabilities, including firewalls and routers. Subnets promote the efficiency of networks. Subnetting ensures network traffic does not travel through unnecessary routers, thus reducing the distance the traffic travels to reach its intended destination.

We also have Hypervisors, their features, and the versions of hypervisors differ between cloud providers. A hypervisor allows a host computer to share processing, memory, and other resources to support multiple virtual machines.

Also, machine types and power vary from one cloud provider to another. Clouds also offer different storage types, including object, persistent, and block.

Such differences may bring a downstream effect. For instance, for an organization to use different storage subsystems and hypervisors, it may also have to use additional virtual machine images built for each cloud. Still, the organization has to maintain these base machine images with every security patch and operating system.

Complexity and latency

Effective cloud bursting requires a flexible and scalable network that can handle the workload changes between public cloud infrastructures and on-premises private clouds. The management and orchestration of the applications moving between the two cloud environments must be in synchronization. And this requires two identical clouds with matching platforms and templates and a lot of scripting.

Orchestration involves integrating two or more services or applications to allow real-time data synchronization and automation of processes.

To address the orchestration issue, you can host both the private and public clouds in the same data center for consistent configuration, testing, and management. Besides, you can use containers to create a consistent development environment across these cloud platforms. The latency connectivity between clouds must be low for containers to work effectively.

You can also address the latency problem through a hybrid cloud colocation solution where you rent networking equipment, space, and bandwidth. This requires the two cloud models to have a direct, low-latency interconnection infrastructure.

This direct interconnection is essential to support automated management and provide virtualized connections in multiple cloud networks and services. It also mitigates complexity and latency issues related to cloud bursting.

How to save on cloud computing costs with cloud bursting

Big data analysts and software developers are intense consumers of cloud computing services. Software developers need to test code and applications, especially at the end of the software development cycle.

It requires organizations to spin up multiple virtual machines to meet the increased demand for computing services. Spinning-up involves booting up a virtual machine on a computer, therefore saving you money and the need to manage virtual machines manually.

However, these services are usually only needed for a short period, mainly during the development process’s testing stage. While investing in the virtual machines and infrastructure is necessary to run these tests, you must also consider your investment return.

The use of cloud bursting offers on-demand computing resources, so you do not need to invest in this infrastructure. This is a pay-as-you-use arrangement that will help you save on your cloud computing costs.

The availability of social media data and the spread of IoT devices has empowered organizations to collect and analyze more data about markets, products, consumer behavior, and much more. Organizations are using these insights from data analytics to formulate more effective business strategies and better business decisions.

The analysis of data requires the deployment of computationally intensive algorithms. These algorithms perform data sequencing, risk analysis, and other heavy workloads that can drain the resources available in your private cloud.

If this happens, all the functions and processes may come to a near standstill. Cloud bursting ensures that analytics workloads overflow into your public cloud, thus reserving computing resources in the private cloud for applications essential and business processes.


Organizations with their most critical applications hosted in the private cloud or on-premises find cloud bursting a cost-effective solution to their cloud computing needs. If we address configuration and latency issues, cloud burst platforms’ usage can improve performance across all applications.

Peer Review Contributions by: Lalithnarayan C

About the author

Eric Kahuha

Eric is a data scientist interested in using scientific methods, algorithms, and processes to extract insights from both structural and unstructured data. Enjoys converting raw data into meaningful information and contributing to data science topical issues.

This article was contributed by a student member of Section's Engineering Education Program. Please report any errors or innaccuracies to