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    Top 9 Docker Use Cases

    Top 9 Docker Use Cases

    The evolution of containers shifted the dynamics of application deployment. Docker played a huge role in that shift.

    It offers ease of creating, deploying, and running applications through containerization. With Docker, developers can easily package the whole application and deploy it through a container.

    We will be looking at some of the top use cases of Docker through real-life examples in this blog. It will help us understand how Docker can help you in your business.

    Top 9 Docker Use Cases

    VR Group-Finnish Railways

    VR Group is a government-owned railway company. It is responsible for all the railway operations in Finland. It is headquartered in Helsinki.

    The key problem faced by the VR group was the high operational costs because of maintaining different applications.

    To solve this problem, VR approached Accenture to develop a common application platform on Docker.

    They migrated some of the existing applications. And they rewrote the rest and migrated the entire data to the newly created containerized platform.

    This migration to Docker helped the VR group to reduce the operational costs by 50%. It also enabled the organization to improve its overall quality.

    It also helped reduce the overall time required for application development and deployment.


    Visa Inc. is a renowned financial services company. It is headquartered in Foster City, California. It provides a platform through which users can digitally transact the money.

    Visa was facing virtualization utilization difficulties.  Their private cloud was only operating at a meager 15% of efficiency. This used to cause frequent downtimes and hampered productivity.

    Visa approached Mirantis for a solution and decided to use Docker Enterprise.

    The key solution was creating two applications for payment processing on the Docker platform. This allowed seamless transactions and reduced downtimes significantly.

    In tangible terms, Visa improved the scalability ten times. And it handled the huge daily transaction without any difficulties. This has also allowed the company to maintain security while improving the user experience.


    Kadaster is a government-owned Dutch Land Registry and Mapping Agency. It collects the data and information for all the properties and the rights in the Netherlands.

    It was using the Platform-as-a-Service earlier (PaaS) on their private cloud network.

    And that limited their operational scope. The organization wanted to opt for a modern solution that could provide flexibility and ease of adoption to the emerging technologies.

    To achieve this objective, Kadaster approached Capgemini for a solution.

    They decided on using Docker Enterprise to fulfill the objectives. It allowed the developers to integrate their own applications in a containerized manner.

    In tangible terms, the collaboration helped the organization to accelerate the application deployment time by 500 times. It has also allowed the organization to handle 50000 requests per minute at their peak and more than 8 billion requests in a year.

    Cornell University

    Cornell University is a reputed private university in the United States. It is based in New York, and it is a part of the illustrious Ivy League.

    It wanted to move its applications to the cloud, but it was facing issues due to application diversity and infrastructure issues.

    It approached Mirantis to solve this problem. It had almost 14 different infrastructures, and it was getting difficult to manage all that.

    And hence they decided to deploy a unified application that manages all the infrastructure.

    They decided to adopt the Docker Enterprise version for the application unification. This allowed the university to easily integrate and manage all the different networks.

    In tangible terms, this association helped the university to run 200 different nodes through Docker and achieve 13 times faster application development and deployment speed. It has also simplified the complicated process.

    BBC News

    BBC News is British Broadcasting Corporation's (BBC) business division that provides news and information on the current affairs. It is a renowned organization across the globe. It is headquartered in London.

    The corporation was facing the waiting time of around 30 minutes in the news schedule.

    They wanted to eliminate the waiting time and use a real-time news schedule. BBC broadcasts in around 30 languages, and the waiting time was causing many issues.

    To solve this problem, the BBC approached Cabot, and they suggested to go for Docker.

    This approach resulted in not only the elimination of waiting time but also the consolidation of the applications and improving the user experience.

    In tangible terms, it allowed the corporation to run 26,000 jobs by 500 developers in parallel without causing any delays or waiting periods.

    Also Read: What's the Difference Between CaaS and IaaS?


    Automatic Data Processing (ADP) Inc. is a company that provides human resource management software and services. It is headquartered in Roseland, New Jersey, US.

    ADP wanted to transform and modernize all its applications across the world. They wanted this to happen without having any security issues. It has around 40 million users across the globe. And hence the emphasis on security.

    ADP approached Mirantis for a solution and was advised to use Docker Enterprise.

    It helped to build and agile unified platform that created an automated and secure process to speed up the application development process.

    This collaboration helped the company to revolutionize its services. That included the modernized existing services and offering exciting new services.

    Baker Hughes

    Baker Hughes is an energy & utilities company. It is headquartered in Houston, Texas. It is owned by General Electric.

    They were using a monolithic infrastructure that was not modern enough to sustain with the dynamically changing requirements. It hampered the deployment times, and the analytics team was handicapped.

    In order to resolve this issue, the company decided to go for Docker Enterprise.

    The key solution offered was to containerize the analytics software. This allowed easier data distribution across the world.

    This collaboration helped the Baker Hughes analytics team to cut the dependency on the existing infrastructure.

    In tangible terms, it allowed the company to reduce the deployment time from six months to a mere one hour.


    Shopify is a Canadian e-commerce company that operates around the world. It provides an online store for small business owners. It is headquartered in Ottawa, Canada.

    Shopify wanted to scale and improve the availability and chose to go for Docker Enterprise.

    The key solution offered was to containerize the application deployment and optimize the time required for the deployment.

    This collaboration helped the Shopify to build and power over 100 million shops. In tangible terms, it allowed the company to scale the business operations and increase its availability.


    Splunk is an American company that specializes in big data, monitoring, and analyzing software. They wanted to increase their data center capabilities to put up with the ever-growing demands.

    They approached Mirantis to solve this issue. They also wanted to implement a DevOps solution that could support both Windows and Linux.

    They were advised to implement Docker Enterprise and automate the testing capabilities with Jenkins.

    This association helped Splunk massively. They could deploy the applications in minutes instead of days by containerizing the applications.

    In tangible terms, it has helped the company to improve the average CPU utilization rate to 75% and support 2000 applications in parallel.

    Key Takeaways

    We can see from the above examples that Docker can be used for reducing the time required for the deployment and increasing the security of the platform as well.

    It can also be used to improve scalability, reduce operational costs, and reduce the response times.

    Also Read: Qubole vs. Databricks: Top 7 Differentiating Factors

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