Contain it: The least intrusive way to modernize applications

As organizations invest more in the cloud and AI, there's a growing need for high-performing applications on flexible, modern development platforms.

These new platforms need to support existing applications and allow developers to create new ones quickly. For those looking to modernize applications but unsure where to start, containerization can be an excellent place to begin. Containerization enables faster application development and deployment, with fewer resources and lower costs.

Plus, containerization provides a flexible way to consistently package and deploy AI across application development, testing, and production. This consistency removes the guesswork and friction often associated with AI projects, giving your teams more time to refine AI-enabled applications, explore new insights, and drive impact.

Here's why you should consider using this approach and how to pick suitable applications for containerization.

Why containerization is crucial for modernizing your stack

Containerization is considered the least intrusive method of modernization because it doesn't require significant changes to application code. It is also straightforward to operate, resulting in cost savings and improved availability.

The importance of containerization lies in its ability to provide a flexible and efficient way to modernize applications. It allows you to package your applications and dependencies into a containerized unit. This container can then be easily moved from one environment to another, making it an excellent solution for modernizing applications.

As organizations adopt agentic AI, containerization helps standardize environments, modularize components, and scale workloads, making complex agent-based systems easier to deploy and manage. Diverse teams can experiment rapidly, share solutions effortlessly, and roll out improvements faster.

Here are a few key reasons why containerization is crucial for companies looking to modernize their technology stack, especially when AI is a priority:

• Agility: Containerization allows companies to quickly adapt and respond to changing business needs. By enabling minimal changes to AI models and application code, containers ease the deployment and updating of AI solutions.
• Reliability: AI workloads depend on consistency. Containerization ensures applications perform reliably across different environments, improving user availability.
• Portability: Containers provide a consistent environment for an application to run in, regardless of the underlying infrastructure. This makes it easier to move applications from one environment to another, such as from a local development machine to a production environment. AI projects thrive on this flexibility.
• Scalability: AI workloads often fluctuate, from training complex models to handling unpredictable inference demands. Containers can be scaled up or down to meet changing demands, handle sudden traffic spikes, and accommodate new users.
• Security: Containers provide an isolated environment for applications, making it more difficult for malicious actors to exploit vulnerabilities in the underlying infrastructure. They also help protect sensitive data and AI intellectual property.
• Cost-effectiveness: AI projects can be resource-intensive. By using containers, companies can reduce infrastructure costs and avoid vendor lock-in. Containers can also make it easier to manage resources, as they allow you to allocate resources more efficiently to different applications.

Five factors to consider when evaluating applications for containerization

Identifying suitable applications for containerization requires a thorough assessment of their architecture and dependencies. When AI enters the picture, these factors become even more pivotal. Here are some factors to consider when assessing applications for containerization:

• Statelessness: Applications that are stateless, meaning they don’t save client data from one session to the next, and that don’t rely on local storage are typically good candidates for containerization, as they can be easily moved between containers and environments.
• Dependencies: Applications with well-defined dependencies that can run with limited resources are ideal for containerization. Applications that require significant resources or have complex dependencies may be more challenging to containerize.
• Scalability: Applications that are expected to scale up or down frequently are good candidates for containerization, as containers can be easily scaled to meet changing demands.
• Portability: Applications that need to run in different environments, such as those moved from a local development machine to a production environment, are good candidates for containerization.
• Security: Applications that require a high level of security, such as those that handle sensitive data, are good candidates for containerization, as containers provide an isolated environment for applications to run in.

Include containerization in your application modernization plan

Containerization provides a flexible, scalable, and cost-effective approach for modernizing applications. By adding it to your application modernization plan, your organization gains:

• Minimal intrusion into existing applications, with minimal changes required to application code
• Easy identification of suitable applications
• Improved scalability, reliability, and availability
• Cost savings through improved resource utilization

Explore how Unisys can help you add containerization and other low-risk, low-effort approaches to your application modernization journey to advance your AI strategy.

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