6 considerations for choosing a modern application platform

The right application platform gives IT teams the flexibility to modernize existing applications, build new cloud-native applications, and scale delivery across hybrid cloud environments. IT teams can speed up deep-learning (DL) model training and performance by pairing Red Hat® OpenShift® with Intel® Gaudi® AI accelerators and Intel® Xeon® 6 processors.

Application transformation starts with an integrated, Kubernetes-powered platform that includes a security-focused Linux® container host operating system (OS).

• To simplify management: Choose a platform that provides orchestration and cluster services such as automated installation, over-the-air updates, monitoring, and logging.
• For developer efficiency: Look for cloud-native application and data services, security and management controls, broad integration capabilities, and self-service interfaces.

Using common security tools and processes across the open hybrid cloud environment helps teams adopt DevSecOps practices. To protect infrastructure, applications, and data privacy: 

• Choose a platform with protections like access controls, network security, and an enterprise registry with a built-in scanner. 

Deliver security-focused applications rapidly with a platform that provides: 

• Continuous integration and continuous delivery (CI/CD) pipelines.
• Integrated development environments (IDEs).
• Support for programming languages and runtimes.
• Data- streaming capabilities.

In a Red Hat survey conducted by Illuminas, “76% of respondents used generative artificial intelligence (AI), often for documentation, code generation, and intelligent code suggestions.”¹ Red Hat OpenShift provides the flexibility to run AI applications alongside non-AI workloads. Red Hat OpenShift is the foundation for Red Hat AI. The portfolio of AI products included with Red Hat AI can be used to build and deploy AI powered models and applications. 

1. Pair Red Hat OpenShift AI with Intel Gaudi AI accelerators to speed DL model training and AI computations while also increasing energy efficiency. 
2. For AI inference, retrieval-augmented generation, and agentic AI, Intel® Xeon® 6 processors running small to midsize models can provide a cost-effective alternative.

Lower management time and costs with a platform that offers a unified management interface, automated development and deployment pipelines, and certified integrations for managing third-party applications and services.

• User-friendly management tools and automation help to increase consistency, compliance, and IT efficiency.

To use preferred IT components—and switch them when needed—look for an application platform that integrates with a broad ecosystem of trusted third-party technologies, products, and services. 

• Look for a vendor that offers expert support, consulting, and training  to help your organization’s IT teams build the skills needed to get started experiencing efficient operations and innovation.