Red Hat, Inc., the world’s leading provider of open source solutions, has announced the addition of automated policy as code, a new feature that will be integrated into future versions of Red Hat Ansible Automation Platform. This tool is designed to help enforce policies and ensure compliance in hybrid cloud environments, which are increasingly incorporating a greater number and variety of artificial intelligence (AI) applications. As part of the evolution of automation, policy as code will allow organizations to adhere to changing internal or external requirements, better preparing for infrastructure expansion and supporting the scalability of AI workloads.
According to IDC forecasts, “Despite the challenges posed by skills gaps and human resource shortages, IT operations face constant pressure to improve efficiency and reduce costs. Meeting the demands of continuous innovation and business unit time-to-market objectives, while adapting to the agile and dynamic needs of DevOps and security teams, while ensuring resilience and reliability of IT services, poses an extraordinary challenge for traditional IT operations teams.”
Red Hat believes that this challenge can grow exponentially as AI expands the capabilities of individual systems, surpassing what humans can manage on their own. Implementing essential policies in such broad workloads not only requires a lot of time and attention, but also the collaboration and documentation of multifunctional teams. Manual processes leave room for human error, and any mistake can be costly. Applying compliance directives to mission-critical systems before focusing on AI is vital, as these systems are often the most affected by compliance requirements that determine system security, performance, and auditability.
Establishing a foundation of consolidated automation with operational controls allows organizations to prepare a more robust security environment for AI innovation. Policy automation as code will help customers better position themselves to operate information technology in accordance with specific governance, risk, and compliance (GRC) requirements. It will help align technical environments and resources with agreed standards at any time -before automation runs or in real-time when components deviate from policy- and repeat it wherever applicable, extending control at scale across the hybrid cloud and keeping the potential expansion of AI within predetermined limits.
Red Hat is facilitating the creation and management throughout the workload life cycle before and after AI, at scale across global operations, and through automated audit reports that help free up technology teams. Policy automation as code will create the necessary consistency of control for IT teams to confidently invest in new technology by providing a layer of protection integrated into operations. With these programmatic controls, there are more guarantees that AI is based on what is already approved by the organization to deliver real business value.
Ansible Automation Platform is the industry-leading comprehensive automation platform. It offers a steady stream of innovation to empower IT teams with new functionalities like Red Hat Ansible Lightspeed to bridge the skills gap and Event-Driven Ansible to have an always-on tool.
If teams use an AI service, such as Red Hat Ansible Lightspeed, to accelerate automation development, policy as code capabilities could be applied when creating automation content and governance could be infused into the learning model from the start. This will allow content creators to write code that automatically maintains mandatory compliance requirements, greatly reducing the impact of skills gaps and human errors in IT operations.
The tech preview of automated policy as code for Ansible Automation Platform is expected in the coming months. Customers and partners can participate in advisory groups where they can share their feedback and learn best practices. Partners can also discuss integration, so that recommended best practices can be automatically applied and/or included in service offerings.
For over 30 years, open source technologies have merged innovation speed with significant reductions in IT costs and barriers to innovation. Red Hat has been leading this trend for almost the same amount of time, from delivering open enterprise Linux platforms with RHEL in the early 2000s to driving containers and Kubernetes as the foundation of open hybrid cloud and cloud-native computing with Red Hat OpenShift.
This momentum continues with Red Hat empowering AI/ML strategies through open hybrid cloud, enabling AI workloads to run where the data is, whether in the data center, multiple public clouds, or at the edge. Beyond workloads, Red Hat’s vision for AI takes training and model tuning down this same path to better address constraints around data sovereignty, compliance, and operational integrity. The consistency provided by Red Hat platforms in these environments, regardless of where they run, is crucial to maintaining the flow of innovation in AI.