Why choose Red Hat Ansible Automation Platform as your AI foundation?

Enterprises are under pressure to capitalize on artificial intelligence (AI), but adopting and maintaining AI tools presents a number of infrastructure challenges. Businesses require greater computing power, network bandwidth, and storage capacity to ensure uptime for AI workloads and meet the growing demand for custom model training. The data processed by AI applications is often sensitive, making data security, compliance, and privacy just as crucial. 

This added complexity must be managed efficiently to control costs and enhance developer productivity, so AI can accelerate your progress—rather than slow you down.

Organizations looking to position themselves for AI-enabled opportunities and transformation must establish a strong infrastructure foundation, which—at an enterprise scale—can only be achieved with IT automation. Automation helps companies balance the complexity of building, scaling, and maintaining existing IT systems—and the new infrastructure needed for AI.
 

Watch the webinar 

Both automation and AI help businesses increase the speed and efficiency of operations, while reducing manual tasks. However, there are distinct differences:

• Automation performs tasks the same way every time, based on predefined, human-written rules. It follows set instructions—it doesn’t learn from experiences. However, humans can write their knowledge into these codified rules, so that complex processes can be completed without error, in a fraction of the time it would take to do so manually. Automation platforms serve as a framework for different parts of IT infrastructure to communicate quickly and securely between each other. This includes communication via Secure Shell (SSH) protocol, application programming interfaces (APIs), and other mechanisms—and the ability to use credentials and execute the automation provided.
• AI performs tasks based on learned behavior or experience, which is built on observed patterns and past outcomes. AI mimics humans at a more intellectual level, and can learn from data, improve over time, and make decisions based on its experience. In its ideal implementation, AI learns from experiences and adapts to new situations. AI relies on existing automation tools, frameworks, and plugins to communicate to disparate IT systems. Often, AI tools require an AI agent to interact with environments and infrastructure outside the model and its runtime environment.

AI’s potential to make informed decisions and replicate human intelligence makes AI tools incredibly attractive for businesses hoping to improve the speed of complex decision making. But the potential gains offered by even the most developed and complex AI tool depend entirely on how it’s used—and in the distributed IT environments of modern enterprises, adopting AI is far from straightforward. Pairing your AI solution with an automation foundation can help you accelerate progress toward your long-term goals.

When looking to adopt or scale enterprise AI, organizations should prepare to meet the technical and strategic demands needed to maximize the benefits of AI.

Ensure the uptime and availability of infrastructure 

For an AI tool to make effective real-time decisions, it relies on a constant flow of data from whatever source it’s monitoring. As a result, uptime is crucial. Whether delivering accurate patient data in hospitals or shutting down malfunctioning equipment to prevent costly mishaps in factories, AI-driven business operations depend on resilient infrastructure that can guarantee uptime and availability. If the infrastructure falters and the data is disrupted, the AI model’s lapse can negatively impact operations, undermine customer experiences, and cause considerable financial losses. To maintain consistent uptime, the flow and storage of data must be configured appropriately from the data center to edge locations.

Establish practices to help teams manage and scale workloads 

Because AI models depend on IT infrastructure that’s consistently reliable and available, organizations need to assess their datacenters to determine if they have adequate resources. You might need to upgrade your infrastructure to provide additional power and cooling, as well as expand server, storage, and network capacity to meet the elevated demands on uptime and availability for AI workloads. But even with the right resources in place, many organizations struggle to manage these processes effectively. With automation, you can efficiently manage your workflows to ensure that infrastructure tasks are executed with speed and consistency, with less room for human error.

For organizations able to harness AI as a competitive differentiator, success won’t be due to having the biggest data model, or excessive expenditure into GPUs. They’ll succeed by operating automated, resilient infrastructure that can seamlessly scale AI workloads, while at the same time integrating with AI tools to become more intelligent. Simply put, if you’re not automating—and maturing your automation journey—it will take you longer to incorporate and benefit from AI.

Red Hat® Ansible® Automation Platform establishes a solid foundation for AI implementations by simplifying the deployment, management, configuration, and lifecycle of AI models and infrastructure components. Ansible Automation Platform can help you:

Standardize deployment. Ansible Playbooks offer a consistent and repeatable method for deploying AI components like operating systems, servers, storage, models, containers, and data and networking resources. By codifying the infrastructure as code, Ansible Automation Platform promotes uniformity and reliability across all AI environments, reducing the likelihood of configuration errors or discrepancies. You can also use a standardized deployment as a blueprint for your business continuity and disaster recovery (BCDR) plans and operations.

Integrate monitoring and alerts. Ansible Automation Platform integrates seamlessly with monitoring and alerting tools, allowing IT operations teams to automate the setup of monitoring agents, thresholds, and alerting rules for AI infrastructure components. By continuously tracking performance metrics and system health, Ansible Automation Platform helps you proactively identify and address potential issues, preventing disruptions to AI operations.

Manage data. One of the most difficult tasks for training AI models is getting data from where it’s created to a location where it can be trained. Ansible Automation Platform helps move data from servers to storage in region—to enhance data security—and also makes sure the data is accessible to the correct users for training the models using Red Hat OpenShift® AI.

Ansible Automation Platform serves as the automation glue needed to manage hybrid IT environments.

Learn how it can unify your people and processes 

Automating these use cases can lead to standardized, codified, and intelligent Day 2 operations. 

Orchestrate

It’s likely that many of the existing tools in your tech stack have built-in predictive AI features, but it’s up to you to use these capabilities efficiently to maximize their benefits. Ansible Automation Platform can help you put AI to use immediately by orchestrating AI capabilities with all of your systems and tools into larger workflows—so that you can consistently perform complex IT processes that span your entire infrastructure. With Ansible Automation Platform, you can:

• Streamline configuration: Automate the configuration of storage, servers, edge devices, network switches, GPUs, data, and activation of AI features across your tech stack—using a single YAML-based language.
• Increase service availability: Proactively identify and resolve IT issues before they affect your customers. Use the AI capabilities in your tech stack to determine root cause analysis (RCA) to automate troubleshooting and prevent future incidents.
• Automate remediation: Use AI features built into your existing tools as event sources to trigger automation workflows and orchestrate IT infrastructure with Event-Driven Ansible. 

Deliver AIOps

With Ansible Automation Platform, you can incorporate generative AI and Event-Driven Ansible directly into automation workflows. By integrating disparate AI solutions into unified workflows, your ITOps teams can start building fully self-healing infrastructure.

• Support ticket enrichment: Use Red Hat Insights or other third-party observability solutions to coordinate unknown events from Event-Driven Ansible and provide context for IT infrastructure engineers. If Event-Driven Ansible processes an event and you don’t know what to do with it, you can integrate with an AI solution, such as Red Hat Enterprise Linux® AI  or Red Hat OpenShift AI, to determine what the error means—so that you can speed up your mean time to resolution (MTTR) by not only automatically opening issues, but also immediately providing context so that engineers can start troubleshooting.
• Accelerate automation creation: Use Red Hat Ansible Lightspeed with IBM watsonx Code Assistant and other industry-leading gen AI solutions to quickly create automation with the guardrails and security standards built into Ansible Automation Platform. Ansible Lightspeed lowers the barrier to creating automation by offering code recommendations, and provides sources to explain how it produces each piece of automation.
• Build self-healing infrastructure: Use Red Hat AI solutions with Event-Driven Ansible to fully realize self-healing infrastructure end to end. Red Hat’s AI solutions can help you determine the error and then create the automation to fix the error. You can now put this information into a full-cycle loop to fully realize self-healing infrastructure. 

Optimize

With Ansible Automation Platform, you can optimize your IT infrastructure to enhance AI workload performance while at the same time using AI to improve your stack. You can use Ansible Automation Platform to set up and configure AI services, install and manage different models, configure GPUs, and coordinate different parts of your infrastructure.

• Deploy and configure AI: Automate the deployment and configuration of AI workloads to ensure an ongoing steady state.
• Coordinate Red Hat AI infrastructure: Connect and configure all components of AI platforms for seamless operation in a production environment.
• Onboard edge data: Streamline the onboarding of new edge deployments, such as Internet of Things (IoT) devices, to collect and sync their data with AI solutions. Coordinate the setup and distribution of data ingestion for AI training and inferencing models.

Red Hat can help you accelerate enterprise AI adoption with small, purpose-built models, efficient customization techniques, and the flexibility to develop and deploy anywhere. IT automation is critical for taking full advantage of AI capabilities in your organization. Whether automation is helping to improve your IT infrastructure by increasing resiliency and uptime, coordinating your existing IT solutions to take advantage of new AI capabilities, or even helping your IT infrastructure engineers directly by enabling AIOps, automation is the foundational layer that can help you realize AI in the modern enterprise.

Red Hat Ansible Automation Platform is an end-to-end automation platform that comes with all the tools you need to create, manage, and scale automation across the enterprise. It reduces operational complexity and provides a consistent user experience across teams, breaking down barriers between architects, developers, and system administrators. An Ansible Automation Platform subscription includes an event-driven solution, an expanding suite of development tools, and access to Ansible Content Collections that contain modules, playbooks, and documentation to help your cross-functional teams start automating fast.

Learn more about Ansible Automation Platform