Today’s automotive manufacturers must deploy and manage applications at scale. Plus, they need to scale out new services and applications for edge computing. But the question remains: How do you do this while ensuring fast development and deployment of both internal and customer-facing innovations—and high availability of critical applications?
The go-to solutions for achieving application portability and ease of management across clouds and datacenters are microservices, containers, and Kubernetes—the leading container orchestration framework. As a leading contributor to Kubernetes since the project switched to open source, Red Hat provides one of the most widely used Kubernetes application solutions. Red Hat was also named a leader in the Forrester Wave report among eight cloud container platform vendors2. According to Forrester, "OpenShift® is the most widely deployed multicloud container platform and boasts powerful development and unified operations experiences across many public and on-premises platforms.”
The open, comprehensive, and security-focused enterprise Red Hat® OpenShift® Container Platform offers a single platform capable of building, running, and managing Kubernetes-based workloads at scale across clouds and on-premise. It frees applications from infrastructure, enabling them to work independently and run anywhere Red Hat Enterprise Linux® is supported, including the network edge.
Build on Kubernetes with trust
Red Hat OpenShift defines a defense in depth approach to container security. It focuses on security at every level of the container stack and throughout the application life cycle. This feature includes managing security for the entire software supply chain, which involves controlling content sources and then defending against attacks in all layers of the platform. Red Hat has also created application programming interfaces (APIs) that allow security providers to augment the existing security services. This increased security prevents attackers from accessing communications to edge devices—whether those are self-driving cars, programmable logic controllers (PLCs), or other machine controllers on the factory floor.
Build, deploy, and monitor applications with ease
With built-in logging and monitoring, Red Hat OpenShift gives operations teams visibility into deployments no matter where they are—across teams. It uses Prometheus and Grafana, which are both open source. Red Hat OpenShift Operators for Kubernetes also embed the unique application logic that enables services to function reliably—not just configured but tuned for performance. Applications can also be updated and patched from the OS with one touch.
This open platform further allows dev teams to use the tooling they prefer—including Jenkins, Java, and Python. These tools help developers speed applicaton innovation, and with containers they can package an application with all the parts it needs—such as runtimes and libraries—and ship it as one product. When the time comes to launch, Red Hat OpenShift simplifies deployment by ensuring each of the individual applications can talk to each other, leaving developers free to focus on coding.
All this helps teams quickly deliver new applications and migrate existing apps to the cloud for more agility. This increased agility helps automakers propel the innovation cycle—whether it is rapidly building and deploying new applications or improving the customer experience (CX).
Speed innovation with AI/machine learning
Red Hat cloud technologies help automakers apply the power of AI and machine learning—from automating the factory edge to increasing the safety of autonomous vehicles. For example, AI can power applications that span the automotive manufacturing floor. Automakers can also use AI-driven systems to create schedules and manage workflows. Or they could improve the safety of robots working alongside humans on factory floors and assembly lines.
In autonomous and connected vehicles, AI and machine learning enable OEMs and suppliers to continuously improve the quality of a vehicle by upgrading high-level software as well as low-level code on the electronic control units (ECUs). Additionally, cloud application developers must choose from among an overwhelming variety of languages, application frameworks, tools, and test frameworks. Fortunately, Red Hat OpenShift is designed to support machine learning workloads, which can offload some of those decisions to a computer brain. For example, the computer could do much of the mundane work, identify patterns and drawbacks learned by examining millions of lines of other peoples’ code, and then provide advice to developers on their own code. Red Hat Decision Manager adds the ability to intertwine machine learning models with conventional decision models.
This capability is helping organizations across the automotive industry accelerate business and mission-critical initiatives by developing intelligent applications in hybrid cloud.
Learn more about Red Hat technologies for automotive and see how we can help you build a modern hybrid or multicloud infrastructure to increase innovation and manufacturing efficiency.