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6 reference architecture designs for automation projects

A successful automation architecture strategy hinges on accountability, governance, attention to security, and standards.
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Gold gears on a black background

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A successful automation strategy requires an enterprise-wide focus on adoption, from vision to execution, emphasizing simplicity and shared knowledge. The strategy includes:

For the past few years, Red Hat's Portfolio Architecture team has been developing reference architectures based on customers' real-world use cases in various industries. We have multiple criteria for developing and vetting an architecture collection before publishing it, which you can read in my intro article about Portfolio Architectures.

We're publishing these architectures for anyone's use on our Red Hat Portfolio Architecture Center and Portfolio Architecture Examples repository.

This article presents six architectures centered around automation. I provide a short overview of each and allow you to explore them in-depth on your own.

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Portfolio Architecture Automation Collection
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In each of these architectures' GitHub repository, you'll find a table of contents outlining the technologies used, several example schematic diagrams with explanations, and a link to open the diagrams directly into the online tooling in your browser.

[ For more insight, download the automation architect's handbook. ]

Cloud adoption

As enterprises adapt to public and private clouds, it is important to provide automation to manage and scale server deployments and to provide the capability to transition servers between datacenters and cloud providers. The cloud adoption architecture provides necessary flexibility and portability.

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Cloud adoption architecture
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This architecture accelerates cloud adoption with effective automation for deploying and managing workloads across multiple cloud infrastructures according to performance, security, compliance, and cost requirements.

Cloud factory

Instead of buying a cloud, large enterprises want a cloud factory, which enables them to deploy and manage the cloud in a modern and automated manner. This architecture covers automated deployments of multiple OpenStack and Ceph-based cloud instances, following Infrastructure-asode principles.

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Cloud Factory Architecture
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This architecture's use case is deploying multiple private clouds based on the same (infrastructure as) code using different parametrization.

Near-zero downtime maintenance for SAP

This architecture covers near-zero downtime maintenance for Red Hat Enterprise Linux (RHEL) servers hosting SAP workloads. SAP workloads are critical for companies, and the maintenance windows are very strict, sometimes making it difficult for systems administrators to finish update tasks properly in time.

This architecture allows the application of operating system patches, fixes, updates, database patches, new versions, and SAP kernel updates while users continue to work inside SAP, not perceiving any disruption.

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Near Zero Downtime for SAP
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The use case is minimizing the downtime of maintenance on SAP hosts so that users and processes can continue to work without perceiving any interruption.

[ Learn about using SAP on Red Hat OpenShift. ]

Remote server management

This architecture covers remote server management. As more and more enterprises deploy across different datacenters and public and private clouds, it is important to provide consistency and security in an automated way across all servers to reduce risk and costs.

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Remote Server Management Architecture
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This use case provides administration for a consistent server estate across hybrid cloud and datacenters with remote management, security, and data protection for the entire life cycle.

Self-healing infrastructure

This architecture focuses on providing a self-healing infrastructure. Modern application infrastructure increases in complexity as it becomes more powerful and easy to consume. Keeping that infrastructure safe and compliant is a challenge for many organizations. One of the most powerful approaches to infrastructure management today is combining historical data-driven insights and automation tools for applying remediation across a scaling estate of hosts in a targeted and prioritized manner.

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Self-Healing Infrastructure
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This use case is managing security, policy, and patches for a large number of servers in datacenters or public and private clouds.

Smart management for SAP

This architecture covers smart management for RHEL servers hosting SAP workloads. SAP landscapes are usually very complex, with many servers and lots of dependencies. In addition, SAP workloads are very performance-demanding, and new recommendations need to be applied whenever a new operating system release or workload is certified. Keeping servers in these landscapes aligned and current with the latest recommendations can be very challenging. On the other hand, preventing potential issues in these critical systems is of utmost importance. The following combination of powerful and robust tools helps keep SAP workloads healthy and operating smoothly and performantly:

  • Red Hat Insights and its SAP-specific rules detect potential problems
  • Red Hat Automation Platform remediates issues before they occur
  • Red Hat Satellite manages the servers' life cycle
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Smart Management for SAP
Click image for larger view (Eric Schabell, CC BY-SA 4.0)

The use case is managing security, policy, and patches for servers in the SAP ecosystem (on premises, public, private, and hybrid cloud), ensuring they are compliant with SAP and Red Hat's recommendations throughout their life cycle.

Learn more

These are six of the many reference architectures Red Hat's Portfolio Architects have published, and we'll continue to publish them as we complete them. If you are interested in more architecture solutions like these, feel free to export the Portfolio Architecture Examples repository.


This article originally appeared on Eric D. Schabell's blog and is republished with permission.

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Eric D. Schabell

Eric is the Director of Technical Marketing and Evangelism at Chronosphere where he leads the technical marketing and evangelist teams for the only observability platform that tames rampant data growth and cloud-native complexity. More about me

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