Aligning system management, automation, and application lifecycle with your edge strategy

In part 1 of this two-part blog series, we introduced the decision framework for Red Hat Device Edge, when it makes sense compared to Red Hat Enterprise Linux (RHEL) or Red Hat OpenShift, and the unique role of MicroShift in enabling Kubernetes at the edge.

In this article, you’ll learn how to manage the system that you’ve chosen for your edge strategy. Once you’ve selected Red Hat Device Edge, the next step is designing a management approach that matches your deployment model, team expertise, and operational requirements.

We’ll explore:

  • The trade-offs between package-based and image-based Red Hat Device Edge deployments.
  • How Red Hat Satellite, Red Hat Ansible Automation Platform, and Red Hat Advanced Cluster Management for Kubernetes fit into the picture.
  • The future of large-scale image-based management with Red Hat Edge Manager.
  • Application lifecycle management options for MicroShift in both package-based and image-based environments.

By the end of this article, you’ll have a clear understanding of the management strategies available for Red Hat Device Edge and how to align them with your edge computing goals.

Managing Red Hat Device Edge: Red Hat tools and strategies

Red Hat Device Edge is built with RHEL, allowing you to confidently take advantage of familiar management tools. The primary differentiator is MicroShift support, which introduces additional considerations for container orchestration alongside traditional system management.

Red Hat provides several products for scale management, but the optimal selection depends on your deployment approach, particularly whether you choose package-based or image-based RHEL deployments (both are supported with Red Hat Device Edge).

The choice between using package-based or image-based (bootc) RHEL is a topic of its own and falls outside the scope of this article.In short, the choice depends on the trade-off between the consistency and ease of deployment and distribution of image-based RHEL and the flexibility and granular control of package-based systems. Other factors include selective security patching without rebuilding full images, immutable versus mutable infrastructure, CI/CD or GitOps workflow integration, update size and frequency, compliance requirements for traceability and change approvals, and organizational maturity in managing content, rollbacks, and customizations.

Package-based Red Hat Device Edge system management: The traditional approach

Core management with Red Hat Satellite

Traditional package-based deployments maintain full compatibility with established RHEL management patterns. Organizations can continue using Red Hat Satellite for:

  • Repository management
  • Content distribution
  • Patch management and security updates
  • Configuration management
  • Compliance reporting
  • System provisioning and lifecycle management

Automation with Red Hat Ansible Automation Platform

Complement Red Hat Satellite with Ansible Automation Platform to automate:

  • Configuration management
  • Event-driven automation triggers
  • GitOps workflows

Pro tip: Red Hat Device Edge subscriptions include Satellite entitlements, and specific bundled options include Ansible Automation Platform subscriptions for simplified procurement.

MicroShift application management

If you decide to deploy MicroShift on package-based Red Hat Device Edge, you'll need to choose your application management strategy:

Option 1: Red Hat Advanced Cluster Management for Kubernetes is ideal for organizations with existing Red Hat OpenShift expertise, as it maintains consistency with multi-cluster OpenShift deployments and takes advantage of familiar Kubernetes APIs that teams already understand.

Option 2: Alternative automation approaches work better for organizations with limited Kubernetes exposure. This includes solutions like GitOps (optional component in MicroShift), Ansible Automation Platform, or custom implementations using scripts and Helm charts, providing more flexibility for teams who prefer to avoid the additional complexity and learning curve associated with OpenShift-specific tooling.

Note: When using Red Hat Advanced Cluster Management with Red Hat Device Edge, unlike with OpenShift nodes, Red Hat Advanced Cluster Management cannot manage the underlying Red Hat Device Edge OS (configuration, upgrades, or applications outside MicroShift). Red Hat Advanced Cluster Management is limited to managing applications within MicroShift only.

Image-based Red Hat Device Edge system management: The modern approach

Lifecycle automation with Ansible Automation Platform

For image-based RHEL deployments, Ansible Automation Platform can automate the entire lifecycle:

  • Device configuration management
  • Application deployment
  • RHEL image creation for image-based deployment

Although Ansible Automation Platform is a good option, a new solution for edge computing, Red Hat Edge Manager, will be available soon.

The future: Edge Manager

A revolutionary new service called Red Hat Edge Manager, based on the upstream flightctl project, is specifically designed for managing systems running RHEL in image mode.

Edge Manager is designed to manage edge devices at scale, going beyond traditional automation frameworks by offering built-in state awareness to track system conditions without repeatedly running workflows. This approach supports smarter decisions, reduces redundant operations, and comes with ready-made workflows for Red Hat platforms to simplify and speed up implementation. It provides basic monitoring for operational visibility and uses a pull-based architecture that allows edge devices to initiate communication, reducing firewall complexity and improving security through mutual TLS and resilient agent design. 

When using image-mode RHEL, changes typically require creating a new image. With Edge Manager, configurations and applications can be managed separately through a GitOps model if needed, increasing flexibility, simplifying deployments, and allowing more granular control over updates.

MicroShift application management

When deploying  Red Hat's build of MicroShift in your image-based Red Hat Device Edge environment, you have 3 distinct approaches for application lifecycle management. In addition to using Red Hat Advanced Cluster Management or automation tools like Ansible Automation Platform, a third option is to embed applications directly within the system image.

This approach allows you to bind your application lifecycle with your device OS lifecycle by including MicroShift applications directly in the image. While this strategy delivers exceptional consistency across all devices without requiring external management tooling, it creates a tight coupling between configuration changes and image creation. Every application update, configuration change, or upgrade necessitates building and deploying a new device image, a trade-off that may not suit all operational scenarios but can be ideal for environments prioritizing simplicity and absolute consistency over deployment flexibility.

Conclusion: The right tool for the right job

Red Hat Device Edge is more than a lightweight subscription model; it’s a platform designed for flexibility in how you deploy and manage at scale. Whether you continue with package-based management using Red Hat Satellite or Ansible Automation Platform, or adopt the image-based approach with Edge Manager, Red Hat Device Edge gives you the tools to tailor your edge operations to your team’s expertise and your environment’s needs.

The decision comes down to your priorities:

  • Flexibility and granular control → package-based Red Hat Device Edge with Red Hat Satellite or Ansible Automation Platform
     
  • Consistency and simplified distribution → image-based Red Hat Device Edge with Edge Manager
     
  • Kubernetes application management → Add MicroShift with Red Hat Advanced Cluster Management, GitOps, or embedded application

With the arrival of Red Hat Edge Manager, organizations can look forward to a new level of automation and scalability for image-based edge computing. Combined with Red Hat Device Edge’s foundation, these capabilities help build manageable, resilient edge infrastructures ready for the future.

Ready to move forward? Evaluate your deployment model, align it with your operational maturity, and choose the management strategy that sets your edge journey up for long-term success. Learn more about Red Hat Device Edge today.

Hatville:エッジコンピューティングが実用化されたミニチュアシティ

Hatville。この小さな大都市を探索し、エッジコンピューティングが私たちの身の回りの産業にどのような変革をもたらすかを体験してください。

執筆者紹介

Hey there! I'm Luis, a tech enthusiast who thrives at the intersection of Edge Computing, AI/ML, and MLOps. With over 15 years in the industry, I’ve built a career around solving complex problems, driving innovation, and pushing the boundaries of open-source technology.

By day, I help organizations design scalable architectures and refine their cloud-to-edge strategies, with a strong focus on extending AI solutions to the Edge for real-time processing, automation, and efficiency. By night, I geek out over the latest AI models and MLOps tools.

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