As embedded devices become increasingly prevalent and complex, managing firmware updates and monitoring fleet health at scale can be a daunting challenge. This is where device cohorts come into play.
A device cohort is a group of devices that share common characteristics or are used for a similar purpose. These shared traits can be based on factors such as device type, hardware revision, firmware version, deployment stage, or geographic location. By organizing devices into cohorts, you can manage and monitor them more effectively, targeting specific groups for firmware updates, feature releases, and data analysis.
Common Use Cases for Cohorts Device cohorts are versatile tools that can be applied to a wide range of scenarios. Some of the most common use cases include:
One of the key benefits of using device cohorts is the ability to view and analyze metrics in the context of specific device groups. By comparing data across cohorts, you can gain valuable insights into how different subsets of your fleet are behaving and performing.
Cohort-based metrics enable you to:
When starting out with cohort-based firmware management, it's recommended to create at least four essential cohorts:
Even for smaller teams managing a few thousand devices, starting with these four basic cohorts can provide a solid foundation for organizing and managing firmware releases effectively. As the team and device fleet grow, additional cohorts can be introduced to accommodate more specific use cases, such as beta testing groups, regional or country-specific firmware variants, partner or customer-specific builds, or experimental releases.
By adopting this basic cohort structure, teams can begin to realize the benefits of targeted firmware deployments, phased rollouts, and data-driven decision-making, even at a smaller scale. The flexibility of Peridio's cohort management system allows teams to easily expand and adapt their cohort strategy as their needs evolve.
One powerful technique for managing firmware releases is to use tags within cohorts to implement a phased rollout strategy. By assigning tags to subsets of devices within a cohort (e.g., phase1
, phase2
, phase3
), you can gradually deploy updates to increasingly larger groups.
A phased-release workflow using tags might look like this:
phase1
) for testingphase2
)Once a release is ready for production, the release mechanism can be switched from tags to a percentage-based approach. This allows for a gradual rollout to a larger portion of the device fleet, starting with a small percentage and increasing it to 100% as confidence in the release grows.
It's important to note that releases can be paused at any time if issues are detected, providing a safety net and allowing for quick mitigation of potential problems. Additionally, eligibility for a release can be specified using semantic versioning (semver), ensuring that only devices meeting specific version requirements receive the update.
This post will be followed by visual guides showcasing the cohort setup process, phased rollout workflows, and best practices, which will provide a clear and practical understanding of how to implement cohort-based firmware management effectively.
This measured approach allows you to catch and address issues early, minimizing the impact on your overall fleet.
Device cohorts are a powerful tool for simplifying firmware management at scale. By organizing devices into logical groups and leveraging cohort-based metrics, you can streamline your update processes, gain valuable insights into fleet performance, and make data-driven decisions.
Peridio makes it easy to get started with cohorts, providing a flexible and intuitive platform for defining groups, deploying targeted updates, and monitoring device health. By adopting a cohort-based approach, starting with the essential cohorts recommended above, and following best practices like phased releases using tags and percentage-based rollouts, you can confidently manage your device fleet as it grows and evolves. Stay tuned for visual guides that will provide step-by-step walkthroughs of these processes.