"DevOps" and "Endpoint Management" are not frequently used together. When people talk about DevOps, they usually mean creating and deploying software that will run on servers rather than endpoint devices. However, DevOps could teach us just as much about endpoint device management as it does about traditional software delivery. The issues of endpoint device management are strikingly similar to those of software delivery, and the DevOps practices that make software delivery faster and more reliable can also help with endpoint administration.
Deploying and managing a range of heterogeneous endpoints within an organization has always been challenging. Outages, glitches, and dependability concerns among hardware and software elements and situational realities are always around. With rapid release cycles, fleet managers have to consistently monitor the impact of new updates on endpoints to avoid endpoint device failures. Beyond regular performance monitoring, organizations need deep observability to better understand the processes and challenges associated with endpoint management.
Observability can assist in diagnosing hardware and operating system issues, resolving outages, patching individual clients, and more when it comes to fleet management. In the following section, we’ll look into common endpoint management challenges and how they can be resolved with popular DevOps principles.
#1 Teams Working in Silos
The fact that the teams in charge of controlling endpoints are segregated is maybe one of the biggest challenges of endpoint management. Endpoints are often configured by one group, while another handles support requests and other operations.
Developers are the third team who gets to work on endpoints if you’re designing custom applications. Even if they’re not directly involved in endpoint management, they have a stake in it. The endpoint management process becomes slow, inefficient, and error-prone when these teams operate separately and without understanding each other's aims and priorities.
These silos are pretty similar to those in traditional IT companies between development and IT operations teams, and the DevOps approach tries to break them down.
#2 Infrastructure Management at Scale
Large organizations have massive and ever-growing infrastructure, comparable in scale to that of a large data center or public cloud. A large IT fleet's endpoint device might easily number in the tens of thousands, if not hundreds of thousands. A comprehensive strategy to automate device provisioning, deployment, and monitoring is vital to ensure speed, consistency, and efficiency within teams.
#3 Multiple Endpoints & Configurations
Managing large IT resource fleets with numerous different configurations is another challenge. Teams must work harder to establish a reliable and practical approach to track all of their devices and configurations and ensure that software is installed and updated as needed.
This variation is akin to the many application versions and deployments that DevOps teams must handle as part of their software delivery processes.
#4 Continual Change
Not only do devices and configurations vary over time, but so do their locations. Endpoint management teams must be able to adapt to such changing conditions.
This ongoing shift is analogous to the regular changes in a configuration that DevOps teams experience within the environments where they release software. Endpoint management teams, like DevOps teams, must be able to provide a consistent end-user experience even if they have no idea what their infrastructure or configurations will look like from one hour to the next.
Organizations can gain higher stability and automation in large-scale endpoint devices by addressing endpoints the same way DevOps software delivery teams treat infrastructure and application code.
The following are ways in which Chef applies principles of DevOps to endpoint management:
1. As device configurations are continuously changing and updates are frequent, Chef ensures that every small incremental change is rapidly and consistently applied across endpoints—just as DevOps teams attempt to deliver quick application updates rather than work in a traditional waterfall approach. Introducing a new sub-fleet of devices or a new set of adjustments is not a good idea. Accept updates in small increments but regularly.
Infrastructure-as-Code tools like Chef automate the configuration and management of hundreds of servers that DevOps teams use. Centralized policies that govern how devices are configured and which software runs on them are the foundations of Infrastructure automation. Chef extends this capability to define and apply configurations across large fleets of heterogeneous endpoints.
2. DevOps practitioners frequently refer to servers as "cattle" to indicate that they can be easily replaced when something goes wrong with one member of the herd. Endpoint management follows a similar principle: instead of obsessing over tiny faults with individual devices, replacement is an ideal alternative (especially if you can automate device configuration and deployment rather than trying to update each device individually if something has to be changed).
Built on the principles of DevOps, endpoint management solutions like Chef are platform agnostic. Chef operates across various devices (laptops, desktops, and kiosks), form factors, and performance levels, without the need for any code changes. This allows you to upgrade your appliances or introduce a new product form factor without changing your endpoint management solution.
Join us on May 11, 2022, at 10:00 AM PT, to understand more about how Chef uses DevOps principles to manage endpoints.
Sudeep Charles, Senior Manager, Product Marketing, and Chaithra Mailankody, Associate Product Manager at Chef, will discuss current endpoint management trends and challenges, as well as how Chef Desktop manages them using DevOps principles. A panel will also address all your questions during the Q&A session.
If the content of this blog piques your interest, you should register for the webinar to see how Chef can help you manage your endpoints efficiently.