February 19, 2020 By Jeffrey Palmer 3 min read

Learn how autonomous management will revolutionize your edge computing approach.

If you’re a CIO in retail, manufacturing, distribution, banking, or just about any other industry, you’re building a strategy that will empower your lines of business to increase revenue and cost savings by adopting a massively decentralized computing architecture, otherwise known as edge computing.   

However, you’re concerned that traditional management approaches aren’t designed to manage and secure a topology with tens of thousands of edge servers and hundreds of thousands of edge devices in a cost-effective manner.  

How to handle the scale, variability, and rate of change of 5G and enterprise edge applications

As computing expands, the scale, variability, and rate of change of edge environments present a challenge that traditional management software was not designed for. It was originally built for centralized topologies with many servers (often standardized) in a few data centers or public cloud regions, with infrequent changes to the environment.

Now with edge, you have tens of thousands of servers and hundreds of thousands of edge devices that are much more heterogeneous, deployed in thousands of remote locations, with new locations or edge devices and servers being continuously added.  It’s nearly impossible for an administrator to understand the topology and relevant differences, which is critical when attempting to deploy new applications to the edge.

“Developing a successful edge strategy requires taking into consideration the complexity of management endpoints and recognizing that scale and variability are dramatically different from traditional on-premises or public cloud deployments.”

IDC White Paper, sponsored by IBM, “The Importance of Effective Operations in Unlocking Edge IT Value,” January 2020

Move to autonomous management

The massive scale, variability, and rate of change of edge environments requires a new approach—an autonomous management approach. Management actions such as deployment negotiation, agreement, execution, and on-going validation of workloads must be offloaded from the human administrator and onto autonomous management software.

This is achieved by asynchronous communication between software agents on edge endpoints and a management hub that constitute the autonomous management software. The actions carried out are based on the administrator intent but without his or her intervention, even during new endpoint onboarding.

Watch to learn more about autonomous management:

Administrators express an intent and autonomous management software executes in line with the intent

Here’s an example: “Deploy this application on any edge server with OpenShift 4.2, 8 cores free, 2GB of memory, 1TB of storage, not located in Toronto, Canada, not running an application owned by dept ABCD.”

Edge software agents autonomously decide if the edge endpoints they represent meet the intent set by the administrator, and if so, automatically initiate the installation of the application. The software agents continuously check for agreement validity over time. For instance, if the version of Red Hat OpenShift is later upgraded to 4.3, the agent can notify the administrator that the agreement is no longer valid, or it can automatically shut down the application, all without administrator initiation or intervention.  

With autonomous management, a single administrator can manage tens of thousands of endpoints without human initiation or intervention. 

Your house is becoming autonomous, isn’t it time your management software did?

Take your next steps in edge computing

This is truly an amazing time. The convergence of 5G, edge computing, and AI will spark a level of innovation that hasn’t been seen before. IBM believes enterprises can use edge IT to enable faster insights and actions, maintain continuous operations, and provide new customer experiences.  

Was this article helpful?
YesNo

More from Cloud

IBM Tech Now: April 8, 2024

< 1 min read - ​Welcome IBM Tech Now, our video web series featuring the latest and greatest news and announcements in the world of technology. Make sure you subscribe to our YouTube channel to be notified every time a new IBM Tech Now video is published. IBM Tech Now: Episode 96 On this episode, we're covering the following topics: IBM Cloud Logs A collaboration with IBM watsonx.ai and Anaconda IBM offerings in the G2 Spring Reports Stay plugged in You can check out the…

The advantages and disadvantages of private cloud 

6 min read - The popularity of private cloud is growing, primarily driven by the need for greater data security. Across industries like education, retail and government, organizations are choosing private cloud settings to conduct business use cases involving workloads with sensitive information and to comply with data privacy and compliance needs. In a report from Technavio (link resides outside ibm.com), the private cloud services market size is estimated to grow at a CAGR of 26.71% between 2023 and 2028, and it is forecast to increase by…

Optimize observability with IBM Cloud Logs to help improve infrastructure and app performance

5 min read - There is a dilemma facing infrastructure and app performance—as workloads generate an expanding amount of observability data, it puts increased pressure on collection tool abilities to process it all. The resulting data stress becomes expensive to manage and makes it harder to obtain actionable insights from the data itself, making it harder to have fast, effective, and cost-efficient performance management. A recent IDC study found that 57% of large enterprises are either collecting too much or too little observability data.…

IBM Newsletters

Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters