Gartner defines edge computing as solutions that facilitate data processing at or near the source of data generation. In this context edge computing is a key consideration while planning your digital business roadmap.
“Organizations that have embarked on a digital business journey have realized that a more decentralized approach is required to address digital business infrastructure requirements,” says Gartner.
Many scenarios like autonomous driving cars and industrial equipment monitoring systems have very low latency tolerance. Large volumes of data are collected and analyzed instantaneously to take action. Even a delay of milliseconds renders the data stale and useless. With edge computing data can be processed locally, decisions can be taken in real-time, and only relevant data can be transferred back to the hub.
Containers are Lightweight
Containers by definition are lightweight with a very low footprint which makes them ideal for running on edge devices. They allow legacy services to interact with modern cloud services like AI/ML to achieve rapid in-place computation. This is the primary reason that many machine learning models leverage containers.
Additionally, Containers are units that can be deployed to any device, built using any architecture as long as it can run the container runtime. This allows containers to run on a wide variety of hardware without the need to port the application code. Updating containers in-place is very simple and is greatly simplified by orchestration solutions like Kubernetes.
“Around 10% of enterprise-generated data is created and processed outside a traditional centralized data center or cloud. By 2025, Gartner predicts this figure will reach 75%”
What does it take to Leverage Edge Computing?
Containerization of legacy applications is a good starting point for edge computing initiatives. Organizations build an estate of business processes and enterprise applications over decades. While it’s easier to develop an application ground-up to suit cloud and edge environments, it is much harder to transform legacy applications to leverage cloud and containers. With firms planning to use these legacy stacks and infuse them with the latest AI/ML capabilities, the proportion of such applications could be as high as 70 to 80% of the total edge computing estate.
CloudHedge with its proprietary containerization technology ‘Discover + Transform’ enables organizations to automatically transform their legacy software into process containers. This allows organizations to realize their edge computing use-cases while leveraging decades of investment in existing applications. The entire process is secured, automated, and streamlined.
Once containerized, these enterprise apps need to be deployed & managed across thousands of devices, working in several clusters, with their own policies and guidelines. The situation to manage these complex clusters of devices, services, and networks can get very complicated, really fast. Solutions like recently announced IBM Edge Application Manager addresses these needs by providing a central control pane, from where thousands of edge devices can be managed, monitored, upgraded, and visualized.
Read the exclusive press-release to know how CloudHedge is working with IBM to support edge computing initiatives – Link