Cloud native computing and edge computing are two of the most important aspects of modern infrastructure. While cloud native computing is the second wave of cloud computing responsible for delivering the best ROI in the cloud, edge computing is the practice of processing data near the edge of a network, where the data is being generated instead of doing it in a centralized data processing warehouse. It is a variant of cloud computing with infrastructure services for compute, storage and networking placed physically closer to the field devices that are actually generating the data. Edge computing is a distributed, open IT architecture that features decentralized processing power enabling mobile computing and Internet of Things (IoT) technologies. As part of edge computing, the data is processed by the device itself or local computer or server, rather than being sent to the data processing warehouse, as mentioned earlier, thereby increasing service availability, emerging as a quick and reliable platform to solve unique challenges across different industries.
As the popularity of edge computing has grown, Kubernetes has become an important constituent in edge computing systems. Kubernetes helps organizations run containers at the edge such that there is a maximization of resources, increased ease of testing, smoother and faster functioning of the DevOps teams, while helping them consume and analyze data in a faster and smoother manner.
It is an established fact that the volume of data generated each day is increasing at an unimaginable pace. With this, organizations need to pick an economic and feasible option – whether to transmit data from the edge to the core for processing and analyzing, or filter and pre-process the data locally. It is important for every organization that the workloads that do not entail major latency requirements be served by the most optimal cloud solutions possible. This also generates a host of new use cases that would require operators to re-think how the network has been architected. This is where edge computing becomes extremely useful for organizations.
What are the benefits of edge computing?
There are three main benefits of edge computing –
- Lower Latency: This boosts the performance of the field devices by enabling quicker responses to a larger number of events
- Lower Internet Traffic: This helps the organization reduce costs and boost their overall throughput, giving the core data center a better chance to support a larger number of field devices
- Higher Availability: This is especially true for internet- dependent applications, and is extremely helpful when there is a network outage between the edge and the core
The three most important factors that are spearheading the requirement for edge computing are –
- Increased amount of data generated from smart devices and IoT
- Roll-out of 5G
- Increased adoption of artificial intelligence tasks, especially, at the edge
All these three factors demand an ability to handle an elastic demand and shifting workloads.
For edge computing to be successful, the edge clouds need to have two layers –
- Infrastructure-as-a-Service (IaaS) layer: This layer provides compute and storage resources, satisfies network performance requirements (ultra-low latency and high bandwidth)
- Kubernetes layer: This layers orchestrates containerized workloads in the data center and public clouds
The Kubernetes in the second layer is optional, but it has become an immensely popular tool for the later, and has become a sort of de facto standard. Kubernetes successfully provides a common layer of abstraction over and above the physical resources it provides, i.e., compute, storage and networking; so, developers and DevOps engineers are able to deploy applications and services in a standard manner, anywhere in the system, including at the edge. Kubernetes helps developers to smoothen out and simply their DevOps practices, while reducing the time they spend integrating heterogeneous operating environments.
Chick-fil-A, which is apparently on track to be the third largest US fast-food chain, just behind McDonald’s and Starbucks, is known for more than just its chicken sandwiches and waffle fries. The company is also a market-leader in adopting this deadly combination of Kubernetes and edge computing. Chick-fil-A runs Kubernetes at the edge on about 6000 devices in all 2000 of its restaurants, which forms part of its Internet of Things strategy for collecting and analyzing larger amounts of data to deliver a better customer experience and boost operational efficiency. For instance, by using Kubernetes and edge computing, it figures out how many waffle fries should be cooked in a minute every day to minimize delays and improve the overall experience of the customers.
This is just one example. This combination of Kubernetes and edge computing is also immensely beneficial for telecom companies. With cut-throat competition in the sector, edge computing and Kubernetes can help companies stand apart with better use cases like industrial automation, virtual reality, connected cars, sensor networks, smart cities, etc.
Kubernetes and edge computing, together, can find ample applications across different industries and sectors. They can help improve efficiency and productivity everywhere, and is a great combination of technologies for the overall benefit of the organizations. Cognixia – world’s leading digital workforce solutions company provides competent, carefully crafted training programs in cloud computing, DevOps and edge computing for individuals as well as corporate workforce, to help them realize their potential and build a successful career in this field. Our band of highly experienced trainers, adopt an interactive, hands-on manner of learning that helps participants thoroughly imbibe all the concepts learnt in class. For corporate customers, we offer customizable training programs to exactly meet their specific requirements. To know more about out training programs, reach out to us today.
