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Is Kubernetes key to enabling edge workloads?

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Is Kubernetes key to enabling edge workloads?

By Borko Drljaca, product marketing writer at phoenixNAP

The growth of connected devices has been impressive over the past few years. In 2020, for the first time, devices such as smart cars, smart home appliances, and smart industrial equipment outnumbered traditional devices such as phones and computers.

Globally, the number of Internet of Things (IoT) units is expected to grow from 16.4 billion in 2022 to 30.9 billion in 2025, creating a robust ecosystem of data and networks. Edge devices keep getting smarter, faster, and more affordable, pulling IoT analytics away from the cloud and closer to the birthplace of data.

However, distributing workloads to hundreds of tiny computers and smart appliances that collect massive amounts of data is easier said than done. Organizations increasingly turn to containers to reduce their edge IT costs and boost data processing efficiency and consistency across environments. In return, developers leverage orchestration solutions such as Kubernetes (K8s) to get the most out of containers and overcome the challenges of building and deploying IoT solutions at the edge.

While solving many problems, this step brings along a set of its own complexities.

Why the edge needs Kubernetes

Lightweight and deployed in milliseconds, containers enable compatibility between different infrastructure environments and apps running across disparate platforms. Isolating edge workloads in containers protects them from cyber threats while microservices let developers update apps without worrying about platform-level dependencies.

Benefits of orchestrating edge containers with Kubernetes include:

  • Centralized Management — Users control the entire app deployment across on-prem, cloud, and edge environments through a single pane of glass.
  • Accelerated Scalability — Automatic network rerouting and the capability to self-heal or replace existing nodes in case of failure remove the need for manual scaling.
  • Simplified Deployment — Cloud-agnostic, DevOps-friendly, and deployable anywhere from VMs to bare metal environments, Kubernetes grants quick and reliable access to hybrid cloud computing.
  • Resource Optimization — Kubernetes maximizes the use of available resources on bare metal and provides an abstraction layer on top of VMs optimizing their deployment and use.

Kubernetes acts as an operating system, which is beneficial for applying continuous software and security patches for distributed applications. Also, developers can automate deployment management without disrupting the day-to-day functionality of IoT because Kubernetes is API-driven.

Despite the obvious reasons for containerizing edge applications, recent surveys show that only 15% of organizations deploy Kubernetes at distributed edge locations.

Kubernetes: Still a bit rough around the edges?

Kubernetes was designed for data center use and is best at orchestrating containers that run on machines with a shared location and network. By default, it does not manage workload orchestration across disparate edge systems.

The most notable challenges of deploying Kubernetes at the edge are:

  • Ensuring low-latency data movement — While Kubernetes can balance incoming traffic from external endpoints, the platform does not optimize the latency of internal traffic well.
  • Tackling resource limitations — Edge devices require minimal container images and configuration to ensure zero-trust security. Implementing autoscaling across heterogeneous hardware is very complex.
  • Multi-cluster management — Kubernetes assumes that an organization runs a single cluster, possibly split into namespaces. It has difficulties managing multi-clusters on independent devices at different locations.

To tackle resource constraints of the edge, developers must optimize their code and applications. Also, they need to invest time and resources into implementing data fabric compatibility into their Kubernetes deployments and improve the platform’s management of internal data movement. These processes put a substantial amount of strain on developers and can easily become cost-prohibitive.

Bringing Kubernetes to the edge of IoT

There are optimized flavors of Kubernetes such as MicroK8s, K3s, or KubeEdge that accommodate the specific needs of edge containers. With a smaller footprint and support for security and orchestration features of Kubernetes, these solutions help developers couple edge apps with their data center Kubernetes deployments.

Yet, a single organization with a small platform team will still struggle to manage hundreds of distributed clusters running thousands of services.

That is why cloud providers have come up with various solutions that help developers streamline the container cluster management process at scale. They are taking advantage of the potential of Kubernetes and the advent of edge data centers and implementing both into pay-per-use, API-driven infrastructure platforms and solutions.

This gives organizations the ability to easily deploy solutions such as bare metal cloud servers with pre-installed open-source container orchestration platforms right at their network’s edge. Integrated with popular Infrastructure-as-Code (IaC) tools, these edge servers allow for easy CI/CD integration and automated provisioning and management.

Such deployments make the creation of production-ready, multi-node Kubernetes environments possible in a matter of minutes, saving developers hours of setup work. Edge data centers enable low-latency regional access to servers and 5G technologies, making solutions hosted on their premises suitable for both current and future-ready edge workloads and apps.

Since edge computing is not an exclusive paradigm but more of a new frontier of the hybrid cloud, it is a perfect match for turnkey Kubernetes solutions such as bare metal cloud. With powerful storage, compute, and networking resources close to IoTs in warehouses and factories, organizations can simplify edge containerization without sacrificing performance, latency, and data availability.

About the author

Borko Drljaca is a product marketing writer at phoenixNAP, a global IT services provider offering progressive IaaS solutions delivered from strategic edge locations worldwide. Its cloud, dedicated servers, hardware leasing and colocation options are built to support growth and innovation in businesses of any size, enabling their digital transformation.

DISCLAIMER: Guest posts are submitted content. The views expressed in this post are that of the author, and don’t necessarily reflect the views of Edge Industry Review (

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