Kubernetes
is the key component in the data centers that are modernizing and adopting
cloud-native development architecture to deliver applications using containers.
Capabilities like orchestrating VMs and containers together make Kubernetes the
go-to platform for modern application infrastructure adopters. Telecom
operators are also using Kubernetes to orchestrate their applications in a
distributed environment involving many edge nodes.
But due to
the large scale of Telco networks that includes disparate cloud systems,
Kubernetes adoption requires different architectures for different use cases.
Specifically, if we look at a use case where Kubernetes is
used to orchestrate edge workloads, there are various frameworks and public cloud managed
Kubernetes solutions are available that offer different benefits and gives
telecom operator choices to select the best fit. In a recent Kubernetes on Edge Day sessions at KubeCon Europe 2021, many
new use cases of Kubernetes for the edge have been discussed along with a
showcase of cross-platform integration that may help enterprises adopting 5G
edge and telecom operators to scale it to a high level.
Here is a
high-level overview of some of the key sessions.
The Edge
concept
There are
different concepts of edge that have been discussed so far by different
communities and technology solution experts. But when Kubernetes is coming into
infrastructure, IT operators need to clearly understand the key pillars on
which the Kubernetes deployment will seamlessly deliver the low latency
performance in telco or private 5G use cases. First, there should be a strong
implementation of Kubernetes management at scale. Second, operators need to
choose the lightweight K8s for edge solution which is preferably certified by
CNCF. And third, there should have a lightweight OS deployed at every node from
Cloud to the far edge.
Microsoft's
Akri Project: Microsoft's
Akri project is an innovation that will surely break into multiple
Kubernetes-based edge implementations. It discovers and monitors far edge
devices of brownfield devices that cannot have own compute - can be a part of
Kubernetes cluster. Akri platform will let these devices exposed to the
Kubernetes cluster.
AI/ML
with TensorFlow: TensorFlow is a machine learning platform that takes inputs to generate
insights. It can be deployed on cloud, on-premises, or edge nodes where ML
operations need to perform. In one of the sessions, it has been shown that
Kubernetes clusters deployed in the cloud and edge can host analytics tools set
(Prometheus, EnMasse/MQQT, Apache Camel, AlertManager, Jupyter, etc) to process
ML request with the lowest latency.
Architectures
for Kubernetes on the edge: While deploying Kubernetes for an edge, there are many architecture
choices that are varied per use case. And each architecture poses new
challenges. But the bottom line is - there is no one-size-fits-all solution as
various workloads have different requirements and IT teams are focusing on the
connection between network nodes. So, the overall architecture needs to evolve
centralized and distributed control planes.
Robotics: Kubernetes has also been
implemented in Robotics. Sony engineers have showcased how the K8s cluster
systems can be for distributed system integration of robots and perform
specific tasks collaboratively.
Laser-based
Manufacturing: Another
interesting use case discussed by Moritz Kröger who is a Researcher at RWTH
Chair for Lasertechnology that leveraged Kubernetes based distributed system.
Kubernetes features like automation configuration management and flexibility in
moving workloads in clusters give operational benefits to Laser manufacturing
machines.
OpenYurt
+ EdgeXFoundry:
OpenYurt is yet another open-source framework that extends the orchestration
features of upstream Kubernetes to the edge. It is showcased that - it can
integrate with EdgeXFoundtry in 5G IoT edge use cases where EdgeXFoundtry is
used to manage the IoT devices and OpenYurt is used to handle server
environments using OpenYurt plugins set.
Using
GitOps: Kubernetes
supports the cloud-native application orchestration as well as declarative
orchestration. It is possible to apply the GitOps approach to achieve the Zero
Touch Provisioning at multiple edges from the central data center.
Hong
Kong-Zhuhai-Macao Bridge: Another use case discussed is - Kubernetes is implemented in edge
infrastructure for managing applications that are managing sensors at Hong
Kong-Zhuhai-Macao Bridge. The use case is unique as it focuses on how to define
the sensor devices on the bridge as CRD in Kubernetes, how to associate each
device with the CI/CD, and how to manage and operate the Applications deployed
on edge nodes.
Node
Feature Discovery: There
are a vast number of end devices that can be part of thousands of edge nodes
connected to data centers. Similar to Akri project, Node Feature
Discovery (NFD) add-on
can be used to detect and push into Kubernetes clusters to orchestrate with
edge server as well as cloud systems.
Kuiper
and KubeEdge: EMQ's
Kuiper is the open-source data analytics/streaming software that runs on edge
devices that have low resource requirements. It can integrate with KubeEdge
where we get a combined solution that leverage KubeEdge's application
orchestration capabilities and with streaming analytics. The combined solution
delivers low latency, saving cost on bandwidth, ease in implementing business
logic and operators can manage and deploy Kuiper software applications from the
cloud.
##
Calsoft is conducting a webinar on the topic, 'Demystifying Kubernetes for Edge', on May 21,
2021. This webinar will touch upon the importance of Kubernetes for simplifying
Edge deployment, along with the most sought-after solutions to real Edge
implementation challenges. Get yourself registered here.
ABOUT THE AUTHOR
Sagar
Nangare, Digital Strategist / Assistant Manager, Marketing at Calsoft
Inc.