Shulou(Shulou.com)06/02 Report--

​ KubeEdge became the first Kubernetes native edge computing platform, and Edge and cloud components are now open source!

Open source edge computing is going through the most dynamic stage of development in its industry. So many open source platforms, so many integration and so many standardization measures! This shows a strong incentive to build a better platform to bring cloud computing to the edge to meet growing demand. KubeEdge, announced last year, now brings good news for cloud native computing! It provides a complete Kubernetes-based edge computing solution with independent cloud and edge core modules. Currently, both cloud and edge modules are open source.

Unlike some of the lightweight kubernetes platforms available, KubeEdge aims to build edge computing solutions that extend the cloud. The control plane is located in the cloud and is scalable. At the same time, the edge can work in offline mode. It is also lightweight and containerized, and can support edge heterogeneous hardware. By optimizing edge resources, KubeEdge can save a lot of setup and operating costs for edge solutions. This makes it the most compelling edge computing platform in the world, based on Kubernetes!

Kube (rnetes) Edge! -create a new Kubernetes-based ecosystem for edge computing

The main goal of KubeEdge is to expand the Kubernetes ecosystem from the cloud to the edge. Since the announcement of KubeCon in Shanghai in November 2018, the architecture direction of KubeEdge has been the same as that of Kubernetes, just like its name!

It starts with v0.1 and provides basic edge computing capabilities. Now, with its latest version v0.2, it connects cloud components and completes the loop. With a consistent and scalable interface based on Kubernetes, KubeEdge supports the orchestration and management of edge clusters, similar to how Kubernetes is managed in the cloud. This provides a seamless possibility to quickly and effectively promote cloud computing capabilities to the edge.

Based on its roadmap and architecture, KubeEdge attempts to support all edge nodes, applications, devices, and even cluster management consistent with the Kubernetes interface. This will help edge clouds behave exactly like cloud clusters. This can save a lot of time and cost for KubeEdge-based edge cloud development deployment.

KubeEdge provides a containerized edge computing platform with inherent scalability. Because it is modular and optimized, it is lightweight (66MB takes up space and ~ 30MB running memory) and can be deployed on devices with few resources. Similarly, edge nodes can have different hardware architectures and different hardware configurations. For device connections, it can support multiple protocols and use standard MQTT-based communication. This helps to effectively expand edge clusters with new nodes and devices.

You heard me!

The KubeEdge cloud core module is open source!

By opening the edge and cloud modules, KubeEdge brings a complete cloud provider-neutral lightweight heterogeneous edge computing platform. It is now ready to support building a complete Kubernetes ecosystem for edge computing and leverages most existing cloud native projects or software modules. This enables the edge of the mini-cloud to support demanding use cases such as data analysis, video analysis machine learning, and so on.

KubeEdge architecture: build Kubernetes native edge computing!

The core architectural principle of KubeEdge is to build interfaces that are consistent with Kubernetes, both in the cloud and at the edge.

Edged: a containerized application that manages Edge.

Communication interface module of EdgeHub:Edge. It is a Web socket client responsible for edge computing interaction with Cloud Service.

CloudHub: the communication interface module in the cloud. An Web socket server that monitors changes in the cloud, caches, and sends messages to EdgeHub.

EdgeController: manages Edge nodes. It is an extended Kubernetes controller for managing edge nodes and pod metadata to locate data to specific edge nodes.

EventBus: use MQTT to handle internal edge communication. It is a MQTT client that interacts with the MQTT server (mosquitto), providing publish and subscribe capabilities for other components.

DeviceTwin: it is a software mirror of a device that processes device metadata. This module helps to process the device status and synchronize it to the cloud. It also provides a query interface for applications because it interfaces with lightweight databases (SQLite).

MetaManager: it manages the metadata of edge nodes. This is the message handler between edged and edgehub. It is also responsible for storing / retrieving metadata to a lightweight database (SQLite).

Even if you want to add more control plane modules based on architectural optimization and improvements (such as enhanced security), it is simple because it uses consistent registration and modular communication in these modules.

KubeEdge provides a scalable, lightweight Kubernetes native edge computing platform that can work in offline mode

It helps simplify edge application development and deployment.

The cloud provider is neutral and can run the cloud core module on any computing node.

Release 0.1 to 0.2-change the rules of the game!

KubeEdge v0.1 was released at the end of December 2018 with very basic edge capabilities to manage edge applications as well as Kubernetes API for nodes, pod, configurations, and so on. In about 2 months, KubeEdge v0.2 was released on March 5, 2019. This version provides cloud core modules and supports end-to-end open source edge computing solutions. The cloud core module can be deployed to any computing node from any cloud provider or local department.

Complete edge solutions, including on laptops, can now be easily installed and tested.

Run everywhere-simple and light

As mentioned above, KubeEdge Edge and Cloud core components can be easily deployed, and user applications can be run. The edge core has the footprint of 66MB and only needs the memory of 30MB to run. Similarly, the cloud core can run on any cloud node. (users can also experience it by running it on a laptop.)

The installation is simple and can be done in a few steps:

Set prerequisites for Docker, KubernetesMQTT, and openssl clones and build KubeEdge Cloud and Edge running Cloud running Edge

KubeEdge/kubeedge provides detailed steps for each step

Https://github.com/kubeedge/kubeedge

The future: take off through competent functions and community collaboration

KubeEdge is developed by community members who are active contributors to Kubernetes/CNCF and engage in edge computing research. The KubeEdge team is also actively working with Kubernetes IOT/EDGE WORKING GROUP. Within months of KubeEdge's announcement, it attracted members from different organizations, including JD.com, Zhejiang University, SEL Labs, Eclipse, China Mobile, ARM and Intel to build the platform and ecosystem.

KubeEdge provides a clear roadmap for its upcoming major release in 2019. V1.0 aims to provide complete edge clustering and device management solutions through standard edge-to-edge communication, while v2.0 aims to have advanced functions such as edge service grid, functional services, data analysis, and so on. In addition, for all functions, the KubeEdge architecture will attempt to take advantage of existing CNCF projects / software.

The KubeEdge community needs different organizations with their requirements, use cases, and support to build it. Join the kubernetes native edge computing platform, which extends the cloud native computing paradigm to the edge cloud.

How to participate?

We welcome more cooperation to build the Kubernetes native edge computing ecosystem. Please join us!

Twitter: https://twitter.com/kubeedge

Slack:kubeedge.slack.com

Website: https://kubeedge.io

GitHub: https://github.com/kubeedge/kubeedge

Email: kubeedge@gmail.com

Date of the meeting:

Announcement date of the schedule of the meeting: April 10, 2019

Date of the conference: June 24-26, 2019

For related services, please visit: https://support.huaweicloud.com/cce/index.html?utm_content=cce_helpcenter_2019

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