akri VS shifu

akri: AdmissionErrors and if it actually mounts something the process cant access the device for some reason.

If you're talking about hardware attached to nodes, Akri might be of interest: https://github.com/project-akri/akri

Fun hands on use-case/story. Trying to connect sensors & actuators sounds fun! It's clear that they need some kind of infra/platform that they can run on-prem, & this feels like a lock.

There's a new Dynamic Resource api in k8s 1.26 that feels potentially well suited to managing their various kinds of node-attached resources in a pretty broad/generic/cloudy way. Taking the cloud from anonymous compute/storage nodes to an all encompassing management system for whatever we have is an interesting next step. I rather doubt we'll see folks like this spend the 3x effort to pioneer use of these abstractions but over time it should start to emerge & become more regular. https://kubernetes.io/docs/concepts/scheduling-eviction/dyna...

There's also a really neat really nice CNCF Sandbox project Akri which performs semi-similar-ish functions as Dynamic Resources. One of the examples they use as a goto is managing a fleet of OVNIF cameras, like, security cameras. https://github.com/project-akri/akri

On another topic, appreciate this article talking about the mixed human/robot workflows. Good to consider! I worked at a great & interesting data-warehouse company a long time ago that had some very complex long running ETL pipelines & limited compute resources (good number of boxes... pre-cloud era!), and a lot of time-sensitivity. The company used Jira to manage the ETL end to end, with custom workflows where work would gate, process, get checked through various stages, with processors updating the ticket as work advanced or to report % complete. Intensely sharp choice not to build it ourselves, to use a tool for tracking work, even though the code (robots) we built were doing 9/10ths the work. Fun to see a similar topic discussed here.

Good problem setup, interesting view here. Would appreciate a little more technical specifics, but still fun to see.

You need something to act as the runner queue to schedule the nodes, so perhaps you could pull them into a k8s cluster and auto-scale oh the load queue. Using something like this to tag the nodes what special devices might be attached on certain nodes https://github.com/deislabs/akri

Some notes on Plex/Emby/Kodi and transcoding. If you want true transcoding with GPU acceleration, you have to have Nvidia GPU or be a k8s device plugin genius. The whole idea of mounting elastic devices in k8s is fairly new and rather complex. In the mean time transcoding is best done on a beefy device with a proper CPU (eg i7) or specifically Nvidia GPU because there are numerous pre-made plugins. I just run Plex and Emby on an old ATX gaming machine without GPU acceleration and it works totally fine. They were barely usable for just me when running on the RPis, wouldn't recommend it unless you can figure out how to mount the correct devices in the pod using a custom raspberry pi device plugin . . . lol good luck! - Arm labs device manager: https://community.arm.com/developer/research/b/articles/posts/a-smarter-device-manager-for-kubernetes-on-the-edge - Deis labs Akri device manager: https://github.com/deislabs/akri - Nvidia GPU plugin: https://github.com/NVIDIA/k8s-device-plugin

To create the Shifu Plugin for ChatGPT, I utilized an open-source infrastructure called Shifu: https://github.com/Edgenesis/shifu. Shifu is a Kubernetes-native industrial edge that allows complete IoT interoperability by virtualizing devices into Kubernetes pods. This adaptability and flexibility made it possible for seamless integration with ChatGPT, providing AI access to and control over the physical world. This approach can be applied to a wide range of IoT devices, further expanding AI-human interaction possibilities.

It's heart breaking to see talents especially former colleagues losing their jobs. But it is also a big warning sign telling people to select open-source software for their infrastructure. With that being said, our startup Edgenesis is building an open-source IoT framework, shifu

I don't know if you have any specific problem you wish to address to, but I've been paying attention to this project: https://github.com/Edgenesis/shifu, it is a Kubernetes-native IoT development framework. If you wish to use k8s to "easily scale and manage large numbers of IoT devices, automate deployments, and ensure high availability", maybe you can take a look at this.

I've been working on a k8s native IoT development framework as well: https://github.com/edgenesis/shifu

Should metaverse be completely virtual? Should it be simply a utopia created according to our needs? But what about the real world? Are we all just gonna discard it and escape to the virtual metaverse? That sounds both impractical and disastrous. I would much prefer a physical metaverse instead.

Wait... What the hell is a physical metaverse? In my opinion, it is a place where we can easily alter things around us to serve our needs. But how can we get there? Here's my answer -- IoT. If we can orchestrate various IoT devices with ease, then we are off to a good start. Smart home is a tangible example, it can be viewed as the prototype of a physical metaverse. Here comes the PROBLEM: how can we orchestrate all these heterogeneous IoT devices with ease? Here I proudly introduce you Shifu, a framework to build your own physical metaverse.

The idea of Shifu is quite simple: Shifu creates digtal twins for IoT devices in the form of Kubernetes pods. This way, we can quickly integrate heterogeneous IoT devices into the cluster, and expose their capabilities as APIs. It means Shifu will make building IoT APPs as simple as building web APPs.

Through a "device integration-- data acquisition-- app development-- decision distribution" feedback loop, Shifu enables developers to build their own physical metaverse. What's even better, Shifu is more than just a crazy idea. Shifu has been successfully deployed in various fully automated labs/factories and received exciting results.

Talk is cheap, it's time to show you the code. Please pay us a visit at https://github.com/Edgenesis/shifu, and join the revolution of building your own physical metaverse!!!

BTW, don't forget to give us a star! It means A LOT to us: ) Thx!

Check out our Github page at https://github.com/Edgenesis/shifu for more information and to see how Shifu can help your business with IoT development.

If you're a developer working with MQTT, I highly recommend giving Shifu a try. To get started, head over to it's Github page at https://github.com/Edgenesis/shifu and take a look at the documentation and code examples. It's a game changer and will save you a lot of time and effort.

Shifu is a Kubernetes native, production-grade, protocol & vendor agnostic IoT development framework. You can develope your application while managing your devices, spare the need for maintaining an additional O&M infrastructure. Check https://github.com/Edgenesis/shifu for more details!

Before you dig deep into https://shifu.run for our great product, buzzword-wise it for sure has the following features that can replace what you enjoy in Google IoT Core as easily and fast as turning a switch: