Kerberos Agent is a cutting edge video surveillance management system made available as Open Source under the MIT License. This means that all the source code is available for you or your company, and you can use, transform and distribute the source code; as long you keep a reference of the original license. Kerberos Agent can be used for commercial usage (which was not the case for v2). Read more about the license here.
This repository contains the next generation of Kerberos.io, Kerberos Open Source (v3), and is the successor of the machinery and web repositories. A switch in technologies and architecture has been made. This version is still under active development and can be followed on the develop branch and project overview.
Read more about this at the FAQ below.
Kerberos.io is a cutting edge video surveillance system with a strong focus on user experience, scalability, resilience, extension and integration. Kerberos.io provides different solutions, but from a high level point of view it comes into two flavours: Kerberos Open Source and Kerberos Enterprise. The main differences, very brief, between Open Source and Enterprise are described below. Both Kerberos Open Source and Kerberos Enterprise can be extended and integrated with Kerberos Storage and/or Kerberos Cloud.
Kerberos.io applies the concept of agents. An agent is running next to or on your camera, and is processing a single camera feed. It applies motion based recording and make those recordings available through a user friendly web interface. Kerberos Open Source allows you to connect to other cloud services or custom applications. Kerberos Open Source is perfect for personal usage and/or is a great tool if you only have a couple of surveillance cameras to be processed.
If you are looking for a solution that scales with your video surveillance or video analytics well, Kerberos Enterprise might be a better fit.
Kerberos Open Source will ship in different formats: Docker, binary, snap, KiOS. Version 3 is still in active development right now, and not yet released.
Kerberos Open Source is divided in two parts a
web. Both parts live in this repository in their relative folders. For development or running the application on your local machine, you have to run both the
machinery and the
web as described below. When running in production everything is shipped as only one artifact, read more about this at Building for production.
web is a React project which is the main entry point for an end user to view recordings, a livestream, and modify the configuration of the
git clone https://github.com/kerberos-io/opensource cd web yarn start
This will start a webserver and launches the web app on port
machinery is a Golang project which delivers two functions: it acts as the Kerberos Agent which is doing all the heavy lifting with camera processing and other kinds of logic, on the other hand it acts as a webserver (Rest API) that allows communication from the web (React) or any other custom application. The API is documented using
You can simply run the
machinery using following commands.
git clone https://github.com/kerberos-io/opensource cd machinery go run main.go run mycameraname 8080
This will launch the Kerberos Agent and run a webserver on port
8080. You can change the port by your own preference. We strongly support the usage of Goland, as it comes with all the debugging and linting features builtin.
Running Kerberos Open Source in production only require a single binary to run. Nevertheless, we have two parts, the
machinery and the
web, we merge them during build time. So this is what happens.
To build the Kerberos Open Source web app, you simply have to run the
build command of
yarn. This will create a
build directory inside the
web directory, which contains a minified version of the React application. Other than that, we also move this
build directory to the
cd web yarn build
machinery is also super easy 🚀, by using
go build you can create a single binary which ships it all; thank you Golang. After building you will endup with a binary called
main, this is what contains everything you need to run Kerberos Open Source.
Remember the build step of the
web part, during build time we move the build directory to the
machinery directory. Inside the
machinery web server we reference the
build directory. This makes it possible to just a have single web server that runs it all.
cd machinery go build
Inside the root of this
opensource repository, you will find a
Dockerfile. This file contains the instructions for building and shipping Kerberos Open Source. Important to note is that start from a prebuild base image,
kerberos/debian-opencv-ffmpeg:1.0.0. This base image contains already a couple of tools, such as Golang, FFmpeg and OpenCV. We do this for faster compilation times.
By running the
docker build command, you will create the Kerberos Open Source Docker image. After building you can simply run the image as a Docker container.
docker build -t kerberos/opensource . docker run -p 8080:8080 --name mycamera -d kerberos/opensource
We have noticed in the past (v1 and v2) splitting the repositories (machinery and web), created a lot of confusion within our community. People didn't understand the different versions and so on. This caused a lack of collaboration, and made it impossible for some people to collaborate and contribute.
Having a mono repo, which is well organised, simplifies the entry point for new people who would like to use, understand and/or contribute to Kerberos Open Source.
In previous versions (v1 and v2) we used technologies like C++, PHP and BackboneJS. 7 years ago this was still acceptable, however time has changed and new technologies such as React and Golang became very popular.
Due to previous reason we have decided to rebuild the Kerberos Open Source technology from scratch, taking into account all the feedback we acquired over the years. Having these technologies available, we will enable more people to contribute and use our technology.
We started the developments of Kerberos Enterprise a year ago (January, 2020), our focus here was scalability, and fast development and easy deployment. We noticed that with technologies such as Golang and React, we can still provide a highly performant video surveillance system.
Kerberos Open Source will use the same technology stack, and some code pieces, of Kerberos Enterprise which we have already build. We have a very clear now, of how a well developed and documented video surveillance system needs to look like.
We plan to ship the first version by the end of Q1, afterwards we will add more and more features as usual.
Kerberos Open Source (v3) is now available under the MIT license.
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Open source today is a word that often include a lot of things, such as open knowledge (Wikimedia projects), open hardware (Arduino, Raspberry Pi), open formats (ODT/ODS/ODP) and so on.
It is a world of opportunities that can be difficult for newcomers but also for intermediates. This article will help you discover how to approach specific roles, activities or projects/communities in the best way.
I decided to write a book in my personal style about my experience in the last 7 to 8 years in open source. I was surprised when I reached 100 pages about various different topics.
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The second goal was to include my experience but also my philosophy on contributing and how I contribute daily.
Thirdly, I wanted to give a lot of hints and resources and an overall view of this open source world.
Basically, I wanted to write something different from self-help or coaching books that includes just a list of suggestions and best practices. Instead, I take real examples from real life about the OSS world.
As a contributor and developer, I prefer to have real cases to study, because best practices are useful, but we need to learn from others and this world is full of good and bad cases to discover.
In 2019, I started writing a book after Fosdem 2019 and after 2 years inside the Mozilla Reps Council. In that Fosdem edition, I had a talk “Coaching for Open Source Communities 2.0” and after the feedback at the conference and my thoughts in various roles, activities, and projects, it was time to write something.
At the end it wasn’t a manual but a book that included my experience, learnings, best practices and so on in Localization, Development, Project Maintainer, Sysadmin, Community Management, Mentor, Speaker and so on. It contains the following sections:
There are also three appendices that are manuals which I wrote throughout the years and gathered and improved for this book. They are about: community management, public speaking, and mentoring.
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I wrote this book and published in October 2019, but it was only possible with the help of reviews and localizers that improved and contributed. Yes, because this book is open source and free for everyone.
I picked the GPL license because this license changed the world and my life in the best way. Using this license is just a tribute. This decision usually is not clear because after all this is a book and there are better licenses like Creative Commons.
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Learning about Java is no easy feat. It’s a prevalent and in-demand programming language with applications in numerous sectors. We all know that if you want to learn a new skill, the best way to do so is through using it. That’s why we recommend working on projects.
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Over the last few years, Kubernetes have become the de-facto standard for container orchestration and has also won the race against Docker for being the most loved platforms among developers. Released in 2014, Kubernetes has come a long way with currently being used across the entire cloudscape platforms. In fact, recent reports state that out of 109 tools to manage containers, 89% of them are leveraging Kubernetes versions.
Although inspired by Borg, Kubernetes, is an open-source project by Google, and has been donated to a vendor-neutral firm — The Cloud Native Computing Foundation. This could be attributed to Google’s vision of creating a platform that can be used by every firm of the world, including the large tech companies and can host multiple cloud platforms and data centres. The entire reason for handing over the control to CNCF is to develop the platform in the best interest of its users without vendor lock-in.
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