π What is Karpor?
Today we are excited to announce that Karpor is now open-source! πππ
Karpor is a Modern Kubernetes Visualization Tool. Its core features focus on π Search, π Insight and β¨ AI. The goal is to connect platforms and multi-clusters more easily and quickly, and use AI to empower Kubernetes to extract key insights from proliferations of cluster resources and provide them to end users.
Karpor is designed to reduce the complexity to use Kubernetes, so that developers and platform teams can extract the most valuable information more effectively and intuitively.
GithubοΌ
https://github.com/KusionStack/karpor
π Why Karpor?
The increasing complexity of the Kubernetes ecosystem is an undeniable trend that is becoming more and more difficult to manage. This complexity not only entails a heavier burden on operations and maintenance but also slows down the adoption of new technologies by users, limiting their ability to fully leverage the potential of Kubernetes.
As an experienced Kubernetes YAML Engineer, you may have also encountered the following perplexities:
- The cluster is like a black box, sometimes all you can see is a KubeConfig, and we can't see what happens behind it
- The team/company has a specific business domain model and needs to establish a mapping between existing systems and Kubernetes resources
- The application has been deployed to multiple Kubernetes clusters, but its topology is not fully visible
We have used several Kubernetes visualization tools over time, such as Lens, k9s, kube-explorer, and the kubernetes dashboard, among others. Some are commercialized, some do not support self-host, and some are rudimentary for production needs... In short, We have not yet encountered a product that completely satisfied with.
The recent rise of large language models has sparked an unprecedented wave of artificial intelligence innovations. This time, AI technology has remarkly infiltrated its way into people's everyday life. Even my retired parents has started using AI services, which makes me believe that we are at a historical moment that is reshaping the world.
So naturally we started building a lightweight, AI-empowered Kubernetes visualization tool to solve the problems mentioned earlier. It features the following:
- Fully empowers Kubernetes with AI.
- Identify potential risks and provide solutions based on AI.
- Intuitive and effective search, providing a number of user-friendly ways to locate resources across clusters, such as keywords, SQL, and natural language.
- Customized logical views to fit the resource organization models for different scenarios, such as applications, environments, etc, which may have different interpretations at places.
- Travel back in time via timeline, time machine to quickly diagnose and troubleshoot based on historical snapshots.
- Cross-cluster topological views, providing a global perspective of resources no matter where they are.
- Low cognitive burden, it is read-only, non-invasive to the cluster it's watching, and users can deploy it to their private environments with one click.
We have named this tool Karpor. In general, we wish Karpor to focus on π search, π insights, and β¨ AI, to break through the increasingly complex maze of Kubernetes, achieving the following value proposition:
As of today, we have built the initial version of Karpor based on this vision, which features the following:
- An optimized search experience for Kubernetes:
- Discover potential problems through compliance reports:
- Manage the customized logical views:
π Karpor vs. Kubernetes Dashboard
In today's Kubernetes ecosystem, there are multiple tools and platforms that can manage and visualize clusters. Kubernetes Dashboard is an officially provided universal web UI for managing and troubleshooting Kubernetes clusters. Karpor, as an emerging Kubernetes Visualization Tool, is designed to provide more advanced features and a better user experience.
Here are some key comparisons between Karpor and Kubernetes Dashboard:
π οΈVision: Embracing the Community
We firmly believe that a successful open-source project should be community-driven. For open-source projects, we come up with an idea and build an initial version. The final form of the project, we believe, should be well guided by the community.
Therefore, we are committed to shaping Karpor into something that is:
- Small and beautiful: Focused on an excellence of user experience.
- Vendor-neutral: Independent from any specific cloud services or companies.
- Developer-friendly: Community-friendly with high-quality documentations and support.
- Community-driven: Encouraging and welcoming contributors to participate in and even lead the development of the project.
We place great emphasis on community participation and contribution. To this end, we have specially put together a community task list to help those that are interested quickly get started and participate in the project. The tasks are categorized by difficulty, ranging from simple tasks such as document translation, bug fixes, and unit testing, to medium-difficulty tasks like log/event aggregators, risk audit enhancements, and automatic cluster imports, to challenging tasks such as OpenCost integration and login authentication.
We encourage every developer interested in Karpor to visit our GitHub page, review the task list, and contribute at ease.
ποΈ Community Task List: https://github.com/KusionStack/karpor/issues/463
All developers who participate in the community will be featured in the Contributors section on the README and the homepage of the official website. We extend our sincerest thanks to all developers and contributors who are already active in the Karpor open-source project, for your efforts and creativity! We look forward to working with the community to make Karpor an even more powerful and comprehensive open-source tool.
π Moving Forward
We are actively soliciting feedback and suggestions from the community to plan the next version of Karpor β v0.5. We want to hear your voice, whether it's feature requests, improvement suggestions, or bug reports; please leave a comment in the corresponding issue.
Our ultimate goal is to shape Karpor into a community-driven Kubernetes Visualization Tool in the AI era. Currently, what we have is a usable version with basic functionalities.
In the next version, we will solidify the basic functionalities and fully embrace AI. We have preliminarily planned some new features, such as support for natural language search of cluster resources, AI-driven diagnostic suggestions, timelines, etc., to help users better understand resources in multiple clusters, identify issues, and troubleshoot. We welcome everyone's feedback!
If you like this project, welcome to Star on GitHub πππ
Top comments (1)
Karpor looks good and promising. I would like to try it out and contribute. Is there any group I can join