jupyter-renderers VS jupyter2kibana

Compare jupyter-renderers vs jupyter2kibana and see what are their differences.

jupyter2kibana

A Workflow for Data Scientists to bring Jupyter Notebook Visualizations to Kibana Dashboards (by walterra)
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jupyter-renderers jupyter2kibana
1 4
485 42
1.0% -
5.2 0.0
about 1 month ago over 1 year ago
HTML Jupyter Notebook
BSD 3-clause "New" or "Revised" License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

jupyter-renderers

Posts with mentions or reviews of jupyter-renderers. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-26.

jupyter2kibana

Posts with mentions or reviews of jupyter2kibana. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-09.
  • Outlining the pros and cons of threat hunting labs and threat sim frameworks on a hobbyist budget.
    1 project | /r/AskNetsec | 10 Apr 2022
    For context, if you didn't read the linked post, our team uses ELK stack as our SIEM, and a few of us wanted to set up a test lab to practice threat hunting on ELK. And we needed to do it on a Hobbyist budget. And we wanted to apply the data-science (inspired by this) strengths of Jupyter to our hunting workflow, since all of us already know Python.
  • Anyone have experience building a Windows AD lab environment in Docker?
    5 projects | /r/docker | 9 Apr 2022
    Big picture: We want to work out an in-depth ELK workflow and develop some threat hunting automation. I found that a small ELK stack is hosted for a very reasonable price ($0.0263/hr for a small stack w/ 45GB storage as of today). And a CoCalc instance (collaborative cloud-hosted JupyterLab) costs another $6 per month. So between those two low-cost resources we've figured out a pretty neat Python -> Vega -> Kibana workflow to apply some data science and visualization to our threat-hunting workflow (after some trouble).
  • Python (Jupyter) -> Vega -> Kibana?
    1 project | /r/elasticsearch | 7 Apr 2022
    Here's the example referred to as well as the overarching project which inspired us to try this.
  • Resources
    1 project | dev.to | 2 Aug 2021
    Elastic Eland (Python Elasticsearch client for exploring and analyzing data in Elasticsearch)

What are some alternatives?

When comparing jupyter-renderers and jupyter2kibana you can also consider the following projects:

ibus - Intelligent Input Bus for Linux/Unix

HELK - The Hunting ELK

latex-input - Enter Unicode characters using LaTeX notation

nbdev - Create delightful software with Jupyter Notebooks

MathJax-src - MathJax source code for version 3 and beyond

invoke-atomicredteam - Invoke-AtomicRedTeam is a PowerShell module to execute tests as defined in the [atomics folder](https://github.com/redcanaryco/atomic-red-team/tree/master/atomics) of Red Canary's Atomic Red Team project.

dash-sample-apps - Open-source demos hosted on Dash Gallery

fastpages - An easy to use blogging platform, with enhanced support for Jupyter Notebooks.

jupyterlab-classic - JupyterLab distribution with a retro look and feel 🌅

PurpleCloud - A little tool to play with Azure Identity - Azure Active Directory lab creation tool

espanso-mega-pack - A collection of curated home built packages for the cross-platform text expander Espanso

espanso - Cross-platform Text Expander written in Rust