What is Bitdribble?
Bitdribble implements distributed agents for dev/ops and IoT. Bitdribble agents can be configured to run modular tasks to measure device, service, network performance and report measurements to back-end databases like Graphite or InfluxDB. Data can be visualized with Grafana or other similar dashboarding solutions.
How is Bitdribble different from other dev/ops tools?
Bitdribble brings the intelligence to the agents - to the edge.
The agent tasks are configured into flows, where the output of a task instance becomes the input of one or more other task instances, with the terminating task instance having the ability to send task instance output to an external database. Other similar dev/ops tools report data to a back end but generally do processing and filtering of data on the back end.
Where is the code?
Code and documentation are available on Github under an Apache version 2 license. Bitdribble provides installation consulting services and support.
Contact
Andrei Radulescu-Banu can be reached at andrei[at]bitdribble.com, on Linked-in and Twitter.
Andrei's posts on Medium:
- TechStars Meet&Greet (Sept 2018)
- Before the Pitch - at StartUp Boston (Sept 2018)
- When & Where - at StartUp Boston (Sept 2018)
Other things I read, watch or listen:
- Self Driving Cars
- Sertac Karaman (MIT, Optimus Ride) on Motion Planning in a Complex World (2018). Describes the MIT entry at the 2007 DARPA Challenge.
- Cognitive Robotics, 16.412J/6.836J MIT Open Courseware (Spring 2016)
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Books
- Probabilistic Robots, by Thurn, Burgard, Fox (2005)
- Programming Robots with ROS: A Practical Introduction to the Robot Operating System, by Quigley, Gerkey, Smart (2015)
- Self-Driving Cars with ROS and Autoware by APEX.ai, 20 classes YouTube Course (2020)
- Market Trading
- Algorithmic Trading & DMA by Barry Johnson (2010), reviewed by Scott C. Locklin
- Inside the black box, by Rishi K. Narang (2009)
- The Truth About High-Frequency Trading: What Is It, How Does It Work, and Is It a Problem?, by Rishi K. Narang (2014), reviewed
- Algorithmic and High-Frequency Trading by Cartea, Jaimungal, and Penalva, Cambridge, 2015
- MIT course 15.487 Algorithmic Trading and Quantitative Investment Strategies syllabus (Spring 2017)
- All about hedge funds, by Ezra Zask (2nd edition, 2013)
- Active Portfolio Management, by Grinold and Kahn (2000), reviewed by Scott C. Locklin. A follow-up was published in 2019.
- Trading and Exchanges, by Larry Harris (2002)
- Modern Portfolio Theory and Investment Analysis, by Elton, Gruber et. al.
- Investments, by Bodie, Kane and Marcus
- Finance Theory I, by Andrew Lo, MIT open courseware
- Data Mining, by Witten and Frank
- Python for Data Analysis, by McKinney
- MIT IAP 2020: The business of quant: Lecture 1 2 3 4, by Rohit Singh
- Value and Utility Functions, lecture slides from Darthmouth ENGS41 class
- Medium.com: Trade Sizing & Kelly Fraction I, I, III, by Joshua Greenwald
- Podcasts at chatwithtraders.com
- EP 054: Components of a black box, humans versus computers, and high frequency trading w/ @RishiKNarang
- EP 118: Trading technology, alternative data, and originality w/ Manoj Narang
- EP 170: The technology edge - how a team of options market makers found success in Asia w/ Joshua Greenwald
- EP 178: Create a Simple Trend Following System - Nick Radge
- EP 77: How to be a profitable short-term trader in a high frequency world - Dennis Dick
- Probabilities and Statistics
- MIT course 14.30 Intro to Statistical Methods in Economics
- Theory of Financial Risk and Derivative Pricing: From Statistical Physics to Risk Management, by Jean-Philippe Bouchaud & Marc Potters (2011)
- Entrepreneurship
- Podcasts at angelinvestboston.com with leading Boston angel investors. See the Ben Littauer and Christopher Mirabile episodes.
- The Seraf Investor blog
- The Seven Deadly Sins of Product-Driven Founders, by Parul Singh (Sept 2018)
- Patrick Campbell's blog on freemium, SAAS revenue, marketing and sales strategy. If Patrick was not running a business, he could be an economics professor.
- DevOps
- The Open Source Guide to DevOps Monitoring Tools, by Dan Barker (Sept 2018)
- Open Source
- CMake Tutorial, by Onur Dündar (Feb 2018)
- How to write CMake platform checks (accessed Oct 2018)
- C/C++ tip: How to detect the operating system type using compiler predefined macros (accessed Oct 2018)
- C/C++ tip: How to detect the compiler name and version using compiler predefined macros (accessed Oct 2018)
- C/C++ tip: How to detect the processor type using compiler predefined macros (accessed Oct 2018)
- C/C++ tip: How to list compiler predefined macros (accessed Oct 2018)
- Network tools
- Socat, by Cindy Sridharan (Oct 15, 2018). Anything by Cindy Sridharan is great. She writes about dev/ops, metrics monitoring, logs and distributed event monitoring with open source tools.
- Embedded Programming
- Raspbian "stretch" for Raspberry Pi 3 on QEMU, by Wim Vanderbauwhede (accessed Oct 2018)
- Writing Documentation
- Which tool to choose for API docs, by Tom Johnson (accessed Oct 2018)