MindsDB
litmus
Our great sponsors
MindsDB | litmus | |
---|---|---|
78 | 63 | |
21,223 | 4,182 | |
5.7% | 2.2% | |
10.0 | 9.4 | |
4 days ago | 9 days ago | |
Python | Go | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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.
MindsDB
-
Whatβs the Difference Between Fine-tuning, Retraining, and RAG?
Check us out on GitHub.
-
How to Forecast Air Temperatures with AI + IoT Sensor Data
If your data lacks uniform time intervals between consecutive entries, QuestDB offers a solution by allowing you to sample your data. After that, MindsDB facilitates creating, training, and deploying your time-series models.
-
Fine-tuning a Mistral Language Model with Anyscale
MindsDB is an open-source AI platform for developers that connects AI/ML models with real-time data. It provides tools and automation to easily build and maintain personalized AI solutions.
- Vanna.ai: Chat with your SQL database
- FLaNK Weekly 08 Jan 2024
-
MindsDB Docker Extension: Build ML powered apps at a much faster pace
MindsDB combines both AI and SQL functions in one; users can create, train, optimize, and deploy ML models without the need for external tools. Data analysts can create and visualize forecasts without having to navigate the complexities of ML pipelines.MindsDB is open-source and works with well-known databases like MySQL, Postgres, Redit, Snowflakes, etc.
-
How Modern SQL Databases Are Changing Web Development - #4 Into the AI Era
Mindsdb is a good example. It abstracts everything related to an AI workflow as "virtual tables". For example, you can import OpenAI API as a "virtual table":
-
ππ 23 issues to grow yourself as an exceptional open-source Python expert π§βπ» π₯
Repo : https://github.com/mindsdb/mindsdb
-
AI-Powered Selection of Asset Management Companies using MindsDB and LlamaIndex
MindsDB is an AI Automation platform for building AI/ML powered features and applications. It works by connecting any data source with any AI/ML model or framework and automating how real-time data flows between them. MindsDB is integrated with LlamaIndex, which makes use of its data framework for connecting custom data sources to large language models. LlamaIndex data ingestion allows you to connect to data sources like PDFβs, webpages, etc., provides data indexing and a query interface that takes input prompts from your data and provides knowledge-augmented responses, thus making it easy to Q&A over documents and webpages.
-
Using Large Language Models inside your database with MindsDB
Now, imagine if you can deploy these highly trained models in your database to get insights, make predictions, understand your users, auto-generate content, and more. MindsDB makes this possible! MindsDB is an open-source AI database middleware that allows you to supercharge your databases by integrating various machine learning (ML) engines.
litmus
-
Building Resilience with Chaos Engineering and Litmus
Litmus, Gremlin, Chaos Mesh, and Chaos Monkey are all popular open-source tools used for chaos engineering. As we will be using AWS cloud infrastructure, we will also explore AWS Fault Injection Simulator (FIS). While they share the same goals of testing and improving the resilience of a system, there are some differences between them. Here are some comparisons:
-
Strategies for Writing More Effective Tests in Golang
This LFX quarter I got to get my hands on LitmusChaos, a CNCF incubating opensource project that dives deep on making cloud-native chaos-engineering accessible to multiple developer personas.
-
Introduction to Chaos Engineering
In 2010 Netflix developed a tool called "Chaos Monkey", whose goal was to randomly take down compute services (such as virtual machines or containers), part of the Netflix production environment, and test the impact on the overall Netflix service experience. In 2011 Netflix released a toolset called "The Simian Army", which added more capabilities to the Chaos Monkey, from reliability, security, and resiliency (i.e., Chaos Kong which simulates an entire AWS region going down). In 2012, Chaos Monkey became an open-source project (under Apache 2.0 license). In 2016, a company called Gremlin released the first "Failure-as-a-Service" platform. In 2017, the LitmusChaos project was announced, which provides chaos jobs in Kubernetes. In 2019, Alibaba Cloud announced ChaosBlade, an open-source Chaos Engineering tool. In 2020, Chaos Mesh 1.0 was announced as generally available, an open-source cloud-native chaos engineering platform. In 2021, AWS announced the general availability of AWS Fault Injection Simulator, a fully managed service to run controlled experiments.
-
Building a More Robust Apache APISIX Ingress Controller With Litmus Chaos
Litmus Chaos is an open-source Chaos Engineering framework that provides an infrastructure experimental framework to validate the stability of controllers and microservices architectures. It can simulate various environments, such as container-level and application-level environments, natural disasters, faults, and upgrades, to understand how the system responds to these changes. The framework can also explore the behavior changes between controllers and applications, and how controllers respond to challenges in specific states. Litmus Chaos offers convenient observability integration capabilities and is highly extensible.
-
Getting the Github Octernship
I am Pratik Singh, a final-year engineering student from Bangalore. I have been alumni of the pilot program of the Github Octernship. Back in 2021, it was called Github Externship. I worked for an organisation LitmusChaos
-
rootly Vs firehydrant, any experience?
https://litmuschaos.io/ (open source)
-
How to Deploy and Scale Strapi on a Kubernetes Cluster 2/2
LitmusChaos, is a platform that helps you to run Chaos Engineering in your cluster to identify weaknesses and improvement opportunities.
-
From KubeCon to my first keynote as a DevRel
When the workshop was over, I headed back to the conference pavilion to attend the LitmusChaos Project Office Hours. These discussion events are great because they allow you to learn more about the project ask questions, meet the maintainers, and learn about new features and upcoming updates.
-
Reliability/chaos engineering tools
I don't have experience with the solutions you mentioned but I'll add one more to your list. It's Litmus which is open source... https://github.com/litmuschaos/litmus
-
Implement DevSecOps to Secure your CI/CD pipeline
Implement Chaos Mesh and Litmus chaos engineering framework to understand the behavior and stability of application in real-world use cases.
What are some alternatives?
tensorflow - An Open Source Machine Learning Framework for Everyone
chaos-mesh - A Chaos Engineering Platform for Kubernetes.
H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
chaosmonkey - Chaos Monkey is a resiliency tool that helps applications tolerate random instance failures.
postgresml - The GPU-powered AI application database. Get your app to market faster using the simplicity of SQL and the latest NLP, ML + LLM models.
aws-fis-templates-cdk - Collection of AWS Fault Injection Simulator (FIS) experiment templates deploy-able via the AWS CDK
CapRover - Scalable PaaS (automated Docker+nginx) - aka Heroku on Steroids
podtato-head - Demo App for TAG App Delivery
scikit-learn - scikit-learn: machine learning in Python
backstage - Backstage is an open platform for building developer portals [Moved to: https://github.com/backstage/backstage]
lightwood - Lightwood is Legos for Machine Learning.
mentoring - π©πΏβππ¨π½βππ©π»βπCNCF Mentoring: LFX Mentorship + Summer of Code