DEV Community: Chris Churilo

Comparing Observability tools

Chris Churilo — Thu, 02 Oct 2025 22:28:40 +0000

As cloud-native environments continue to grow in complexity, observability has become essential for ensuring the reliability, performance, and scalability of modern applications. From monitoring infrastructure health, enabling deep visibility into distributed systems, or getting real-time insights into reasoning paths, token usage of LLM Agentic applications. However, traditional vendors sliced visibility into separate products (APM, Log Management, Infrastructure Monitoring, LLM Observability) and priced them in ways that forced tradeoffs making it important for team to choosing the right observability platform is critical to operational success.

Some simple comparisons of some popular Observability tool that breaks down their strengths, pricing models, and trade-offs to help teams choose the right observability platform for their priorities—whether that’s cost efficiency, deployment flexibility, or depth of insights.

[Datadog vs Dynatrace](https://www.groundcover.com/comparison/datadog-vs-dynatrace)

[Grafana vs New Relic](https://www.groundcover.com/comparison/new-relic-vs-grafana-cloud)

[Dynatrace vs New Relic](https://www.groundcover.com/comparison/new-relic-vs-dynatrace)

[Grafana vs Datadog](https://www.groundcover.com/comparison/datadog-vs-grafana-cloud)

[New Relic vs Datadog](https://www.groundcover.com/comparison/datadog-vs-new-relic)

8 new RAG tutorials with the Voyage-3-Lite ML model

Chris Churilo — Thu, 27 Feb 2025 19:31:22 +0000

From Code Confusion to Coding Confidence

Have you ever stared at your screen, cursor blinking accusingly in a sea of syntax you barely understand? You're not alone. Who hasn't been lost in a maze of brackets, semi-colons, and error messages that seemed written in hieroglyphics?

This post is for those of you who are just starting out, who feel overwhelmed by the mountain of knowledge ahead, and who wonder if you'll ever reach that magical moment when coding finally "clicks."

Here are Eight RAG Tutorials using Milvus, Langchain, and the Voyage-3-lite model to get your started before you decide to throw your laptop out the window. Whether you're learning your first language, building your first project, or recovering from your first (of many) debugging rabbit holes, I've been there. Let's navigate this journey together with some cool tutorials!

Number Eight

LangChain, Milvus, Anthropic Claude 3.5 Haiku, and voyage-3-lite
Anthropic Claude 3.5 Haiku: This model builds upon Claude 3's capabilities with enhanced understanding and generation of nuanced language. It excels in creative writing, conversational AI, and complex query handling. Best suited for tasks where clarity and depth of response are paramount, Claude 3.5 balances efficiency with sophisticated insights.

Number Seven

LangChain, Milvus, Cohere Command R, and voyage-3-lite
Cohere Command R: This model is designed for high-performance retrieval tasks, offering advanced capabilities in understanding and generating natural language. Its strengths lie in semantic search and document summarization, making it ideal for applications such as customer support, content generation, and knowledge management, where accuracy and context relevance are paramount.

Number Six

LangChain, Milvus, Mistral AI Mistral Nemo, and voyage-3-lite
Mistral AI Mistral Nemo: This model is designed for high-performance natural language processing, emphasizing interpretability and adaptability. It excels in tasks involving text generation, dialogue systems, and content creation. Ideal for industries like marketing and entertainment, Mistral Nemo delivers rich, coherent narratives while allowing for fine-tuning to specific domain requirements.

Number Five

LangChain, Milvus, OpenAI GPT-4, and voyage-3-lite
OpenAI GPT-4: GPT-4 is OpenAI's advanced language model, designed for comprehensive understanding and context-aware text generation. It excels in creative writing, complex problem-solving, and nuanced conversation, making it suitable for applications in content creation, tutoring, and interactive AI. Its robust capabilities enable it to handle a wide range of topics with depth and coherence.

Number Four

LangChain, Milvus, Anthropic Claude 3.5 Sonnet, and voyage-3-lite
Anthropic Claude 3.5 Sonnet: This advanced model in the Claude 3 family is designed for nuanced understanding and creative language generation. With enhanced prompt comprehension and contextual awareness, it excels in complex dialogue, creative writing, and sophisticated content creation. Ideal for applications where deep engagement and high-quality output are paramount.

Number Three

LangChain, Milvus, Mistral AI Mistral Large, and voyage-3-lite
Mistral AI Mistral Large: This model offers a high-performance solution for a range of natural language processing tasks. With a focus on large-scale text generation and comprehension, it excels in handling complex queries and generating nuanced responses. Ideal for applications in content creation, conversational agents, and research analysis, Mistral Large combines versatility with efficiency.

Number Two

LangChain, Milvus, Mistral AI Pixtral, and voyage-3-lite
Mistral AI Pixtral: Pixtral is a cutting-edge image generation model designed for high-quality visual content creation. With a focus on artistic style transfer and detail accuracy, it excels in transforming text prompts into vibrant images. Ideal for applications in design, marketing, and creative fields, Pixtral enhances workflows with its versatility and aesthetic precision.

And, last but not least

Number One

LangChain, Milvus, OpenAI GPT-4o, and voyage-3-lite
OpenAI GPT-4o: This advanced model from OpenAI focuses on generating highly coherent and contextually relevant text. With enhanced understanding of nuanced language, it excels in creative writing, conversational agents, and educational content. Ideal for applications needing in-depth responses and creativity, GPT-4o offers versatility across various industries

Milvus Adventures November 15, 2024

Chris Churilo — Fri, 15 Nov 2024 15:57:31 +0000

We have started a weekly Office Hours where you can schedule some time with our DevRel and Engineering team members to get our Milvus questions answered!

COMMUNITY

We had some fun at our meetups recently and there still is one more next week in San Francisco. But we always record a past sessions, so come check them out!

Nov 19, 2024 | Unstructured Data San Francisco Meetup Register
- Hakan Tekgul, Evaluating RAG pipelines built on unstructured data
- James Luan, Dense Embeddings != Complete Search - a sneak peak of Milvus 2.5
- Max Mathys, Gandalf: Insights from the World's Largest Red Team

Hot Topics

What is GraphRAG? | Microsoft's GraphRAG advances traditional RAG architectures by leveraging graph databases to create more intelligent, context-aware search and retrieval systems for large language models.
Similarity Metrics | Cosine similarity, a key metric for measuring how closely two vectors match, helps power modern search systems by finding the most relevant results based on semantic meaning rather than exact matches.
Llama 3.2 function calling | Llama 3.2 introduces native function calling capabilities, allowing developers to define and trigger specific actions directly through the model's output—similar to GPT's function calling but now available in open source.
text-embedding-3-small model | The text-embedding-3-small model delivers improved embedding quality at lower latency and cost, making it ideal for production vector search applications.
Class activation maps | Class activation maps visualize which regions of an image influenced a neural network's decision, helping developers understand and debug computer vision models.
Convolutional neural network | Convolutional neural networks process images by applying filters that detect patterns and features, forming the backbone of modern computer vision applications from facial recognition to medical imaging.
knn algorithm in machine learning K-Nearest Neighbors (KNN) | The K-Nearest Neighbors (KNN) algorithm classifies data points by finding their closest matches in your training data, making it an intuitive yet powerful approach for tasks like recommendation systems and anomaly detection.
Vector database benchmarks | VectorDBBench provides standardized performance metrics across vector databases, measuring critical factors like query latency, throughput, and recall to help teams make data-driven infrastructure decisions.

GITHUB REPOS

Milvus Milvus is an open-source vector database built to power embedding similarity search and AI applications.

Akcio: Enhancing LLM-Powered ChatBot with CVP Stack A full chatbot app all open-source for you to try out for your self!

GPT Cache. GPTCache is an open-source tool designed to improve the efficiency and speed of GPT-based applications by implementing a cache to store the responses generated by language models.

VectorDBBench. VectorDBBench is an open-source benchmarking tool to help you evaluate the performance of mainstream vector databases and cloud services with yoru specific use case.

Milvus Adventures October 25, 2024

Chris Churilo — Fri, 25 Oct 2024 16:05:39 +0000

I have been a little absent on this newsletter of late. Sorry! So many fun things going on! We have been busy building a lot of notebooks, demos, and tutorials along with the regularly scheduled blogs! Of, let's get this rolling!

COMMUNITY

The Next set of Meetups!

Nov 13, 2024 | Unstructured Data South Bay Meetup Register
- TBD - Stefan Webb
- Dinesh Chandrasekhar, Challenges in Structured Document Data Extraction at Scale with LLMs
Nov 14, 2024 | Unstructured Data Berlin Meetup Register
- TBD - Stephen Batifol, Zilliz
- LLM Agent Observability: Lessons Learned from Real-World Applications - Dat Ngo, Arize
- Structuring Unstructured Text using generative AI: The key to information extraction - Oren Matar, Anaplan
Nov 21, 2024 | Unstructured Data NYC Meetup Register
- 6:00 - 6:30 - Tim Spann, Principal DevRel, Zilliz
- 6:30 - 7:15 - David K, DevRel, StreamNative
- 7:15 - 8:00 - Ravi, Tecton AI, VP of Engineering
Nov 19, 2024 | Unstructured Data SF Meetup Register
- John Gilhuly, DevRel, Arize
- TBD - Stefan Webb
- Talk 3 TBD

Recaps

Oct 8 SF TechWeek Data & AI Edition Watch now
South Bay Unstructured Data Meetup Oct 15 2024 Watch now
NYC Unstructured Data Meetup Oct 23 2024 Watch now

Learn about Graph RAG

What is GraphRAG? | Unlike a baseline RAG that uses a vector database to retrieve semantically similar text, GraphRAG enhances RAG by incorporating knowledge graphs (KGs). Knowledge graphs are data structures that store and link related or unrelated data based on their relationships.
Graph database vs a Vector database | Compare vector and graph databases, helping you understand their fundamental differences, strengths, and ideal applications.
Knowledge Graph RAG LLM | Get an overview of Knowledge Graphs, RAG, and how to integrate knowledge graphs into RAG systems for better performance.
GraphRAG Neo4j | This blog post details how to build a GraphRAG agent using the Neo4j graph database and Milvus vector database. This agent combines the power of graph databases and vector search to provide accurate and relevant answers to user queries. In this example, we will use LangGraph, Llama 3.1 8B with Ollama and GPT-4o.

Learn more!

GITHUB REPOS

Milvus Milvus is an open-source vector database built to power embedding similarity search and AI applications.

Akcio: Enhancing LLM-Powered ChatBot with CVP Stack A full chatbot app all open-source for you to try out for your self!

GPT Cache. GPTCache is an open-source tool designed to improve the efficiency and speed of GPT-based applications by implementing a cache to store the responses generated by language models.

VectorDBBench. VectorDBBench is an open-source benchmarking tool to help you evaluate the performance of mainstream vector databases and cloud services with yoru specific use case.

Milvus Adventures August 19, 2024

Chris Churilo — Mon, 19 Aug 2024 18:38:17 +0000

COMMUNITY

Our VP of Engineering, James Luan will be speaking at the Data for AI Meetup on August 29, 2024 at Microsoft Reactor in SF. You can also get a head start on the September meetups:

Sept 5, 2024 | Unstructured Data Berlin Meetup Register
- Multi Agent Systems with Mistral AI, Milvus and llama-agents - Stephen Batifol, Zilliz
- Meghana Satish, GetYourGuide
- Wang Bo, Jina AI
Sept 9, 2024 | Unstructured Data SF Meetup Register
- Christopher Nguyen, CEO, Aitomatic
- Zhuo Li, CEO, Hyrdox.ai
- Amit Sangani, Senior Director, Meta
- (Lightning Talk) Jed Pitera, Strategy Co-lead, Sustainable Materials, IBM
Sept 17, 2024 | Unstructured Data South Bay Meetup Register
- Yi Ding, formerly of LlamaIndex
- Kunal Sonalkar, Data Scientist, Nordstrom
- Hakan Tekgul, Solutions Architect, Arize
Sept 18, 2024 | Unstructured Data South Bay Meetup Register
- David, DevRel, StreamNative
- Tim Spann, Principal DevRel, Zilliz
- Unstract

Learn about Natural Language Processing (NLP)

ColBERT Embedding Model | Master ColBERT: Boost your search capabilities with this powerful token-level model.
NLP Beginner Guide | Jumpstart your NLP journey with Zilliz Cloud's embedding tools.
NLP Technologies | Track the evolution of NLP in deep learning - stay ahead of the curve.
NLP Datasets | Find the best datasets for your NLP projects.
Top NLP Tools | Supercharge your ML apps with top NLP tools and platforms.
NLP Basics | Grasp key NLP concepts: tokens, n-grams, and bag-of-words models explained.
NLP Applications | See NLP in action: from chatbots to transcription services.
NLP Models | Discover the NLP models powering modern ML applications
Transformers in AI | Unlock the power of transformer models in NLP.
NLP and Vector DB | Combine NLP and vector databases for advanced data processing.
Neural Networks NLP | Explore how neural networks and embeddings shape language models.
OpenAI Embeddings | Create powerful embeddings with OpenAI models for NLP apps.

Large Language Models

LLMs and Search | See how large language models are revolutionizing search tech.
What Are LLMs? | Get the lowdown on large language models and their real-world uses.
Top LLMs 2024 | Stay current: Learn about 2024's most influential language models.
Prompt Engineering | Master prompt engineering for better NLP and AI outcomes.
ChatGPT with LangChain | Boost ChatGPT with LangChain and Milvus - a developer's guide.

GITHUB REPOS

Milvus Milvus is an open-source vector database built to power embedding similarity search and AI applications.

Akcio: Enhancing LLM-Powered ChatBot with CVP Stack A full chatbot app all open-source for you to try out for your self!

GPT Cache. GPTCache is an open-source tool designed to improve the efficiency and speed of GPT-based applications by implementing a cache to store the responses generated by language models.

VectorDBBench. VectorDBBench is an open-source benchmarking tool to help you evaluate the performance of mainstream vector databases and cloud services with yoru specific use case.

Milvus Adventures August 14, 2024

Chris Churilo — Wed, 14 Aug 2024 21:28:29 +0000

COMMUNITY

Bussin' summer indeed! We have had a lot of legit talks from so many people representing some cool GenAI projects. If you are feeling FOMO, you should! But we got you covered because all the talks are recorded for you viewing pleasure.

Unstructured Data SF Meetup video
- Tim Spann, Principal DevRel, Zilliz
- Bill Reynolds, CTO, Quarbine
- Corey Nolet, Principal Engineer, NVIDIA
- Jacob Marks, Senior Machine Learning Engineer and Researcher, Voxel51
Unstructured Data Palo Alto Meetup video
- James Le, Head of Developer Experience, TwelveLabs
- Bill Zhang, Software Engineer, Zilliz
- Sriharsha Yayi (Senior Product Manager) & Derek Wang (Principal Software Engineer), Intuit
Unstructured Data NYC Meetup video
- Charles Xie, CEO, Zilliz
- Robertson Taylor, Solutions Engineer, marqo.ai
- Aamir Shakir, Co-founder, mixedbread.ai

Get stuck in on Multimodal RAG

Vanilla RAG is so 2023. We are getting hyped on Multimodl RAG this summer!

Gemini RAG Building a Multimodal RAG with Gemini 1.5, BGE-M3, Milvus Lite, and LangChain
Clip and Llama3 RAG Build a multimodal RAG locally with CLIP and Llama3
What is Multimodal Retrieval-Augmented Generation (RAG)
Build Better Multimodal RAG Pipelines with FiftyOne, LlamaIndex, and Milvus
Exploring OpenAI CLIP: The Future of Multi-Modal AI Learning

Vector Embedding, the magic behind vector search

You probably heard about how vector embeddings can be used for Semantic Similarity Search, but let's go a little deeper and learn more about how these arrays of numbers achieve their super power!

Vector Index basic

GITHUB REPOS

Milvus Milvus is an open-source vector database built to power embedding similarity search and AI applications.

Akcio: Enhancing LLM-Powered ChatBot with CVP Stack A full chatbot app all open-source for you to try out for your self!

GPT Cache. GPTCache is an open-source tool designed to improve the efficiency and speed of GPT-based applications by implementing a cache to store the responses generated by language models.

VectorDBBench. VectorDBBench is an open-source benchmarking tool to help you evaluate the performance of mainstream vector databases and cloud services with yoru specific use case.

Milvus Adventures August 7, 2024

Chris Churilo — Wed, 07 Aug 2024 20:39:36 +0000

COMMUNITY

I can't believe that we just had another full house at the Unstructured Data meetup in San Francisco, with our lovely hosts, Github! Palo Alto and NYC are next week so there is plenty of time to register and join us in person. Or, if you would like to give a talk, let us know!

Unstructured Data SF Meetup video
Unstructured Data Palo Alto Meetup register
Unstructured Data NYCMeetup register

Learn About Gen AI

Explore the cutting edge of Generative AI (GenAI) and its impact on software development. From code generation to automated testing, GenAI is transforming how we build and maintain applications. Discover key frameworks, best practices, and potential pitfalls when integrating GenAI into your development workflow. Stay ahead of the curve and learn how to leverage this powerful technology in your projects.

Get Started with LangChain

LangChain is a powerful framework for building language model applications. Learn how to quickly create chatbots, question-answering systems, and other NLP-driven tools using LangChain's intuitive APIs. We'll cover key concepts, basic setup, and practical examples to help you integrate large language models into your projects efficiently. Unlock the potential of AI in your applications with LangChain.

Building an Open Source Chatbot with Milvus
Self Querying in LangChain
Build RAG with Langchain and Notion
Experimenting with different LangChain Chunking Strategies
LangChain Prompts
Advanced Langchain
Combine Langchain Multiple Documents
Getting Started with Langchain
Connecting to Milvus with LangChain
Intro to LangChain
LangChain Integration

GITHUB REPOS

Milvus Milvus is an open-source vector database built to power embedding similarity search and AI applications.

Akcio: Enhancing LLM-Powered ChatBot with CVP Stack A full chatbot app all open-source for you to try out for your self!

GPT Cache. GPTCache is an open-source tool designed to improve the efficiency and speed of GPT-based applications by implementing a cache to store the responses generated by language models.

VectorDBBench. VectorDBBench is an open-source benchmarking tool to help you evaluate the performance of mainstream vector databases and cloud services with yoru specific use case.

Milvus Adventures July 29, 2024

Chris Churilo — Mon, 29 Jul 2024 19:02:31 +0000

COMMUNITY

We had so much fun at the meetup this week in Palo Ato and can't wait to see you all again next month. We haven't had the chance to upload the video, yet, however, the Berlin and SF videos are up for your viewing pleasure.

Unstructured Data SF Meetup video
Unstructured Data Berlin Meetup video

Learn About Vector Databases

There are so many databases with Vector Search capabilities that it can be overwhelming to know where to start! This week, let's focus on learning about similarity metrics, the diffrence between sparse and dense vectors and get our hands dirty with some hands-on tutorials.

Similarity Metrics for Vector Search like Euclidean distance or cosine similarity are used to measure how closely vectors relate to each other in high-dimensional space. Choosing an appropriate metric is crucial, as it can significantly enhance the performance of machine learning tasks such as classification and clustering.
Getting Started: Pgvector Guide for Developers Exploring Vector Databases. If you are a postgres fan, you can build a little prototype with PGVector.
Beginner Guide to Implementing Vector Databases, including key considerations and steps to get started with a vector database and implementation best practices.

Get Started with Milvus

Milvus is an open source vector database that is a popular choice for builing all kinds of AI applications.

Getting Started with a Milvus Connection. It comes with everything you need to get started built right in, and runs on your local machine.
JSON Metadata Filtering in Milvus is useful when you want to use data other than vectors to fine tune your search results.
Hybrid Search with Milvus is another example of using different kinds of vectors and meta data to get the best search results.
Multimodal RAG with CLIP, Llama3, and Milvus is all the rage! Try this tutorial to see they power of multi-modal search.

Vector Embeddings

In general, there are two types of vectors: dense vectors and sparse vectors. While they can be utilized for similar tasks, each has advantages and disadvantages.

You can also train your own models, learn more about sentence transformers and even give time series embedding a go!

Vector Indexes

Most vector search solutions rely on HNSW, but there are many other vector indexes and understanding the differences will help you create a performant and cost effective AI application. Here are two that you might not have heard about yet:

Learn RAG

Chunking Strategies

Optimizing your RAG applications

GITHUB REPOS

Milvus Milvus is an open-source vector database built to power embedding similarity search and AI applications.

Akcio: Enhancing LLM-Powered ChatBot with CVP Stack A full chatbot app all open-source for you to try out for your self!

GPT Cache. GPTCache is an open-source tool designed to improve the efficiency and speed of GPT-based applications by implementing a cache to store the responses generated by language models.

VectorDBBench. VectorDBBench is an open-source benchmarking tool to help you evaluate the performance of mainstream vector databases and cloud services with yoru specific use case.

Milvus Adventures July 20, 2024

Chris Churilo — Sat, 20 Jul 2024 20:35:30 +0000

COMMUNITY

Join us at our next one in Palo Alto is on July 23, 2024. Please register early because they fill up fast! We will be joined by

Oz Wasserman, Founder, Opsin
Manasi Joglekar, Software Engineer, SAP
Frank Liu, Head of AI/ML, Zilliz

If you can't make it in person, join the Twitch channel or take a look at all of the recordings from all of our locations!

Learn About Vector Databases

There is so much to learn in AI, so let's start with gaining a solid understanding of what is a Vector Database! You might think that any database can be a vector database, but the reality is that all those other databases only support simple vector search. Vector database are sophiticated systems that need to provide support to a number of use cases and their unique requirements. You can also take a look at this page of comparisons of open source vector databases.

Vector Search

Vector Embeddings

Machine learning models are used to convert your unstructured data into vector embeddings! It is good to learn about vector embeddings to get the most of your retrieval results!

Vector Indexes

Most databases have support for 1 or 2 indexes, but Milvus has 15 different vector indexes. This wide range of indexes is important because the uses cases with vector search have different requirements!

Advanced Topics

Learn RAG

Retrieval Augmented Generation (RAG)

GITHUB REPOS

Milvus Milvus is an open-source vector database built to power embedding similarity search and AI applications.

Akcio: Enhancing LLM-Powered ChatBot with CVP Stack A full chatbot app all open-source for you to try out for your self!

GPT Cache. GPTCache is an open-source tool designed to improve the efficiency and speed of GPT-based applications by implementing a cache to store the responses generated by language models.

VectorDBBench. VectorDBBench is an open-source benchmarking tool to help you evaluate the performance of mainstream vector databases and cloud services with yoru specific use case.

#Milvus Adventures July 12, 2024

Chris Churilo — Fri, 12 Jul 2024 15:50:35 +0000

COMMUNITY

Join us at our next one in San Francisco is on July 16, 2024. Please register early because they fill up fast! We will be joined by

Alexandre Bonnet, Lead ML Solutions Engineer, Encord
Joe Maionchi, VP R&D, and Hendrik Krack, Developer Advocate, Aparavi
Frank Liu, Head of AI/ML, Zilliz

If you can't make it in person, join the Twitch channel or take a look at all of the recordings from all of our locations!

Tutorials with Milvus Lite

Milvus Lite, a lightweight vector database that runs locally within your Python application. Based on the popular open-source Milvus vector database, Milvus Lite reuses the core components for vector indexing and query parsing while removing elements designed for high scalability in distributed systems.

ARTICLES

Retrieval Augmented Generation (RAG)

GITHUB REPOS

Milvus Milvus is an open-source vector database built to power embedding similarity search and AI applications.

Akcio: Enhancing LLM-Powered ChatBot with CVP Stack A full chatbot app all open-source for you to try out for your self!

GPT Cache. GPTCache is an open-source tool designed to improve the efficiency and speed of GPT-based applications by implementing a cache to store the responses generated by language models.

VectorDBBench. VectorDBBench is an open-source benchmarking tool to help you evaluate the performance of mainstream vector databases and cloud services with yoru specific use case.

Simplifying the Milvus Selection Process

Chris Churilo — Tue, 20 Feb 2024 05:16:26 +0000

Selecting the right version of open-source Milvus is important to the success of any project leveraging vector search technology. With Milvus offering different versions of its vector database tailored to varying requirements, understanding the significance of selecting the correct version is key for achieving desired outcomes.

The appropriate Milvus version can expedite learning and prototyping or optimize resource utilization, streamline development efforts, and ensure compatibility with existing infrastructure and tools. Ultimately, it's about enhancing developer productivity and improving efficiency, reliability, and user satisfaction.

Available Milvus Versions:

Milvus Lite

As its name suggests, Milvus Lite is a lightweight version designed to seamlessly integrate with Google Colab and Jupyter Notebook. Packaged as a single binary with no additional dependencies, Milvus Lite is easy to install and run on your machine or embed in Python applications. With a CLI-based standalone server, Milvus Lite offers flexibility, whether embedded within Python code or used as a standalone server.

Available Resources

Milvus Standalone

Offering identical core vector database features, Milvus Lite, Milvus Standalone and Milvus Cluster differ in data size support and scalability requirements. Milvus Standalone operates independently as a single instance without clustering or distributed setup, ideal for smaller-scale deployments, CI/CD, and offline scenarios without Kubernetes support.

Available Resources

Milvus Cluster

Distributed across multiple nodes or servers, Milvus Cluster provides scalability, fault tolerance, and load balancing features for handling big data and serving concurrent queries efficiently. Leveraging distributed computing and load balancing, Milvus Cluster offers unparalleled availability, performance, and cost optimization for enterprise-grade workloads.

Available Resources

Making the Decision

When choosing the right Milvus version, factors such as dataset size, traffic volume, scalability requirements, and production environment constraints should be considered. Milvus Lite is perfect for prototyping, while Milvus Standalone offers high performance and flexibility for smaller-scale deployments. Milvus Cluster is ideal for large-scale, highly available production environments.

Additionally, Zilliz Cloud offers a hassle-free managed version of Milvus, providing an alternative for users seeking simplified deployment and management. Plus, with the Pipelines capability, you can created your embeddings in Zilliz Cloud providing you an all in one experience!

Ultimately, the selection of the Milvus version hinges on your specific use case, infrastructure requirements, and long-term goals. By carefully evaluating these factors and understanding the features and capabilities of each version, you can make an informed decision that aligns with your project's needs and objectives. Whether you opt for Milvus Standalone, Milvus Cluster, or Zilliz Cloud, harnessing the power of vector databases can significantly enhance the performance and efficiency of your AI applications.

12 Must-Have Resources for Mastering Milvus - Your Gateway to Seamless Vector Workloads

Chris Churilo — Sat, 13 Jan 2024 00:05:11 +0000

Embark on your Milvus Adventures: 12 Essential Resources for Seamless Vector Workloads - Your Weekly Guide (Jan 12, 2024)

COMMUNITY ٩(＾◡＾)۶

Our first meetup of 2024 is coming up in San Francisco (Github) and Seattle (Microsoft Reactor) on Jan 16, 2024. Please register early because they fill up fast!

San Francisco registration

Christy Bergman, Developer Advocate, Zilliz, Vector Search in the Age of OpenAI Assistants using Milvus
George Williams, Organizer, Big-ANN NeurIPS 2023, Are CPUs Enough? A Review Of Vector Search Running On Novel Hardware
Alexy Khrabrov, OSS Community Director, IBM and Chair, Generative AI Commons at the Linux Foundation, Introducing the Alliance.ai for Responsible, Safe AI

Seattle registration

Beyond RAG: Vector Databases - Yujian Tang
Exploring LLMOps: Building Better AI Applications - Sage Elliott
Elevating User Experience with Image-Based Fashion Recommendations - Joan Kusuma

ARTICLES To check out ໒(＾ᴥ＾)७

RAG

Vector Search & NLP

TUTORIALS ٩(◕‿◕｡)۶

Getting Started with a Milvus Connection
Milvus has four SDKs: Go, Java, Python, React, and Ruby. In this blog, we’ll show steps for Python.

Building an Open Source Chatbot Using LangChain and Milvus in Under 5 Minutes
This tutorial uses a completely open-source RAG (Retrieval Augmented Generation) stack with LangChain to answer questions about Milvus using our product documentation web pages.

Metadata Filtering with Zilliz Cloud Pipelines
This tutorial discuss scalar or metadata filtering and how you can perform metadata filtering in Zilliz Cloud. This blog continues on the previous blog on Getting started with RAG in just 5 minutes. You can find its code in this notebook and scroll down to Cell #27.

VIDEOS (＾▽＾)

GITHUB REPOS ᕙ(‾̀◡‾́)ᕗ

We love stars so give us one on our repo!

Milvus Vector Database. Milvus is an open source vector database used to store, index, and manage massive embedding vectors generated by deep neural networks and other machine learning (ML) models.

Akcio: Enhancing LLM-Powered ChatBot with CVP Stack A full chatbot app all open-source for you to try out for your self!

GPT Cache. GPTCache is an open-source tool designed to improve the efficiency and speed of GPT-based applications by implementing a cache to store the responses generated by language models.

VectorDBBench. VectorDBBench is an open-source benchmarking tool to help you evaluate the performance of mainstream vector databases and cloud services with yoru specific use case.

DEV Community: Chris Churilo

Comparing Observability tools

8 new RAG tutorials with the Voyage-3-Lite ML model

From Code Confusion to Coding Confidence

Number Eight

Number Seven

Number Six

Number Five

Number Four

Number Three

Number Two

Number One

Milvus Adventures November 15, 2024

COMMUNITY

Hot Topics

GITHUB REPOS

Milvus Adventures October 25, 2024

COMMUNITY

Recaps

Learn about Graph RAG

Learn more!

GITHUB REPOS

Milvus Adventures August 19, 2024

COMMUNITY

Learn about Natural Language Processing (NLP)

Large Language Models

GITHUB REPOS

Milvus Adventures August 14, 2024

COMMUNITY

Get stuck in on Multimodal RAG

Vector Embedding, the magic behind vector search

Vector Index basic

GITHUB REPOS

Milvus Adventures August 7, 2024

COMMUNITY

Learn About Gen AI

Get Started with LangChain

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Milvus Adventures July 29, 2024

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Milvus Adventures July 20, 2024

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Simplifying the Milvus Selection Process

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