Anthony Naddeo,

Danny D. Leybzon

Nov 23, 2021

Back to Blog

Running and Monitoring Distributed ML with Ray and whylogs

open source
whylogs
Integration
AI Observability

Anthony Naddeo,

Danny D. Leybzon

Nov 23, 2021

Running and monitoring distributed ML systems can be challenging. The need to manage multiple servers, and the fact that those servers emit different logs, means that there can be a lot of overhead involved in scaling up a distributed ML system. Fortunately, Ray makes parallelizing Python processes easy, and the open source whylogs enables users to monitor ML models in production, even if those models are running in a distributed environment.

Ray is an exciting project that allows you to parallelize pretty much anything written in Python. One of the advantages of the whylogs architecture is that it operates on mergeable profiles that can be easily generated in distributed systems and collected into a single profile downstream for analysis, enabling monitoring for distributed systems. This post will review some options that Ray users have for integrating whylogs into their architectures as a monitoring solution.

Continue reading on the Anyscale Ray Blog

Anthony Naddeo,

Danny D. Leybzon

WhyLabs Announces SCA with AWS to Accelerate Responsible Generative AI Adoption

WhyLabs Team

Nov 14, 2023

WhyLabs announces a Strategic Collaboration Agreement (SCA) with AWS to help enterprises accelerate the development of AI-powered applications.

Read post

WhyLabs
SageMaker

Understanding and Mitigating LLM Hallucinations

Felipe Adachi

Oct 18, 2023

LLMs are known for their ability to generate non-factual or nonsensical statements, more commonly known as “hallucinations.” This blog post will cover the challenges and possible solutions for hallucination detection.

Read post

LLMs
AI Observability

Understanding and Monitoring Embeddings in Amazon SageMaker with WhyLabs

Andre Elizondo,

Shun Mao,

James Yi

Sep 11, 2023

WhyLabs and Amazon Web Services (AWS) explore the various ways embeddings are used, issues that can impact your ML models, how to identify those issues and set up monitors to prevent them in the future!

Read post

WhyLabs
ML Monitoring

Data Drift Monitoring and Its Importance in MLOps

Sage Elliott

Aug 29, 2023

It's important to continuously monitor and manage ML models to ensure ML model performance. We explore the role of data drift management and why it's crucial in your MLOps pipeline.

Read post

MLOps
Data Logging

Glassdoor Decreases Latency Overhead and Improves Data Monitoring with WhyLabs

Jamie Broomall,

Lanqi Fei,

Natalia Skaczkowska-Drabczyk

Aug 17, 2023

The Glassdoor team describes their integration latency challenges and how they were able to decrease latency overhead and improve data monitoring with WhyLabs.

Read post

WhyLabs
Machine Learning

Ensuring AI Success in Healthcare: The Vital Role of ML Monitoring

Kelsey Olmeim

Aug 10, 2023

Discover how ML monitoring plays a crucial role in the Healthcare industry to ensure the reliability, compliance, and overall safety of AI-driven systems.

Read post

ML Monitoring

WhyLabs Recognized by CB Insights GenAI 50 among the Most Innovative Generative AI Startups

WhyLabs Team

Aug 8, 2023

WhyLabs has been named on CB Insights’ first annual GenAI 50 list, named as one of the world’s top 50 most innovative companies developing generative AI applications and infrastructure across industries.

Read post

WhyLabs

Hugging Face and LangKit: Your Solution for LLM Observability

Sage Elliott

Jul 26, 2023

See how easy it is to generate out-of-the-box text metrics for Hugging Face LLMs and monitor them in WhyLabs to identify how model performance and user interaction are changing over time.

Read post

LLMs
WhyLabs

7 Ways to Monitor Large Language Model Behavior

Felipe Adachi

Jul 20, 2023

Discover seven ways to track and monitor Large Language Model behavior using metrics for ChatGPT’s responses for a fixed set of 200 prompts across 35 days.

Read post

LLMs
WhyLabs

Run AI With Certainty

Book a demo

Running and Monitoring Distributed ML with Ray and whylogs

Other posts

WhyLabs Announces SCA with AWS to Accelerate Responsible Generative AI Adoption

Understanding and Mitigating LLM Hallucinations

Understanding and Monitoring Embeddings in Amazon SageMaker with WhyLabs

Data Drift Monitoring and Its Importance in MLOps

Glassdoor Decreases Latency Overhead and Improves Data Monitoring with WhyLabs

Ensuring AI Success in Healthcare: The Vital Role of ML Monitoring

WhyLabs Recognized by CB Insights GenAI 50 among the Most Innovative Generative AI Startups

Hugging Face and LangKit: Your Solution for LLM Observability

7 Ways to Monitor Large Language Model Behavior

Run AI With Certainty

About

Resources

whylogs

WhyLabs