The Data + AI Downtime Blog

The latest trends and news in data + AI observability.

Most recent

Inside Our Final TDAI Council Meeting of 2025: When Agents Meet Reality

Everyone wants to know: How do we make sure agents actually work when it matters?

Introducing Agent Observability: Making AI Work in the Real World

The New Dictionary of AI Reliability

Application Observability vs Data Observability

4 Famous AI Fails (& How to Avoid Them)

LLM-As-Judge: 7 Best Practices & Evaluation Templates

Redefining AI-Ready Data for Production

The Top 5 AI Reliability Pitfalls

In the AI Kingdom, Experience is King

Data Observability

17 Valuable Use Cases for Automated Data Lineage

Learn how today's data teams apply automated lineage to boost productivity, reduce time to incident resolution, and more.

Download

Meet Your New AI Compliance Manager

AI Data Lineage Explained: Automatic Mapping for Modern Data Stacks

Application Observability vs Data Observability

What is Data Integrity and How Do I Improve It?

4 Famous AI Fails (& How to Avoid Them)

Stop Fighting Fires: 3 Easy Ways to Transform Data Engineering with AI Workflows

AI Observability

The 17 Best AI Observability Tools in December 2025

What Is Open Source AI Observability? Tools, Alternatives, and Best Practices.

AI Agent Evaluation: 5 Lessons Learned The Hard Way

LLM-As-Judge: 7 Best Practices & Evaluation Templates

AWS re:Invent 2025: Everything You Need to Know Before You Go

What Is Agent Observability? Key Concepts, Use-Cases, & Vendors

Data Platforms

Reverse ETL: The Missing Piece of the Data Quality Puzzle

Data Migration Risks and the Checklist You Need to Avoid Them

Cheat Sheet: A Data Leader's Guide to Data Metrics

Access the must-have metrics today's data leaders use to measure data quality, platform ROI, team productivity, and more.

Download Your Copy

Data Orchestration 101: Process, Benefits, Challenges, and Tools

What Is Model Context Protocol (MCP)? A Quick Start Guide.

12 Data Management Best Practices Your Team Should Follow

The Complete Guide to Data Management: What It Is, Why It Matters, and How to Get Started

AI Culture

In the AI Kingdom, Experience is King

The Ultimate Guide to Data Product Management

Learn how to build, manage, and scale reliable data products in our latest how-to guide, written by and for data product managers.

Download

AI Data Manager Salary, Skills, & Career Path

10 Data + AI Trends to Watch In Fall 2025

Chief Data and AI Officers to Watch: Data & AI Leaders Driving Enterprise Transformation

How Monte Carlo’s Team Delivers Customer Impact From Day One

How to Create a Data Quality Strategy (in 5 Steps)

Data Reliability

Monitoring Through Disaster: Why Multi-Region Hosting Matters

Data Remediation: Ensuring Data Quality and Reliability in Modern Data Pipelines

2023 Modern Data Leader's Playbook

Stay up-to-date with the latest technologies, trends, and processes shaping modern data management.

Access Today

Data Munging That Actually Works

What Makes a Winning Data Enablement Strategy?

What is Data as a Product vs. Data as a Service?

Data Warehouse Design Best Practices

Data Discovery

6 Tips For Better SQL Query Optimization

Star Schema vs. Snowflake Schema: Which One Should You Use?

The Best Snowflake Orchestration Tools

Data Catalog vs. Data Dictionary: 5 Essential Differences

Tired of Broken Pipelines? Here’s How ETL Orchestration Can Help

Messy Files and Confused Teams? You Need Product Data Management

Case Studies

How Calendly Reduced Data-Related Bug Tickets 40%

How Much Does Bad Data Cost You?

Do you know the cost of data downtime? This guide will help you calculate the cost of bad data for your company.

Download

Data Vault Architecture: Everything You Need to Know Before You Build

Nasdaq’s Journey to Data Reliability with Monte Carlo

How Skyscanner Enabled Data & AI Governance with Monte Carlo

How an Enterprise Intelligence Platform Delivered Self-Service Data Trust with Data Observability

How Roche Built Trust in the Data Mesh with Data Observability

Announcements

Meet MCP: The Next Step in AI-Driven Data + AI Observability

Chief Data and AI Officers to Watch: Data & AI Leaders Driving Enterprise Transformation

Monte Carlo Appoints Former Grafana Labs, AppDynamics Executive Wayne Jin as Chief Marketing Officer

Monte Carlo Launches Agent Observability to Help Teams Build Reliable AI

Monte Carlo First Data + AI Observability Company to Launch Native Integrations with Salesforce to Ensure Reliable, AI-Ready Customer Data

Monte Carlo Unveils Unstructured Data Monitoring, a No-Code Solution to Deliver AI-Ready Data at Scale

Redefining AI-Ready Data for Production

The Top 5 AI Reliability Pitfalls

In the AI Kingdom, Experience is King

AI Observability Tools

What’s AI observability, when do you need it, and what are the best tools to deliver reliable data and agents at scale? Check out our list of 17 AI observability tools.

Learn more

Redefining AI-Ready Data for Production

AI-ready data is about more than what you do before deployment. Find out how to implement an operational model that will enable you to drive AI reliability and adoption in production.

Learn more

Data testing vs. data quality monitoring vs. data observability: What's right for your team?

In the fight against bad data and broken pipelines, there are a few popular options. But what makes the most sense for your data quality needs? We’ve got the answers.

Learn more

The Data + AI Downtime Blog

Most recent

Inside Our Final TDAI Council Meeting of 2025: When Agents Meet Reality

Introducing Agent Observability: Making AI Work in the Real World

The New Dictionary of AI Reliability

Featured

Application Observability vs Data Observability

4 Famous AI Fails (& How to Avoid Them)

LLM-As-Judge: 7 Best Practices & Evaluation Templates

Editors picks

Redefining AI-Ready Data for Production

The Top 5 AI Reliability Pitfalls

In the AI Kingdom, Experience is King

Data Observability

17 Valuable Use Cases for Automated Data Lineage

Meet Your New AI Compliance Manager

AI Data Lineage Explained: Automatic Mapping for Modern Data Stacks

Application Observability vs Data Observability

What is Data Integrity and How Do I Improve It?

4 Famous AI Fails (& How to Avoid Them)

Stop Fighting Fires: 3 Easy Ways to Transform Data Engineering with AI Workflows

AI Observability

The 17 Best AI Observability Tools in December 2025

What Is Open Source AI Observability? Tools, Alternatives, and Best Practices.

AI Agent Evaluation: 5 Lessons Learned The Hard Way

LLM-As-Judge: 7 Best Practices & Evaluation Templates

AWS re:Invent 2025: Everything You Need to Know Before You Go

What Is Agent Observability? Key Concepts, Use-Cases, & Vendors

Data Platforms

Reverse ETL: The Missing Piece of the Data Quality Puzzle

Data Migration Risks and the Checklist You Need to Avoid Them

Cheat Sheet: A Data Leader's Guide to Data Metrics

Data Orchestration 101: Process, Benefits, Challenges, and Tools

What Is Model Context Protocol (MCP)? A Quick Start Guide.

12 Data Management Best Practices Your Team Should Follow

The Complete Guide to Data Management: What It Is, Why It Matters, and How to Get Started

AI Culture

In the AI Kingdom, Experience is King

The Ultimate Guide to Data Product Management

AI Data Manager Salary, Skills, & Career Path

10 Data + AI Trends to Watch In Fall 2025

Chief Data and AI Officers to Watch: Data & AI Leaders Driving Enterprise Transformation

How Monte Carlo’s Team Delivers Customer Impact From Day One

How to Create a Data Quality Strategy (in 5 Steps)

Data Reliability

Monitoring Through Disaster: Why Multi-Region Hosting Matters

Data Remediation: Ensuring Data Quality and Reliability in Modern Data Pipelines

2023 Modern Data Leader's Playbook

Data Munging That Actually Works

What Makes a Winning Data Enablement Strategy?

What is Data as a Product vs. Data as a Service?

Data Warehouse Design Best Practices

Data Discovery

6 Tips For Better SQL Query Optimization

Star Schema vs. Snowflake Schema: Which One Should You Use?

The Best Snowflake Orchestration Tools

Data Catalog vs. Data Dictionary: 5 Essential Differences

Tired of Broken Pipelines? Here’s How ETL Orchestration Can Help

Messy Files and Confused Teams? You Need Product Data Management

Case Studies

How Calendly Reduced Data-Related Bug Tickets 40%

How Much Does Bad Data Cost You?

Data Vault Architecture: Everything You Need to Know Before You Build

Nasdaq’s Journey to Data Reliability with Monte Carlo

How Skyscanner Enabled Data & AI Governance with Monte Carlo

How an Enterprise Intelligence Platform Delivered Self-Service Data Trust with Data Observability

How Roche Built Trust in the Data Mesh with Data Observability

Announcements

Meet MCP: The Next Step in AI-Driven Data + AI Observability

Chief Data and AI Officers to Watch: Data & AI Leaders Driving Enterprise Transformation

Monte Carlo Appoints Former Grafana Labs, AppDynamics Executive Wayne Jin as Chief Marketing Officer

Monte Carlo Launches Agent Observability to Help Teams Build Reliable AI

Monte Carlo First Data + AI Observability Company to Launch Native Integrations with Salesforce to Ensure Reliable, AI-Ready Customer Data

Monte Carlo Unveils Unstructured Data Monitoring, a No-Code Solution to Deliver AI-Ready Data at Scale

Editors picks

Redefining AI-Ready Data for Production

The Top 5 AI Reliability Pitfalls

In the AI Kingdom, Experience is King

Related resources

AI Observability Tools