Your AI Ops Agent Is Guessing

Named root causes are what turn a guessing agent into one you can trust to act without manual review.

Why AI agents burn tokens on every reliability query

AI agents reconstruct environment state from raw telemetry on every reliability query. Causal context eliminates the reconstruction and cuts token use by 60%.

Why Your AI SRE Agent Is Stuck on Read-Only

Most AI SRE agents are stuck on Read-Only — not because teams lack trust, but because raw telemetry offers no causal context to act on with confidence.

How Humm Group Delivered Flawlessly in a High-Stakes Product Launch

Launching a new fintech product required certainty across a complex microservices platform. With Causely modeling cause-and-effect relationships across services, Humm Group gained system-level understanding and confidence that critical dependencies behaved correctly during launch.

Reliability Is Managed In Services, But Felt In Transactions

Reliability is managed in services, but users experience outcomes. In complex, multi-service and AI-driven architectures, systems can look healthy in isolation while end-to-end workflows still fail. Product reliability needs visibility at the level of transactions and flows.

Alerts Aren’t the Investigation: What Comes Next in Incident Response?

Alerts are signals, not explanations. By explicitly mapping alerts to symptoms and inferred root causes, Causely turns alert noise into a coherent explanation of what is actually happening in the system.

How to Turn Slow Queries into Actionable Reliability Metrics with OpenTelemetry

Slow SQL queries degrade UX and reliability. This guide shows how to distill OpenTelemetry DB spans into actionable metrics: build span-derived slow-query dashboards, rank queries by traffic impact, and detect regressions with anomaly baselines, so you fix what matters first. Hands-on lab included.

When Asynchronous Systems Fail Quietly, Reliability Teams Pay the Price

Causely’s causal model has been expanded for asynchronous messaging systems. Instead of treating queues as opaque buffers, Causely models messaging infrastructure as it operates in production, making asynchronous failures explicit and explainable.

Alerts Aren’t the Investigation

Alerts are supposed to start an investigation. Too often, they start translation: what is the system doing right now? That translation slows containment, splinters context, and stretches customer impact.

Queue Growth, Dead-Letter Queues, and Why Asynchronous Failures Are Easy to Misread

Asynchronous pipelines sit at the core of most modern systems. Message brokers accept traffic, consumers process it in the background, and downstream services depend on the results. When these systems fail, the failure rarely shows up where it starts.

Slight Reliability EP 113: AI Use-cases for SRE with Shmuel Kliger

Originally published to the Slight Reliability Podcast.

Causely Expands Datadog Integration to Deliver Causal Intelligence Across Hybrid Environments

Causely’s expanded Datadog integration turns Datadog APM signals into system-level causal intelligence, helping teams understand how issues propagate across services and pinpoint true root cause.

DevOps & SRE

Thank You, FluxCD: How it helps us, and how you can use it too!

How Causely uses FluxCD and GitOps to ship weekly on Kubernetes, keep clusters in sync, and wire up OpenTelemetry and Causely in a hands-on lab you can copy.

Causely Named a Gartner Cool Vendor in AI for IT Operations 2025

Gartner recognized Causely for maintaining a live causality graph and using continuous inference to identify the underlying driver behind changes in golden signals as they emerge, even when failures cascade across multiple services.

Blog

Announcing Reliability Delta: Clear, Objective Insight into Whether Your Release Made Your System Better or Worse

In a 50 to 100+ microservice environment with dense service-to-service dependencies, even small regressions can cascade silently. And slowing down isn’t an option. Leadership needs faster delivery and fewer incidents. This is why we built Reliability Delta. 

Podcast

eAfterWork EP 9: What Every Leader Needs to Know with Severin Neumann

Originally published as a livestream to e-After Work.

coverage

Causely: Continuous service reliability root cause hunting

Originally posted to Intellyx by Jason English.

Podcast

Purposeful OpenTelemetry

Originally posted as a livestream from OllyGarden.

AI

How Causal AI Is Transforming SRE Reliability in Kubernetes Environments

Originally posted to TFIR by Monika Chauhan. Causely’s Severin Neumann explains how causal reasoning, MCP, and AI-driven automation are transforming SRE workflows and Kubernetes reliability.

DevOps & SRE

Causely Brings Reliability Engineering to the Heart of Cloud-Native Development with Yotam Yemini

Originally posted to Techstrong.tv. Learn how Causely integrates reliability engineering into product development, tackling challenges in cloud-native applications.

Blog

Drinking the OTel SODA: Send Observability Data Anywhere

With community-standard instrumentation and the OTel Collector, your metrics, logs, and traces are no longer trapped in a walled garden. Originally posted to the ClickHouse blog.

coverage

International Business Times: Cutting Through the Noise — Startups to Watch at KubeCon 2025

Originally posted to International Business Times by David Thompson.

Causality

TechOps Talk: Causal Reasoning-Based Root Cause Analysis

Learn why causal inference is the missing piece in AI-driven observability, and how Causely is the only AI SRE platform that uses causal reasoning to pinpoint where, what, and why application and system related issues occur.

coverage

Cloud Native Now: Causely Adds MCP Server to Causal AI Platform for Troubleshooting Kubernetes Environments

Originally posted to Cloud Native Now by Mike Vizard.