“Root Cause Analysis” (RCA) is one of the most overloaded terms in modern engineering. Some call a tagged log line RCA. Others label time-series correlation dashboards or AI-generated summaries as RCA. Some reduce noise by filtering or hiding secondary and cascading alarms. And recently large language models (LLMs) have entered
When it comes to observability and IT operations, our goal should be to get humans out of the loop as much as possible.
With Causely, you can see the why behind what’s happening without having to leave your Grafana interface.
“You actually cannot do meaningful reasoning especially when it comes to root cause analysis with LLMs or machine learning alone. You need more than that.” -Shmuel Kliger, Founder of Causely
A version upgrade. A schema change. And suddenly, a critical service stalls. MySQL 8’s hidden metadata locking behavior has tripped up even the most prepared teams. We captured this knowledge — and now, Causely can pinpoint it. If you’ve learned about how Causely works, you already know that our
Assuring service reliability is the most critical goal of IT. It was never easy, and it is getting increasingly complex as businesses require greater speed, agility, and scalability to stay competitive and respond quickly to changing market demands. These needs are driving the adoption of microservices architectures, enabling organizations to
At Causely, we don’t just ship software – we run a reasoning platform designed to detect, diagnose, and resolve failure conditions with minimal human intervention. Our own cloud-native application runs in a highly distributed environment, with dozens of interdependent microservices communicating in real-time. It’s complex, dynamic, and constantly evolving—
Implementing OpenTelemetry at the core of our observability strategy for Causely’s SaaS product was a natural decision. This post shares context on our rationale and how the combination of OpenTelemetry and causal reasoning underpin our platform.
In this DevOps Toolkit episode, Endre Sara joins Viktor Farcic for an Ask Me Anything session.
This production-focused guide offers an understanding of what OpenTelemetry is, its core components, and a detailed look at the OTel Collector.
Shmuel talks with Techstrong.tv's Alan Shimel about Causely launching its integration with OpenTelemetry, which has redefined observability by standardizing how telemetry data is collected and processed.
Causely is a new player on the observability scene. The main problem their platform addresses is that modern teams are drowning in too many alerts and too much data coming from multiple observability solutions across open-source and 3rd party vendors.
Media Article
Causely is announcing its integration with OpenTelemetry, bringing a fresh approach to observability that cuts through the noise and surfaces only what matters.
Media Article
View the original article on CIODive. I’ve spent over three decades in IT Operations. Despite all the talk of transformation, many of the fundamental challenges remain unchanged, or have even worsened. The rise of modern DevOps and observability promised to revolutionize how we monitor and maintain systems, but in
Podcast
In this 10KMedia Podcast interview, Adam sits down with Shmuel to discuss the problems with traditional observability, the importance of OpenTelemetry, and how Causely is helping teams find the signal in the noise.
Causely product
Causely, the causal reasoning platform for modern engineering teams, today launches a native integration with OpenTelemetry.
Blog
Bridging the gap between observability data and actionable insight
Causely product
We’ll introduce the 6 common components and 7 AI Workers of our Causal Reasoning Platform, explaining how the platform works to enable autonomous service reliability.
Causality
Collecting “more data” has been the defining characteristic of observability practices and tools for the last few decades. But over-collection creates inefficiencies, noise, and cost without adding meaningful value. This trajectory must and can be changed.
Causality
By identifying potential risks in real time, predicting future demand, and adapting resources dynamically, teams can maintain reliability even under extreme conditions. This isn’t about eliminating unpredictability; it’s about building systems that respond intelligently to it.
DevOps & SRE
Making changes to production environments is one of the riskiest parts of managing complex systems. In 2025, let's transform how changes are made, empowering teams to anticipate risks, validate decisions, and protect system stability—all before the first line of code is deployed.
Causality
Explore the challenges of multi-team escalations, and the capabilities needed to address them. We’ll show how observability can be transformed to make escalations less contentious and more productive.
Causality
SREs and developers can make troubleshooting more manageable in 2025 by adopting systems that solve the root cause analysis problem.
Media Article
Read the Observability 360 announcement of all The O11ys 2024 winners. Best Use of AI Winner: Causely Many observability systems now claim to support Root Cause Analysis. At the same time though, most of these systems use algorithms – admittedly, advanced…