Causely Announces OpenTelemetry Integration: Solving Observability Overload For Developers

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Causely is announcing its integration with OpenTelemetry, bringing a fresh approach to observability that cuts through the noise and surfaces only what matters.

In today’s world of modern cloud applications, observability is both a necessity and a challenge. With countless services interacting dynamically, engineering teams are often flooded with logs, traces, and metrics, making it difficult to extract meaningful insights when something goes wrong. Traditional observability approaches rely on collecting everything—but the sheer volume of data can be overwhelming, turning troubleshooting into a time-consuming and frustrating process.

Causely is here to change that. Today, the company is announcing its integration with OpenTelemetry, bringing a fresh approach to observability that cuts through the noise and surfaces only what matters.

Yotam Yemini, CEO of Causely, highlights that OpenTelemetry adoption often requires significant effort, as teams must determine which data to collect, how to sample it, and how to extract useful insights. “Causely is focused on cutting through that noise to pinpoint what matters,” Yemini says. Causely does this by automatically filtering out unnecessary data and providing a structured understanding of system dependencies and potential failure points. The integration makes OpenTelemetry more practical and efficient, ensuring engineers receive only the most relevant insights.

The Challenge of Observability Today

Modern applications generate an immense amount of telemetry data, whether it’s from microservices, distributed systems, or cloud infrastructure. While OpenTelemetry has become the de facto standard for collecting and transmitting this data, its adoption often comes with significant hurdles. Engineers frequently struggle with:

• Too much data, too little insight – Logs and traces pile up, making it difficult to identify real issues.
• Slow root cause analysis – Teams spend too much time manually sifting through observability data.
• Uncertain data collection strategies – Debates about sampling vs. full collection leave engineers guessing about what’s really needed.

The result? An overload of information but very few actionable insights.

A Smarter Approach to Observability

Causely’s Causal Reasoning Platform takes a fundamentally different approach. Instead of just presenting raw telemetry data, it analyzes dependencies and causal relationships between different components of an application. This means that instead of looking at an overwhelming sea of logs, engineers can quickly pinpoint what is causing an issue and how it propagates through the system.

With the new OpenTelemetry integration, Causely makes it even easier for teams to:

• Seamlessly ingest OpenTelemetry traces and metrics without any complicated setup.
• Automatically filter out irrelevant data and highlight the most critical insights.
• Predict potential failures before they happen, allowing teams to be proactive instead of reactive.

By integrating with OpenTelemetry, Causely aims to bridge the gap between raw telemetry collection and intelligent observability. Teams can proactively manage service reliability, prevent latency issues, and optimize performance, making observability more effective and manageable.

How it Works

Causely provides two easy ways to integrate with OpenTelemetry. If your team is already using OpenTelemetry, you can simply point your existing collector at Causely. Within seconds, the system begins processing the telemetry data and identifying key dependencies, bottlenecks, and potential risks.

For teams that haven’t yet adopted OpenTelemetry, Causely offers an alternative: auto-instrumentation using eBPF. This allows teams to collect the necessary telemetry data without having to manually modify their applications. The best part? It all runs in your own cloud environment, ensuring data privacy and security while keeping infrastructure overhead minimal.

Beyond OpenTelemetry: Observability without Limits

While this new integration enhances how teams use OpenTelemetry, Causely isn’t limited to a single observability standard. The platform is designed to work with any telemetry source, whether proprietary or open-source, ensuring flexibility for engineering teams regardless of their stack.

By decoupling the intelligence layer from data collection, Causely provides a unified way to analyze and act on observability data, no matter where it comes from. This approach helps reduce the complexity caused by vendor sprawl, allowing teams to focus on application performance rather than managing observability infrastructure.

Who Benefits from Causely?

Causely is built for any engineering team dealing with complex, microservices-driven applications. Whether you’re operating a large-scale SaaS platform, managing a fintech infrastructure, or ensuring the reliability of a healthcare application, Causely helps keep things running smoothly by automating root cause detection and providing predictive insights.

Companies already leveraging Causely include publicly traded SaaS providers, financial institutions, telecom giants, and healthcare tech firms—all benefiting from the ability to reduce incident resolution times and improve service reliability.

Get Started with Causely

Observability doesn’t have to be overwhelming. With Causely’s OpenTelemetry integration, teams can move beyond raw data collection and gain instant, actionable insights that make troubleshooting faster and easier.

For those interested in trying it out, Causely offers a free trial where you can explore a demo environment or set up a real-world deployment in minutes. To get started, visit causely.ai and see how causal reasoning can transform your observability strategy.

Instead of spending hours digging through logs, let Causely do the heavy lifting—so you can focus on building great applications.

Guest: Yotam Yemini
Company: Causely
Show: Let’s Talk

Summary is written by Emily Nicholls