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. Their causal reasoning platform automatically pinpoints root causes in the endless sea of observability data, helping engineers avoid unnecessary manual effort.
Causely's founder, Shmuel Kliger, has been thinking about the frustrations in observability (which was once called monitoring) for decades. He's sold two prior companies to IBM and Dell EMC. His opinions are blunt and straightforward about machines handling some tasks better than humans, and he says that we should embrace the opportunities for software to help engineers solve problems faster.
"If anything, these problems have gotten worse with the rise of microservices and AI," said Kliger. "Businesses are collecting endless data thinking they may need it later, but much of that data ends up being useless—it just gets in the way when something goes wrong, and you need to pinpoint where the issue is and how to fix it."
Causely instead takes a unique "top-down" approach that starts with a defined, finite set of root causes. After automatically mapping an application's topology and service dependencies, their causal reasoning system can make sense of patterns and quickly connect the data to the root cause.
Today, the company announced its latest integration with OpenTelemetry—the beloved open-source project for collecting observability data. According to Kliger, while OpenTelemetry marks a necessary paradigm shift in observability by standardizing how telemetry data is collected and processed, the overwhelming volume of metrics, logs, and traces collected across an organization's cloud and microservices architecture can overwhelm teams, slow down workflows, inflate costs, and make it difficult for engineers to pinpoint root causes.
Causely installs in cloud-native environments in under a minute. For teams who have yet to adopt OpenTelemetry, they can choose to leverage Causely's eBPF-based auto-instrumentation to start collecting traces instantly.
"We're big believers in OpenTelemetry—but there's no free lunch," said Kliger. "OpenTelemetry generates a lot of noise and requires a lot of manual effort to surface the data you need, when you need it, without a system like Causely."
