Assuring service reliability is hard
Cloud-native applications typically involve highly distributed systems with numerous interdependent services. When a problem occurs, observability tools may detect dozens or hundreds of anomalies. This complexity can lead to many symptoms appearing simultaneously or in a cascade, making it challenging to determine which are causal and which are merely consequential.
Finding the signal hidden in all the noise is time-consuming and requires highly skilled engineers. These engineers end up triaging and troubleshooting while application performance degrades and business is disrupted. Continuous application reliability cannot be accomplished in this mode of operation.
Automate root cause analysis
Our Causal Reasoning Platform continuously analyzes observed anomalies to automatically pinpoint the root causes that explain those anomalies and can trigger immediate remediation actions, where applicable. Root causes are categorized and prioritized based on their SLO impacts.
Troubleshooting is automated in software, dramatically reducing incident resolution times and the number of incidents, so your time is spent developing and improving systems.
Proactively prevent SLO violations
We're committed to ensuring service reliability implies that none of your SLOs are being violated.
Causely's causal knowledge represents the relationship between root causes and the SLOs they may impact. Causely continuously pinpoints root causes before SLOs are violated, prioritizes root causes based on their SLO impacts, and identifies opportunities for improvement.
Causely helps you understand what actions to take to prevent future SLO violations.
Better alignment between teams
Transparency builds alignment. Causely empowers application development teams and service owners to independently own and operate what they build, delivering a 360-degree view of the entire service topology and associated cause-and-effect relationships.
Detected issues trigger notifications to relevant teams, explaining both the root cause and affected services. Raising visibility of root causes and their effects knocks down silos, instead driving cross-team alignment and faster collaboration between platform teams and service owners.
Seamless installation
Causely seamlessly integrates with your existing stack, leveraging the telemetry you already collect to deliver immediate value. Whether you're using OpenTelemetry, eBPF, or native cloud instrumentation, Causely consumes and analyzes your existing data streams without requiring additional instrumentation or reconfiguration. It automatically infers your system's topology, mapping service dependencies, interactions, and causality across your cloud-native environment.
This out-of-the-box functionality means no extra overhead for your team—no new agents, no custom instrumentation, and no rearchitecting your workflows. From day one, Causely begins surfacing root causes, identifying active risks, and predicting future failures, allowing your team to focus on resolving issues rather than hunting for needles in the haystack. It's precision at scale, delivered through the tools you already trust.
Security and performance
Your sensitive data stays in your cloud. Minimal performance metrics are transferred to our backend, keeping your data safe and avoiding prohibitive transfer and storage costs.
Our Causal Reasoning Platform minimizes the transfer of data to its SaaS backend and retains most of the data within the customer environment. This primarily encompasses the service topology and detected symptoms such as high CPU utilization. The raw source data, such as metrics and logs, are retained in the customer's environment such as metrics and logs, are retained in the customer's environment and are not transmitted to the SaaS backend.
Learn more about our approach to security →
How Causely works
Causely installs in a cloud-native application environment in under a minute using auto-instrumentation. It automatically maps your topology and service dependencies to start applying causal reasoning without requiring any complex configuration. You can combine Causely's default instrumentation with your existing telemetry data and observability stack, and push insights from Causely anywhere using webhooks.
Get started quickly
Causely installs in seconds using automatic instrumentation. Your existing observability tools can be used as data sources into Causely, no need to rip and replace anything.
Protect your data
Causely keeps your sensitive data in your environment, without causing any negative performance impact. Only kilobytes of boolean data get sent to our SaaS backend each minute.
Use causal reasoning
Causely's Causal Reasoning Platform is the core analytics engine that enables autonomous service reliability. Learn more about how Causely works
Integrate with everything
Users can interact with Causely's analytics via the web UI, as well as operationalize the product via its API and webhooks.
Introducing the Causal Reasoning Platform
Our Causal Reasoning Platform (CRP) is a model driven, purpose-built AI system delivering multiple analytics built on a common data model. It is designed to make troubleshooting much simpler and more effective by providing out-of-the-box Causal Models and automatic topology discovery that generates a Topology Graph. Using the Causal Models and the Topology Graph, CRP automatically generates a Causality Graph from which it generates the Codebook.
CRP uses the Codebook to pinpoint the root causes of issues automatically in real-time.
Causal Models are the knowledge base
Over 120 types of root causes are captured in the 34 out-of-the-box Causal Models applicable to any cloud-native application environment.
The Topology Graph is the cartographer
Causely automatically discovers the entities and their relationships and maps dependencies among the complex, dynamic web of applications, services, and infrastructure.
The Causality Graph maps relationships beyond human scale
A Directed Acyclic Graph (DAG) is automatically generated by applying Causal Models to the Topology Graph.
The Codebook translates symptoms to root cause
Causely maps all possible root causes to all the symptoms each of them may cause with the likelihood of each symptom occurring in a causality table.
The Causely UI empowers remediation & planning
Root causes, related symptoms, service impacts, and remedial actions presented in a simple, intuitive visual interface.
Integrate with anything
Causely provides native instrumentation while also allowing you to use your existing telemetry and observability data sources. As entities and relationships across your cloud-native environment change, Causely automatically updates the Topology Graph, Causality Graph and Codebook for your environment. Our analytics are shared with users via the Causely UI and can take action through incident management, GitOps, CI/CD, and service management systems via webhooks.
Ready to ensure your service reliability?
Causely installs in minutes. Use Causely's out-of-the-box instrumentation or connect your existing observability and monitoring tools as data sources.
