Supported Technologies
Causely supports a wide range of technologies across installation, telemetry sources, and workflow integrations. Find your technologies below to get started.
Installation​
Deploy Causely agents using these installation methods:
Install Causely using the command-line interface for quick setup and configuration.
Deploy Causely on standalone Docker hosts for services running outside Kubernetes.
Deploy Causely using FluxCD for GitOps-based deployment and management.
Deploy Causely on Kubernetes using Helm charts for easy management and configuration.
Deploy Causely on Kubernetes clusters for real-time causal analytics.
Install Causely on HashiCorp Nomad clusters for distributed workload management.
Telemetry Sources​
Connect your existing observability tools and data sources:
Enable cross-service traceability for enterprise and cloud applications.
AWS Managed Services
Integrate CloudWatch metrics and events to infer causes in managed AWS workloads.
Surface reliability issues in Azure services with native telemetry inputs.
Capture detailed performance traces from high-performance systems to improve causal inference precision.
Use API and synthetic check failures as trusted inputs for causal analysis.
Detect message queue congestion and downstream impact from Kafka telemetry.
Use Cortex metrics and alerts as key signals for detecting and diagnosing service-level issues.
Use Datadog traces and monitors as trusted signals for causal analysis.
Use Dynatrace traces and metrics to strengthen causal inference and reliability insights.
Capture kernel-level dependencies and performance signals without modifying code.
Integrate Elasticsearch metrics and logs to detect and resolve performance issues.
Map message-passing and concurrent behavior to detect issues in distributed environments.
Integrate GCP service metrics to infer causes in managed workloads.
Add low-overhead tracing to cloud native applications for faster dependency discovery.
Use Grafana to bring in metrics, logs, and traces as rich inputs for causal analysis.
Combine high-fidelity eBPF data with Causely's analytics.
Leverage incident.io alerts as trusted inputs for causal analysis.
Integrate Instana traces and metrics to enhance causal analysis and deepen reliability insights.
Map service mesh communication patterns for precise dependency-aware causal inference.
Connect JVM traces and metrics for proactive detection of performance regressions.
Instrument JavaScript-based services to capture backend traces and uncover issues in distributed architectures.
Map pod-level health and resource metrics to their upstream service dependencies.
Use Mimir metrics and alerts as key signals for detecting and diagnosing service-level issues.
Identify database query latency or connection errors as causes in distributed issues.
Nobl9
Align SLO breaches with Causely's causal insights to prioritize reliability work.
Odigos
Automatically instrument services with OpenTelemetry and feed traces into Causely's engine.
Enable automatic discovery of service dependencies across both synchronous and asynchronous communications.
Include PHP service traces to expose web transaction bottlenecks in causal analysis.
Link PostgreSQL performance and query issues to affected services in real time.
Use Prometheus metrics and alerts as key signals for detecting and diagnosing service-level issues.
Use Alertmanager alerts as trusted inputs for causal analysis.
Link Python app traces and metrics to detect slow APIs or resource contention.
Enable full-trace visibility across Ruby web and background jobs for causal inference.
Rust
Feed low-level telemetry into Causely to uncover performance and memory-related causes.
Surface warehouse congestion or query slowdowns as upstream causes in analytics pipelines.
Connect Swift app traces to isolate problems across distributed components.
Workflow Integrations​
Send Causely insights to your existing workflow tools:
Visualize causes and their service impact directly in your Grafana dashboards — across Grafana Cloud or your self-hosted deployment.
Send causal insights to Grafana Alertmanager without additional configuration.
Automatically create and resolve incidents in incident.io from causal analysis by Causely.
Create Jira issues from Causely causal insights with service-level impact and ownership metadata.
Post causal insights into Microsoft Teams to keep dev and ops teams aligned.
Route causal insights into Opsgenie with the context your team needs.
Push causal insights into your existing Prometheus Alertmanager pipeline.
Send causal insights directly to your team Slack channels, so critical issues are seen and acted on immediately.
Splunk On-Call
Deliver real-time causal insights into Splunk On-Call with service-level impact and ownership metadata.
Missing a Technology?​
Don't see your technology listed? We're constantly adding support for new technologies. Reach out to us and let us know what you're using - we'd love to help you get started with Causely.