Latest Releases

Each release of Causely includes new features, bug fixes, and performance improvements. This page provides highlights of the most recent releases.

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Overview

Each release of Causely includes new features, bug fixes, and performance improvements. This page provides highlights of the most recent releases.

To get details on older releases, please go to the changelog page, listing all releases.

September 23, 2025

Version 1.0.92

Enhanced Ask Causely with Integration and Documentation Support

Ask Causely now provides intelligent assistance across two critical areas that significantly expand its utility:

Integration Status Intelligence:

• Real-Time Integration Health: Ask about the current state of your telemetry integrations and data sources
• Configuration Validation: Get insights into integration setup and troubleshooting guidance
• Coverage Analysis: Understand which parts of your infrastructure are being monitored and identify gaps
• Performance Metrics: Query integration performance, data ingestion rates, and connection health

Documentation-Aware Assistance:

• Context-Aware Documentation: Ask Causely can now answer questions directly from Causely's extensive documentation
• Feature Guidance: Get help understanding how to use specific Causely features and capabilities
• Best Practice Recommendations: Receive expert advice on configuration, setup, and optimization
• Troubleshooting Support: Access step-by-step guidance for common issues and advanced scenarios

This enhancement makes Ask Causely your comprehensive assistant for both operational troubleshooting and platform guidance, reducing context switching and accelerating problem resolution.

Enhanced Root Cause Management

Managing and analyzing root causes becomes more powerful with new filtering and historical analysis capabilities:

Priority Filtering and Tagging:

• Priority-Based Filtering: Filter root causes by priority levels to focus on the most critical issues
• Tag-Based Organization: Use custom tags for root causes for better categorization and filtering
• Enhanced Search: Quickly find specific root causes using tag and priority filters

Historical Analysis:

• Custom Date Filters: Analyze root causes across any custom date range for historical insights
• Trend Analysis: Identify patterns and recurring issues over time
• Historical Context: Better understand how root causes have evolved and been resolved

These capabilities help teams prioritize incident response and gain insights from historical patterns.

Mediation Insights: Understanding Your Causely Setup

Causely now provides comprehensive visibility into its own operations, giving you clear insights into how your Causely deployment is working and what it's discovering in your environment:

See What Causely Knows About Your Environment:

• Discovered Entities Overview: Get a clear picture of all the services, databases, load balancers, and infrastructure components that Causely has discovered
• Discovery Progress: Track which parts of your infrastructure Causely is actively monitoring and identify any gaps in coverage
• Setup Validation: Understand whether your Causely installation is working as expected and discovering the entities you expect it to find
• Environment Coverage: See the full scope of what Causely is monitoring across your entire system

Monitor Causely's Health and Performance:

• Integration Status: Check the health of all your configured data sources and integrations
• Connection Monitoring: See which external systems (monitoring tools, databases, cloud providers) Causely is successfully connecting to
• Processing Performance: Monitor how efficiently Causely is analyzing your telemetry data and generating insights
• System Resource Usage: Track Causely's own resource consumption and performance metrics

These self-insights gives you confidence that Causely is working correctly, helps you optimize your setup, and ensures you're getting comprehensive coverage of your infrastructure.

Enhanced eBPF Instrumentation with Beyla 2.6

Causely now leverages Grafana Beyla 2.6, bringing significant improvements to automatic instrumentation capabilities:

New Beyla 2.6 Features:

• Improved MongoDB Instrumentation: Enhanced support for MongoDB monitoring and trace collection
• Advanced Service Discovery: Better automatic discovery of services and applications
• Enhanced OpenTelemetry Integration: Improved compatibility with OpenTelemetry ecosystem components
• Stability Improvements: Various fixes and enhancements for more reliable instrumentation

Enhanced Integration Capabilities:

• Configurable OpenTelemetry SDK: More flexible configuration options for telemetry collection
• Improved Metrics Collection: Enhanced metrics gathering through OpenTelemetry protocols
• Advanced Discovery Configuration: Fine-tuned discovery settings for different deployment scenarios

This upgrade ensures that Causely's automatic eBPF-based instrumentation remains at the forefront of eBPF-based observability technology.

Did you know?

Causely works with virtually any programming language because it's built on OpenTelemetry, the industry-standard observability framework. OpenTelemetry provides native instrumentation libraries for all major languages including:

• Java
• .NET
• Go
• Python
• JavaScript
• C++
• Rust
• PHP
• Ruby
• Swift
• Erlang/Elixir
• ... and many more.

Whether your applications are already instrumented with OpenTelemetry or you're just getting started, Causely can help:

• Want to get started quickly? Use Causely's automatic eBPF-based instrumentation for zero-code observability
• Already using or rolling out OpenTelemetry? Learn how to integrate with OpenTelemetry alongside your existing rollout

This flexibility means Causely can provide root cause analysis regardless of your technology stack or observability maturity.

Bug Fixes and Minor Improvements

This release includes numerous enhancements and fixes across the platform:

• Incident.io Integration: Added support for Incident.io auto-mapping and integration for enhanced workflow management
• Improved Notification System: Fixed notification ordering and enhanced support for multiple owner notifications
• Enhanced Performance: Resolved race conditions, improved queue processing, and better latency threshold calculations
• Better Visualization: Improved topology graphs with bidirectional edges and enhanced root cause naming for AWS ALB and GCP load balancers

August 29, 2025

Version 1.0.90

Enhanced Impact Understanding with Blast Radius Analysis

Understanding the scope and potential impact of a root cause is critical for effective incident response. Causely now provides comprehensive Blast Radius Analysis that gives you a clearer understanding of both the current and potential impact of every root cause.

Key capabilities:

• Current Impact Assessment: See exactly which services are currently affected by a root cause and how the issue is propagating through your system
• Potential Impact Prediction: Understand which additional services could be impacted if the root cause persists or worsens
• Risk Assessment: Evaluate the broader implications of each root cause to prioritize response efforts effectively
• Visual Impact Mapping: Clear visualization of impact scope helps teams align on response priorities and resource allocation

This enhanced impact analysis ensures teams can make informed decisions about incident response priorities and resource allocation, leading to more effective incident management.

Datadog Alert Auto-Mapping for Trusted Signal Integration

Causely now automatically maps Datadog monitors to corresponding service symptoms, enabling you to leverage your existing curated signals for enhanced root cause analysis.

For organizations that have invested in creating reliable Datadog alerts and monitors, this integration provides a powerful way to incorporate those trusted signals into Causely's causal reasoning engine.

Key benefits:

• Leverage Existing Investments: Utilize your carefully curated Datadog monitors and alerts within Causely's causal analysis
• Enhanced Signal Quality: Combine Causely's automatic discovery with your domain expertise encoded in Datadog alerts
• Faster Root Cause Identification: Trusted signals accelerate the path from symptom detection to root cause identification
• Seamless Integration: Automatic mapping requires no additional configuration—Causely intelligently correlates Datadog alerts with service symptoms

This capability is particularly valuable for teams who have developed sophisticated monitoring strategies in Datadog and want to enhance their root cause analysis capabilities.

Improved Dataflow Visualization and Topic Metrics

We've enhanced Causely's ability to understand and visualize complex asynchronous data flows across your distributed systems:

Enhanced Topic Metrics:

• Comprehensive Topic Monitoring: Better visibility into message queue performance and throughput
• Producer-Consumer Relationships: Clear mapping of data flow relationships between services through messaging systems
• Queue Depth Analysis: Monitor queue depths and identify potential bottlenecks in asynchronous processing

Improved Flow Visualization:

• Directional Flow Mapping: Enhanced visualization of data flow direction between topics, tables, and services
• End-to-End Tracing: Follow data flows from producers through topics to consumers with improved clarity
• Performance Correlation: Better correlation between data flow metrics and service performance impacts

These improvements provide deeper insights into how data moves through your systems, making it easier to identify bottlenecks and performance issues in event-driven architectures.

Aggregated Pod-Level Metrics

Causely now provides enhanced pod-level observability with aggregated metrics that give you better insights into container performance:

Enhanced Pod Visibility:

• Aggregated Resource Metrics: Combined view of resource utilization across related pods
• Node-Container Relationships: Improved tracking of how containers relate to their host nodes
• Performance Correlation: Better correlation between individual pod performance and overall service health
• Resource Optimization Insights: Clearer understanding of resource usage patterns to inform optimization decisions

This enhancement provides more granular visibility into your containerized workloads while maintaining the broader service-level context that's crucial for effective root cause analysis.

Location-Based Notification Routing

Organizations operating across multiple regions or locations can now route root cause notifications to different destinations based on where entities are located:

Key Features:

• Geographic Routing: Automatically route notifications based on entity location or region
• Multi-Region Operations: Support for organizations managing infrastructure across different states, countries, or data centers
• Customizable Routing Rules: Configure notification destinations based on entity labels, namespaces, or other location indicators
• Operational Efficiency: Ensure the right teams receive notifications for incidents in their operational domain

This capability is particularly valuable for organizations with distributed operations teams who need location-specific incident routing to ensure fast response times and appropriate escalation paths.

Did you know?

Even without an active root cause, you can drill down into a service and get a list of potential root causes that could be impacting it, and a list of symptoms across entities that could be indicative of those root causes. This enables you to assess risk and prioritize response efforts effectively.

Bug Fixes and Minor Improvements

This release includes numerous stability improvements and enhancements across the platform:

• Database Performance: Improved database headline scanning for better performance and reliability
• Entity Management: Enhanced handling of entity data request pathways with status tracking
• Cloud SQL Stability: Improvements to cloud-sql proxy for more stable database connections
• Memory Management: Enhanced memory noisy neighbor detection with additional condition checks
• Notification System: Improved notification routing per mediator for better distribution
• Network Metrics: Enhanced collection of basic network metrics for improved observability
• Entity Relationships: Better management of node-container relationships in the mediator
• eBPF Instrumentation: Upgraded to Beyla 2.5 for improved automatic instrumentation capabilities
• Entity Configuration: New database table and APIs for enhanced entity configuration management
• Manifestation Handling: Improved handling of manifestations for deleted entities
• Redis Performance: Enhanced Redis queue performance for better system responsiveness

August 25, 2025

Version 1.0.89

New Features

Docker Host Installation Support

Causely now offers a new streamlined installation option for Docker hosts. This installation method enables telemetry collection and root-cause analysis for containerized services on any Docker-enabled host, complementing our existing deployment options.

Key capabilities:

• eBPF-based telemetry collection for Docker containers
• Root cause analysis for services running on Docker hosts
• Easy setup with automated installation scripts
• Support for privileged container deployment with host PID access

Learn more about setting up Causely on Docker hosts in our Docker Host Installation guide.

Multi-Database Support for MySQL and PostgreSQL

Causely now supports multiple MySQL and PostgreSQL databases using the same secret configuration. This allows you to monitor multiple databases with the same credentials, reducing the need for separate secret management.

Learn more about setting up multiple MySQL and PostgreSQL databases in our MySQL Configuration guide and PostgreSQL Configuration guide.

Did You Know?

Streamline incident response with CauselyBot webhook integration

Causely can automatically forward root cause notifications to your preferred collaboration tools through CauselyBot, our open source webhook service. CauselyBot receives authenticated payloads from Causely and intelligently routes them to platforms like Slack, Microsoft Teams, and OpsGenie.

Key capabilities include:

• Smart Filtering: Configure custom filters based on severity, entity type, SLO impact, or root cause name to ensure teams only receive relevant notifications
• Multiple Destinations: Route different types of incidents to appropriate teams—send critical database issues to the DBA team while routing general service degradations to the on-call engineers
• Secure Authentication: Built-in bearer token validation ensures only authorized notifications reach your systems
• Easy Deployment: Available as Docker containers or Helm charts for seamless integration into your existing infrastructure

This enables faster incident response by delivering actionable context directly to the tools your teams already use, reducing mean time to resolution and improving collaboration during critical incidents.

Bug Fixes and Minor Improvements

This release focuses on stability improvements and bug fixes across the platform:

• Impact Graph Resilience: Improved impact graph calculation to handle missing services gracefully, resulting in faster loading of the impact graph UI.
• Database Health Checks: Added comprehensive health checks for cloud-sql-proxy and ping-check database connections for improved monitoring.
• Redis Span Enhancement: Improved Redis span collection for better distributed tracing coverage.
• Service Impact Calculation: Improved accuracy of service impact calculations to address scenarios where impact was too broad.
• Entity Deletion Handling: Improved logic for handling deleted entities in the system. For example clusters or namespaces that have been removed, will no longer be shown in the topology.
• Copilot Improvements: Various enhancements to the Causely Copilot functionality.

More Releases

Go to the changelog page.