Contextual Network Observability Powered by AI-Driven Automation
Network observability is no longer just about collecting raw log, metric, and telemetry data. NetBrain delivers contextual network observability by combining real-time visibility, intent-based automation, and AI-driven diagnostics to continuously diagnose, validate, and remediate hybrid and multi-cloud networks.
Put Observability Data to Work with AI-Based Automation
Make sense of raw observability data using deep network visibility, intelligent automation, and agentic AI.
Ultimate Network Visibility
Gain clear visibility for your hybrid network with on-demand, dynamic maps, one-click Word documents powered by agentic AI, and inventory reports.
Proactive Network Observability
View application, security, config drift, what’s changed, and past outages data in map-based summary observability dashboards—completely customizable and shareable.
24/7 Digital Network PhD
Augment your engineers with agentic AI that reasons like a senior engineer to automate root cause analysis, summarize findings, and dramatically accelerate MTTR.
Transform Observability into Action
Human Intelligence, at Machine Speed
NetBrain turns observability into a strategic asset—ensuring optimal health, performance, and security across your hybrid environment.
| Functionality | Network Observability | Network Automation |
|---|---|---|
| Primary Goal | Visibility, monitoring, and data collection. Answers “What is happening and why is it happening?” by providing a comprehensive, correlated view of the network’s state. |
Action, enforcement, and orchestration. To leverage observability data for automated root cause analysis, remediation, and enforcing the desired state through policy application. |
| Real-time Visibility | Yes, through continuous telemetry streaming, flow analysis, and metrics aggregation. Provides the raw, granular data layer. |
Yes, but focused on the operational outcome. Uses map-based dashboards to visualize automation results, policy compliance status, and the health of the automated remediation pipeline. |
| Root Cause Analysis (RCA) | Correlates data to identify symptoms and potential causes, often using AI/ML for anomaly detection and pattern recognition. Finds the “what.” |
Can automate RCA and remediation via predefined runbooks and intent-based policies. It acts on the “what” by executing the “how” to fix it (e.g., “if latency spike on Path A, reroute via Path B”). |
| Hybrid-Cloud Understanding | Yes, via agent or agentless collection from diverse endpoints (on-prem devices, cloud VPCs, SaaS applications). |
Yes, achieved through API integration with cloud providers and SDN controllers. Applies consistent policies across domains, translating high-level intent into domain-specific configurations. |
| Prevention & Remediation Capability | Alerts on trends and anomalies. Enables proactive human intervention but does not act autonomously. |
Can auto-remediate common issues and proactively enforce intent (e.g., “always maintain two available paths”). Prevents drift by continuously reconciling actual state with declared policy. |
| Agent Requirement | Often agentless (SNMP, NetFlow/IPFIX, API polling), but can use lightweight agents for deep service or application visibility. |
Execution can be agent-based (on-box configuration) or agentless (via API). The policy engine is typically a central service. |
| Change Management | Tracks changes in performance and state, detecting drift from baselines. Acts as a passive auditor of change impact. |
Automates changes and validates pre- and post-state against policies. Acts as the active executor ensuring consistency and correctness. |
| Coding / Development Need | Usually low-code or no-code for core functions (queries, dashboards, alerts). Advanced use cases may require scripting. |
Ranges from no-code (GUI-driven runbooks, intent forms) to full code (IaC, APIs, Python playbooks). Policies are defined as code. |
| Core Mechanism | Data Pipeline: Collect → Correlate → Visualize → Alert | Control Loop: Observe → Decide (Policy) → Act → Verify |
How Does Network Automation Enhance Network Observability?
NetBrain doesn't just monitor—it understands. By continuously auto-discovering and mapping your entire hybrid, multi-vendor environment, we build a living digital twin of your network. This real-time map becomes the foundation for true observability, where every device, path, and configuration is contextualized and correlated.
Continuous Discovery & Dynamic Mapping
Automatically discover every device and maps each connection in real time, delivering an always-accurate, live view of your hybrid, multi-vendor infrastructure, including edge-to-cloud application paths and golden configurations.
Intent-Based Network Validation
Define how your network should perform to support business services. NetBrain continuously validates live behavior against your unique intents, automatically detecting and flagging deviations before they impact users.
Contextual Observability Dashboards
Move beyond isolated alerts. Intelligent dashboards correlate topology, configuration, and performance data into a unified view that reveals not just what’s happening, but why—turning raw data into actionable insight.
Automated Diagnostics & Remediation
When issues arise, observability tools trigger NetBrain to automatically investigate, perform root-cause analysis, and run diagnostics—delivering answers, not more questions. The platform can even trigger pre-built remediations to resolve problems without manual intervention.
Centralized Collaboration Hub
Every insight, analysis, and diagnostic result is captured and summarized in the platform, transforming observability data into shared intelligence for your entire team.
True Observability Through Automation
Go beyond monitoring by turning data into intelligence. Operating directly on the management plane, NetBrain collects rich telemetry to fuel no-code automation, continuously validating performance and compliance while accelerating troubleshooting and maintaining resilience.
Why Pursue Network Observability with NetBrain?
NetBrain transforms network observability by turning raw data into actionable intelligence. By combining intent-based automation with dynamic mapping, it creates a live, continuously updated view of your entire hybrid network.
Key Advantages:
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Dynamic Network Mapping: Auto-discovers and maps multi-vendor environments in real time, providing an up-to-date digital twin of traffic paths and infrastructure health.
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Actionable Dashboards: Move beyond basic alerts with contextual insights and on-demand analysis from a unified view.
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Intent-Based Validation: Continuously checks network behavior against defined business intents, automating the validation of performance and compliance.
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Proactive Diagnostics: Triggers intelligent troubleshooting and centralizes insights for faster root-cause analysis and team collaboration.
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Management Plane Telemetry: Goes beyond limited SNMP by operating directly on the network management plane, fueling no-code automation with rich, actionable data.
NetBrain delivers deeper visibility into network behavior and health automatically, enabling earlier problem detection and a more resilient network.
Frequently Asked Questions
- What is network observability?
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Network observability is the ability to continuously visualize and understand the state and behavior of a network using real-time data. It goes beyond monitoring by providing contextual insight into performance, configuration, and network health.
- How does network observability differ from network monitoring?
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Network monitoring focuses on collecting metrics and alerts, while network observability explains why issues occur by correlating topology, configuration, and telemetry. Observability enables proactive troubleshooting rather than reactive alert handling.
- How does NetBrain deliver network observability?
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NetBrain uses a dynamic Digital Twin to model the live network’s state and configurations from across hybrid and multi-cloud environments and collects real-time telemetry data. It then provides dynamic mapping and pathing. Leveraging data from observability tools and its network knowledge, it turns observability topology, traffic paths, and performance metrics into actionable validation and remediation workflows.
- What are the benefits of AI-driven network observability?
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AI-driven network observability enables faster troubleshooting, proactive issue detection, and automated remediation. It reduces operational risk by continuously validating network health and performance at machine speed, and presents the results in summary dashboards.
- How does NetBrain compare to other tools?
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Unlike Dynatrace, SolarWinds, and Cisco ThousandEyes, which focus mainly on monitoring, observability, and performance metrics, NetBrain takes a fundamentally different approach: it focuses on network automation, intelligent documentation, and actionable troubleshooting.
While other platforms excel at collecting and alerting, NetBrain excels at understanding and acting:
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Dynatrace tells you: *”The payment service has 5-second latency originating from Database Cluster A.”*
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ThousandEyes tells you: “The path to your AWS VPC has 200ms of latency in the Verizon backbone.”
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SolarWinds tells you: *”Router-Core-01 has 95% CPU utilization and 3 interfaces are down.”*
NetBrain does something fundamentally different: It automatically maps the exact network path, retrieves real-time configurations from every device along that path, executes diagnostic commands, and can even run predefined remediation scripts—all within its live, interactive network diagram.
Importantly, NetBrain doesn’t replace these monitoring tools—it complements and amplifies them. It consumes alerts from Dynatrace, SolarWinds, or ThousandEyes and then provides the network-layer context and automation needed to resolve those alerts quickly. It’s the bridge between knowing something is broken and actually fixing it, especially when network configuration or topology is involved.
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- What NetBrain automation solutions support observability?
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- Dynamic network mapping: Continuously visualize the live network and service paths for enhanced visibility across hybrid environments.
- Intent-based automation: Verify that the network is behaving as designed by checking against defined intents.
- Triggered diagnostics: Automatically run root cause analysis when NetBrain detects alerts or anomalies from monitoring tools, giving you actionable insights.
- Proactive health and security checks: Automate pre-, during-, and post-event assessments to detect issues before they impact performance or SLAs.
- Centralized dashboards and incident portals: Consolidate all automation outputs, diagnostics, and maps for end-to-end observability during incident response.
- Can network observability work across hybrid and multi-cloud environments?
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Yes. Network observability platforms like NetBrain continuously discover, map, and analyze hybrid and multi-cloud networks, providing a unified, real-time view across on-premises, cloud, and edge environments.
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