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Paragon Insights

Juniper
Translate real-time analytics into actionable insights.
Datasheet
Datasheet
  • Collect and normalize data across standards-based collection methods, including UDP, OpenConfig and gNMI streaming Telemetry, gRPC, SNMP, NETCONF, CLI, Syslog, NetFlow, custom-defined ingest, or ingest from your own data lake.
  • Dynamically masters the baseline performance of infrastructure elements and network applications for anomaly detection, outlier detection, predictive analytics, and network resource optimization.
  • Paragon Insights is a critical component of Juniper’s intent-based networking solution, providing critical historical and predictive analytics.
  • Paragon Insights provides customizable analytics through YANG-based playbook definitions and user-defined functions, along with seamless integration with Kafka, Webhook, Slack, REST APIs, and HBEZ/HBEZGo (for Python and Go libraries) for data ingestion, analytics, and notifications.
  • By combining the power of fine-grained telemetry and analytics with workflow automation, Paragon Insights automates root cause analysis and performs corrective actions based on predefined KPIs
  • By providing visualized details about network logs, health status, outliers, and behavior, Paragon Insights improves capacity planning while eliminating service downtime.
  • Paragon Insights playbooks, which can be created by Juniper, the Paragon Insights user community, and end users like you, provide holistic solutions for EVPN-VXLAN, Microburst detection, Juniper Networks SRX Series Services Gateway security, L3VPN monitoring, and more

Paragon Insights (formerly HealthBot) is a network health and diagnostic solution that provides operational intelligence across all service provider, cloud, and enterprise network domains, from network access to servers in the data center.

Paragon Insights supports multiple open-source data collection formats, including Junos telemetry interface (JTI) and standards-based OpenConfig telemetry. Once collected, built-in advanced algorithms and machine learning (ML) technology correlate these data sources, establish operational benchmarks, determine anomalies, and perform proactive corrective actions—all critical to intent-based networking. By translating real-time analytics into actionable insights, Paragon Insights provides you with a multidimensional view across your network and its application layer services.

The automated analytics capabilities of Paragon Insights give you the power to easily monitor and continually evaluate your network infrastructure, bringing substantial improvements in root cause analysis while simplifying operations. This integrated approach democratizes the use of network and service analytics and ultimately inspires collaboration for business agility and growth.

Paragon Insights is cloud native and can be deployed in highly available configurations across private data centers and public clouds. An intuitive web-based dashboard eliminates operational complexity, extracting telemetry data into a single view. YANG-based health and root-cause analysis modeling enables you to extend and customize KPIs. Open programmability supports customized playbooks, enabling highly tailored health monitoring and diagnostic workflows.

featureBlockTitlefeatureBlockBody
ML and Advanced AlgorithmsApplies ML to dynamically master the baseline performance of infrastructure elements and network applications; proactively triggers corrective actions when real-time metrics deviate from configured tolerance levels.
Health Monitoring and Network AnalyticsProvides an aggregated and abstracted view of network health, correlating raw streaming telemetry data into a multidimensional view of the health and projected risk of your infrastructure and its workloads.
Closed-Loop AutomationEnables highly customized policies and playbooks through a functional drag-and-drop web interface; intelligently automates diagnostic workflows and sustains overall performance goals.
Cloud-Native PlatformProvides deployment flexibility, supporting VMs and containers across private data centers and public or private clouds with a highly available, highly redundant, scale out architecture.
Datasheet
Datasheet