Network Operations teams have multiple significant Network Tool Complaints. Addressing these complaints requires a clean page AI/ML, cloud-native approach that delivers significant improvements well beyond monitoring and observability
Regardless of where Network Operations teams are on their monitoring, observability, and AIOPs journey, Network AI is the leading platform, available on-Prem or as SaaS
The above Network Operations pain points are just a few of the pain points addressed by Augtera’s Network AI.
The above Network Operations pain points are just a few of the pain points addressed by Augtera’s Network AI.
The above Network Operations pain points are just a few of the pain points addressed by Augtera’s Network AI.
The above Network Operations pain points are just a few of the pain points addressed by Augtera’s Network AI.
The above Network Operations pain points are just a few of the pain points addressed by Augtera’s Network AI.
The above Network Operations pain points are just a few of the pain points addressed by Augtera’s Network AI.
Augtera’s Network AI is purpose-built for today’s Hybrid IT challenges. Cloud-native, geo-diverse, and horizontally scalable with a simple per device license structure, makes Network AI the ideal, next-generation replacement for SolarWinds patchwork of poorly integrated acquisitions. Collect any data source at scale, use AI/ML to learn patterns and discover anomalies, prevent future incidents, reduce redundant alerts/tickets, identify incident root, create trouble tickets, use your own python automation playbooks, and more. The table below illustrates some of the significant differences between a legacy tool and a forward-looking platform. Capability Network AI SolarWinds Comment Configurable dashboards Yes Yes With widgets Dashboard export in HTML Yes Yes For third-party integration Ticketing Yes Yes Example Service Now. SNMP, Flow data, Syslog Yes Yes Performance limitations for SolarWinds Static Topology Ingestion Yes Yes – Multi-vendor support Yes Yes Arista, Cisco, Juniper, Dell, F5, VMware, other JSON logs, Streaming Telemetry, Kafka, platform API Yes No Industry directions & Integration On-Prem Yes Yes Good for rare Enterprises with acute operations data concerns SaaS Yes No SaaS relieves network tooling management burden from Network Operations Team ML-based anomaly detection Yes No Learns patterns rather than using thresholdsReduces false positives.Eliminates threshold maintenance burden Multi-layer auto-correlation Yes No Eliminates redundant alerts / ticketsQuickly identifies incident root Application Flow and Underlay Correlation Yes No Reduces time to innocence & arguing with application teams about performance issues High-frequency probes Yes No Reduces identification time for latency and other probe metrics Real-time rare log message identification Yes No Allows Network Operations teams to prevent incidents before they occur Real-time rate-based anomaly detection Yes No Change of log message rate, for example bursts, indicate anomalies Real-time Classification Yes No Network operations teams can take action based on any log signature Real-time Metric extraction Yes No Metrics embedded in log messages can be placed in time-series, analyzed, and use real-time anomaly detection algorithms Cloud-native Software Architecture Yes No Align with broader IT software directionsTake advantage of agile and scalable micro-services Geo-diverse active-active Software Architecture Yes ? High-availability whether due to software failure or software upgrade To learn more about Augtera’s Network AI:
Beyond Monitoring With millions to billions of streaming data points per day, can Network Operations teams : Beyond Observability With millions to billions of streaming data points per day, can Network Operations teams : Network AIOps Not IT AIOps. Purpose-built AIOps for Network Operations teams. Network operations automation from ingestion to notification / action. Let us be your Level 1, 2, & 3 AI/ML team The future is now. Learn more:
