The journey into the future of AI Network Experts begins here
Buckle up. You are about to unveil the secrets of modern AIOps Networks
Buckle up. You are about to unveil the secrets of modern AIOps Networks
(1) Agentless data ingestion & Intelligent pre-processing
(2) Proactive Anomaly Detection
(3) Intelligent data routing
(4) Multi-dimensional event auto correlations
(5) Auto-remediation
(*) Digital Twin for “What If Analysis”
SliceUp automates data collection and onboarding, so you can enjoy its benefits right away.
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Scalable Data Ingestion Through APIs
supporting Syslog, SNMP, Synthetic Traffic, DPI, Kafka, and others
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Real-time Log Parsing Automation
dynamically identifies static and variable parts of logs. No more rigid regex/grok
L1/L2 Network Topology Auto-discovery
through existing and/or proprietary SNMP collection systems
Once the data is onboarded, SliceUp analyzes it, looking for anomalies.
Over ten domain-specific ML models
for Traditional and GPU/HPC Data Center as well as WAN use cases
The meta-model ranks the criticality of the incidents and prioritizes what matters most
"Human on the Loop" provides feedback to ML models the system can constantly learn and improve
SliceUp can automate data re-routing to different types of storage for cost optimization and remove human bias from the process.
>95% of telemetry data tells you: "Everything is fine". SliceUp forwards it to a cheaper storage option
<5% of data is abnormal. SliceUp detects it and forwards it for further correlations and analysis.
No manual processes, no human bias. Let the SliceUp system decide which data is worth the hustle
Anomalous events are forwarded to SliceUp's auto-correlation engine, which understands contextual network relationships. It enables more accurate results for root cause analysis.
Event correlations across multiple dimensions like time, topology, sites, etc
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Correlations across multiple telemetry domains and high fidelity data sources
"Human on the Loop" to provide learning feedback and adjust correlation strengths
SliceUp distinguishes between anomalies and routine issues. Routine issues like duplex mismatch or cert expired can be automatically remediated with Ansible scripts.
Streamlined remediation workflow
with three levels of automation - silent, manual, and auto
Auto: Automatically opens a ticket and runs an attached script. Manual: Opens a new ticket and queues script for review and execution later
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Auto-remediation workflow is triggered the next time the incident that matches the pattern is detected
Auto-discovered Network Topology. SliceUp integrates with existing SNMP data collection systems to auto-discover your network topology. By overlaying key metrics on an always current topology, network administrators can easily find where the future problems are.
Plan Ahead - Get Proactive: SliceUp allows you to withstand the next big product launch or a black swan event. Proactively mitigate the risk based on modeled scenarios and take the appropriate action - add additional links, increase bandwidth, or re-route traffic.
Identify Resources Needed. SliceUp's "what if calculator" models different future scenarios to identify bottle necks and see which interfaces may become over utilized if traffic increases, adjusted for risk. Examples of metrics measured: Interface Utilization, TCAM, Memory.
