SOLUTIONS / NETWORK HEALTH
Connect the Dots Across Any Data with The Selector Network Health Solution
Operations teams are struggling to achieve their KPIs because it takes too long to triage outages and performance problems.
The main reasons are too many siloed tools that require manual correlation, and lack of collaboration. Selector’s Usable AIOps is the first analytics solution to provide instant actionable insights to manage multi-domain network and application infrastructure.
The Selector Network Health Solution
The Selector Network Health solution is a fundamentally different and new solution that connects the dots across any data type or source to rapidly isolate any existing abnormal network conditions and ranks incidents so operations teams can quickly focus triage efforts for rapid
Reduces mean time to innocence (MTTI)
by rapidly establishing that the network is behaving as it normally does.
Reduces mean time to detection (MTTD)
by eliminating noise and highlighting high-ranking issues
Reduces mean time to repair (MTTR)
by rapidly enabling action through immersive collaboration, automation, & dashboard actions
Observability is used to mean everything from receiving alerts to automating remediation. Selector defines observability as a new generation of insight that is created by correlating information from multiple data sources and data types. For example:
- BGP log messages with availability and performance metrics
- Configuration changes with abnormal conditions
- Synthetic testing data with abnormal conditions
The power of the Selector Analytics architecture is the ability to easily evolve by ingesting and analyzing any data, and rapidly generating actionable insights.
Operations teams are buried under a mountain of inaccurate alarms and status indicators.
The reasons for this are many, including how legacy approaches to network health create and maintain thresholds. This is either manual, creating significant overhead for the operations team, or based on noise generating heuristics.
A new approach is taken by the Selector Network Health solution. Machine learning is used to create a prediction of what a threshold should be set to, and when that prediction is not realized, then alerts are created. Selector customers are finding this provides a much clearer view of actual network health.
Service Restoration & Remediation
When abnormal conditions arise, operations teams have two main directions to pursue:
Rapid anomaly detection and triage is critical, regardless of whether service is restored with or without first doing root cause remediation. Focus operations teams on the most important and impactful issues dramatically reduces the time to service restoration.
In either service restoration or remediation, Selector Analytics can invoke an automation webhook, execute its own automation playbook, or an operator can initiate an action from the portal.
They can accept there is an anomaly that will not quickly be resolved and work around the problem
They can attempt to correct the cause of the problem, either after or during service restoration
The Selector Network Health solution dramatically reduces MTTI, MTTD, and MTTR.
Overall network health is easily viewed, a new more powerful approach to anomaly detection is combined with ranking to focus operations teams, and automation can be achieved through manual command, webhook, or integrated playbook.
Collect from Various Data Sources
Ingest variety of data sources in various formats
Correlate Metrics & Events
Machine Learning based data analytics for automated anomaly detection
Collaborate Across Boundaries
Instant actionable insights on collaborative platforms using Natural Language Queries (NLQ)
24×7 Product support
A fully interactive web portal with on-demand dashboards
Selector AI can be deployed in three possible modes – public, private, and cloud VPCs