Webinar Abstract

The rise of Edge Computing and Multi-cloud deployment has exacerbated the challenges around the 4V’s of the data – Volume, Velocity, Veracity, and Variety. The traditional approach of Collect ->Store ->Search results in data stores results in data swamps, due to repetitive and redundant data, without many actionable insights. Traditional search tools need data to be ingested, indexed, and then searched using proprietary query languages, creating data silos.

Log Intelligence as a Service, is very effective in implementing cyber security mandates for log retention, and preventing security breaches by optimizing Security Incident and Event Management(SIEM), predictive business analytics, incident response, cloud automation, and orchestration.

Existing Log Analytics solutions ingest repetitive and redundant data which drives licensing TCO exorbitantly high, drives compute and storage infrastructure costs, and most importantly results in poor MTTI and MTTR.

Attendees of this webinar will learn:

Log Intelligence overcomes these challenges, by reducing TCO by 40-80% , improving MTTI/MTTR by over 60% and productivity by over 40% as follows

• Log Ingestion - Bring your own Log Tool ( BYOL) and ingest data in pull/push/batch modes
• Log Reduction and Replay – Up to 40-80% log volume reduction using correlation techniques and replay using UTC timestamps, IP addresses, and certain patterns, to your choice of stream
• Log Routing – Aggregate logs, normalize, transform, enrich, and route to multiple locations - Data Lakes, log stores, analytic platforms, Composable dashboards and more.
• Log Enrichment – Enrich logs using Geo-IP or DNS lookups from Infoblox, CVE( Common Vulnerability and Exposure) feeds, TIP (Threat Intelligent Platform) feeds
• Log Predictive Analytics – Convert logs into metrics and use a number of regression AI/ML models for anomaly detection
• Edge IoT, In-place Search - Composable Search compliments Log Intelligence service. Collect and store only valuable data as a full-fidelity copy in Observability Data Lake and In-place search as needed on security breaches and compliance needs