Log Analysis

The Problem
Monitoring systems comprised of multiple services is typically done by monitoring each service individually using it's logs, or on an end to end basis that lacks visibility into the individual performance characteristics of each service. Root cause analysis is usually based on operations personnel instinct and past experience, making automated remediation next to impossible for many use cases.
The Solution
With thatDot's streaming graph logs and events from servers, operating systems, databases, applications, and clients are ingested in real-time and assembled into a graph data model. The graph data model natively connects events with unlimited categorical classifications and calculated metrics to identify "alerts that matter" and instantly associate them to servers, VMs, containers, code versions, subnets, etc. This real-time comprehensive view of the inter-relationships between services allows rapid assessment of root causes for operations investigations or automated remediation workflows.

Key Value Delivered

Identify issues that matter, in real-time and at scale
Graph data modeling eliminates the complexity of deeply nested joins
NOC technicians can easily pivot data to understand issue impacts and root causes
Automatic handling of out-of-order data arrival
Entity resolution between log and event sources
Integrates with existing Apache Kafka, AWS Kinesis, data lake, and API event sources

What people are saying

thatDot Platform’s advanced Novelty Scoring for categorical data feature is the future of anomaly detection. Its speed powers our new real-time services while also significantly reducing false-positive findings for our customers.

Gery Szlobodnyik

CEO

The security industry is headed towards leveraging knowledge graphs of all the relevant evidence provided by threat groups, network indicators and endpoint artifacts to quickly identify and mitigate threats. The security companies that can most confidently extract relevant context from these graph and then immediately action on findings to mitigate threats will be the winners. This is exactly the problem Quine aims to address.

Evan Wright

Staff Data Scientist

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If you think Streaming Graph or Novelty might be for you, contact us to see them in action.

Log Analysis

The Problem

The Solution

Key Value Delivered

Recent posts

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4 Advantages to Streaming Analytics in Graph Form

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