Ensuring Core Business Continuity
Tool Usage
Uses various observability tools to complete work ensuring business continuity
Observability
All reasoning decisions are based on complete business observability
Customized
Tailored reasoning scenarios that create unique value for enterprises
Rich Usage Scenarios
Minute-Level Diagnosis
DeepFlow Agent with 99.99% accuracy rivals a senior technician, autonomously using various observability tools to provide clear problem identification and solutions, achieving 1-minute location, 5-minute trace, 10-minute recovery, defending the enterprise's digital lifeline.
Continuous Inspection
DeepFlow Agent replaces your night shift, providing 7x24 intelligent inspection, continuously outputting health and unhealthy analysis reports, achieving early detection and prevention, reducing manual inspection costs, making troubleshooting AI's responsibility and innovation humanity's.
One-Sentence Query
DeepFlow Agent assists you in quickly responding to key indicator queries and summaries, providing clear and complete analysis insights. In just a few minutes, it analyzes the system's past and real-time status, saving significant team collaboration and data analysis waiting time. Analysis reports help you spot key points at a glance, find optimization paths for events, and assist leaders in making correct decisions!
Core Technology
Zero-Intrusion Collection
Through the integration of cBPF, eBPF, Wasm and other technologies, we achieve zero-intrusion data collection for large-scale distributed businesses and infrastructure, solving the complete observability problem of DeepFlow Agent's operating environment.
SIGCOMM: "Network-Centric Distributed Tracing with DeepFlow: Troubleshooting Your Microservices in Zero Code"
Thought State Machine
Through Chain of Thought guidance, it can solve hallucination problems caused by large model reasoning. However, as business and scenarios continue to change, the complexity of thought chains increases exponentially. By using hybrid state machine technology based on DFA + NFA, we can effectively solve the state space explosion problem caused by thought chain complexity.
JNCK: "A pattern partition based engine for fast and scalable regular expression matching in practice"Adaptive Perception
Adaptive perception technology implements hybrid perception technology combining pre-reasoning perception and in-reasoning perception. Pre-reasoning perception technology includes real-time feature extraction and classification of data, while in-reasoning perception technology combines business scenarios for on-demand specific feature extraction and classification of data. Adaptive perception technology allows users to continuously optimize between cost and performance, avoiding uncontrollable computing resource investment.
Implementation Process
01
Data CollectionData Collection
02
Business ReviewBusiness Review
03
Scenario OptimizationScenario Optimization
