TiFlow Microprobe

Background

In cloud, cloud native, and cross architecture security, operation, and monitoring scenarios, multi-dimensional and fine-grained traffic and asset data are required; Especially in AI analysis for security, there is a greater need for high-quality traffic log data;

However, due to the dynamic, lightweight, and sensitive characteristics of the cloud environment, it is not easy to obtain this data without affecting business and hosts, and without pressure on the cloud environment and network bandwidth.

1. Highly integrated standalone featherweight program

In an standalone program with only 800KB, all functions including packet capture, session reassembly, content extraction, KPI calculation, JSON encapsulation, communication forwarding, and configuration management have been completed;

2. Higher performance, lower resource consumption

Excellent architecture and coding capabilities ensure that in 99% of environments, users do not need to deploy and run TiFlow, adding computing resources (can provide stress testing reports); Even in extreme situations, provide self decompression algorithms to fully ensure no increase in user costs and no impact on business and hosts;

3. Multi-dimensional, fine-grained data capabilities

In an open JSON message, it includes host and process information, TCP/UDP aggregated data, L7 Header/HTTP/API/SQL......, Body/Payload, dozens of performance/communication metrics; Fully support various security and operational needs;

4. No impact on applications and hosts

In deployment, there is no need to restart or modify the business and host, and there are no third-party program dependencies;

More importantly, during operation, there is no increase in application latency and interruption risk in principle, but L7 and Payload content and various KPI/KQI can be obtained;