Qi Layer: Effective System Flow and Pressure Fields
Qi (气) in Chinese culture refers to the energy and flow field that permeates all things. In AI infrastructure, we borrow the concept of “Qi” to describe the effective flow and pressure distribution within systems.
This includes the circulation of data, tasks, and signals throughout the system, as well as how various explicit or implicit system pressures accumulate, propagate, and release.
The Essence of Qi: Overall State of Affairs
Unlike traditional single-point metric monitoring, the concept of “Qi” reminds us to focus on the overall state of affairs:
Signals are not isolated events, but rather gather and flow like a field
For example:
- A sudden spike in GPU utilization may not be abnormal
- But if multiple metrics (job queue length, response latency, memory usage, etc.) show a simultaneous trend of increase and persistence → this indicates a change in the “Qi field”
- This signals the system entering a high-pressure state
This signal field manifests as the gathering and stretching of Qi, indicating the accumulation of some form of system tension.
Two States of Qi
Qi Flow: System Active
When all elements coordinate well, data and instructions flow smoothly, producing value efficiently:
- Processing rates across all stages are basically matched
- No long-term backlogs or idle resources
- Timely system responses
- Balanced resource utilization
Qi Stagnation: System Pathological
If a bottleneck or imbalance occurs somewhere, Qi’s flow is obstructed, causing local pressure to surge:
- Jobs queue for long periods
- CPU/GPU long-term idle or 100% utilization
- Serious message queue backlog
- Frequent anomaly alerts
Ultimately, this may trigger failures or performance collapse at weak points.
Qi’s Flow Path
To intuitively understand Qi’s flow path, we can view the system as a closely connected network:
Qi’s Cycle:
- Data (Water) Qi enters Model (Wood)
- Drives Computing Power (Fire) to operate
- Coordinated via Platform (Earth)
- Executes computation on Hardware (Metal)
- Outputs results, producing new data or signals
- Feeds back into the data pool (Water)
- Cycle repeats
Two Forms of Qi
Healthy Flow
Qi circulates ceaselessly among the five elements, maintaining system functionality:
- If every step flows smoothly → system operates smoothly
- If any step is obstructed → Qi flow slows or even reverses, damaging system performance and stability
Pressure Propagation
Qi refers not only to healthy flow, but also to pressure propagation:
Example: Data Inflow Surge
- Data inflow surges but model processing capacity cannot keep up
- Unprocessed data continuously accumulates
- Manifests as excessive pressure in the data layer (Water)
- Leading to suppression of computing power performance (Fire weakens)
Example: Hardware Resource Exhaustion
- Hardware (Metal) resources exhausted
- Computing requests cannot be satisfied
- Obstructed Qi transforms into queuing pressure
- Feeds back to platform (Earth) scheduling layer and user experience
Application of Qi Layer in Operations
Through the lens of “Qi”, operations and architecture teams can more sensitively detect sub-optimal system states:
Not Just Whether There’s a Problem, But How It’s Trending
| Qi State | Manifestation | Warning Significance |
|---|---|---|
| Stagnation Emerging | Latency jitter gradually worsening | System entering sub-stable state, needs 疏导 |
| Flow Obstruction | Request failure rate rising, retries increasing | 某环节阻塞，needs investigation |
| Qi Scattering | Metrics fluctuating severely, irregular | System severely imbalanced, needs overall adjustment |
| Qi Deficiency | Resource utilization long-term low | Configuration unreasonable, needs optimization |
Qi Disorder Precedes Major Incidents
- Latency jitter gradually worsening → signals system entering sub-stable state
- If no measures are taken to resolve (scaling resources, optimizing algorithms, or rate limiting) → may evolve to complete failure
- Agent task interaction rhythm (Qi) slows or stops → may indicate poor communication between agents or deadlock
Strategies for Guiding Qi Flow
Maintaining smooth Qi flow requires building resilience:
Architecture Level
- Peak shaving and valley filling mechanisms: Absorb 突发流量
- Message queue backpressure protection: Prevent pressure backflow
- Elastic buffer design: Reserve margin to handle impacts
Strategy Level
- Slack capacity: Maintain certain redundancy
- Elastic scaling strategies: Dynamically adjust resources
- Rate limiting and degradation mechanisms: Protect core functionality
Agent System Special Attention
- Monitor task queues and communication latency
- Ensure information flow (Qi) between agents is unobstructed
- Introduce coordinator agents or reduce concurrency when necessary to smooth Qi flow
Qi Layer Monitoring Practices
Establish system-wide observability:
| Monitoring Dimension | Focus | Tool Examples |
|---|---|---|
| Traffic Distribution | Request flow across stages | Distributed Tracing |
| Queue Backlog | Queue length trends | Message Queue Monitoring |
| Resource Utilization | CPU/GPU/Memory/Storage | Prometheus + Grafana |
| Latency Distribution | P50/P95/P99 latency | APM Tools |
| Anomaly Trends | Error rate, retry rate changes | Log Aggregation Analysis |
The Qi layer provides an effective liquidity metric, helping us pulse-check whether the system’s “blood and Qi” are abundant and flowing smoothly
Summary
Qi’s operation can be understood as whether the system’s “meridians” are unobstructed:
- Qi flow means system active: Data and instructions flow smoothly, producing value efficiently
- Qi stagnation means system pathological: Flow obstructed, local pressure surges, ultimately triggering failures
Just as in Traditional Chinese Medicine’s four examination methods, by observing “Qi’s” operation, we can predict the trajectory of system problems and apply targeted remedies.