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c4111eb6da
Introduces a client benchmark utility to track system resource usage (CPU, memory, disk I/O, and network I/O) of a process, so we don't need to write scripts to capture usage stats according to different OS standards. This becomes extremely helpful when I benchmark on Python notebook instances, e.g. Google Colab, where system monitor is not easily accessible or when running a separate monitor script is not easy. # Usage # Users can enable monitoring by setting `HF_XET_SYSTEM_MONITOR_ENABLED` to true, set usage sample interval using `HF_XET_SYSTEM_MONITOR_SAMPLE_INTERVAL`, this outputs metrics to the tracing stream at `INFO` level by default. In addition, these metrics can be redirected to a separate file by setting sample log path using `HF_XET_SYSTEM_MONITOR_LOG_PATH`. # Output # The stats are output in JSON format, which can be queried using tools like `jq`, e.g. 1. Trace of peak memory usage: `jq '.memory.peak_used_bytes' [HF_XET_SYSTEM_MONITOR_LOG_PATH]` 2. Trace of disk write speed: `jq '.disk.average_write_speed' [HF_XET_SYSTEM_MONITOR_LOG_PATH]` 3. Trace of network receive speed: `jq '.network.average_rx_speed' [HF_XET_SYSTEM_MONITOR_LOG_PATH]`
Proto
Directory where gproto files will be created
Operational helpers
- Logs, metrics and traces
- Configuration
- Access to AWS services (e.g. S3)
Examples
Identify which cas_server owns a particular key
cargo run --example infra -- --server-name cas-lb.xetbeta.com:5000 --key bar
Host: 35.89.208.89
Load Stats: SystemStatus { timestamp: "2022-07-06T19:15:00Z", cpu_utilization: 0.3416666833712037 }
Host: 54.245.178.249
Load Stats: SystemStatus { timestamp: "2022-07-06T19:15:00Z", cpu_utilization: 0.2943333333333333 }
Key bar gets hashed to server "54.245.178.249"