Additional Features¶
Scaler comes with a number of features that can be used to monitor and profile tasks, and customize behavior.
Scaler Top (Monitoring)¶
Top is a monitoring tool that allows you to see the status of the Scaler. The scheduler prints an address to the logs on startup that can be used to connect to it with the scaler_top CLI command:
scaler_top ipc:///tmp/0.0.0.0_8516_monitor
Which will show an interface similar to the standard Linux top command:
scheduler | task_manager | scheduler_sent | scheduler_received
cpu 0.0% | unassigned 0 | HeartbeatEcho 283,701 | Heartbeat 283,701
rss 130.1m | running 0 | ObjectResponse 233 | ObjectRequest 215
| success 53,704 | TaskEcho 53,780 | Task 53,764
| failed 14 | Task 54,660 | TaskResult 53,794
| canceled 48 | TaskResult 53,766 | DisconnectRequest 21
| not_found 14 | ObjectRequest 366 | TaskCancel 60
| DisconnectResponse 21 | BalanceResponse 15
| TaskCancel 62 | GraphTask 6
| BalanceRequest 15 |
| GraphTaskResult 6 |
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Shortcuts: worker[n] agt_cpu[C] agt_rss[M] cpu[c] rss[m] free[f] sent[w] queued[d] lag[l]
Total 7 worker(s)
worker agt_cpu agt_rss [cpu] rss free sent queued lag ITL | client_manager
2732890|sd-1e7d-dfba|d26+ 0.5% 111.8m 0.5% 113.3m 1000 0 0 0.7ms 100 |
2732885|sd-1e7d-dfba|56b+ 0.0% 111.0m 0.5% 111.2m 1000 0 0 0.7ms 100 | func_to_num_tasks
2732888|sd-1e7d-dfba|108+ 0.0% 111.7m 0.5% 111.0m 1000 0 0 0.6ms 100 |
2732891|sd-1e7d-dfba|149+ 0.0% 113.0m 0.0% 112.2m 1000 0 0 0.9ms 100 |
2732889|sd-1e7d-dfba|211+ 0.5% 111.7m 0.0% 111.2m 1000 0 0 1ms 100 |
2732887|sd-1e7d-dfba|e48+ 0.5% 112.6m 0.0% 111.0m 1000 0 0 0.9ms 100 |
2732886|sd-1e7d-dfba|345+ 0.0% 111.5m 0.0% 112.8m 1000 0 0 0.8ms 100 |
scheduler section shows the scheduler’s resource usage
task_manager section shows the status of tasks
scheduler_sent section counts the number of each type of message sent by the scheduler
scheduler_received section counts the number of each type of message received by the scheduler
worker section shows worker details, you can use shortcuts to sort by columns, and the * in the column header shows which column is being used for sorting
agt_cpu/agt_rss means cpu/memory usage of the worker agent
cpu/rss means cpu/memory usage of the worker
free means number of free task slots for the worker
sent means how many tasks scheduler sent to the worker
queued means how many tasks worker received and enqueued
lag means the latency between scheduler and the worker
ITL means is debug information
I means processor initialized
T means have a task or not
L means task lock
Additional client-facing feature guides have been consolidated into Scaler Client.
Scaler Web GUI¶
Scaler also provides a browser-based monitoring dashboard through scaler_gui.
It subscribes to the scheduler monitor stream and serves a real-time web UI over HTTP.
Note
The GUI requires optional dependencies. Install with pip install opengris-scaler[gui].
Start the GUI by pointing it at the scheduler monitor address:
scaler_gui tcp://127.0.0.1:6380 --gui-address 127.0.0.1:50001
Open http://127.0.0.1:50001 in your browser.
What the Web GUI shows:
Live: scheduler metrics, worker manager summary, and worker-level metrics (CPU/RSS/free/sent/queued/lag/ITL).
Task Log: recent task lifecycle updates (running/success/failure/canceled), duration, peak memory, and capabilities.
Worker Task Stream: a timeline by worker with capability colors and status overlays (failed and canceled patterns).
Memory Usage: rolling cluster memory chart derived from task profiling metadata.
Worker Processors: manager-grouped view of processor-level CPU/RSS and state flags (initialized, has task, suspended).
Interactive behavior:
Uses WebSocket updates with auto-reconnect if the browser temporarily disconnects.
Sends a full current snapshot on connect, then incremental updates in short batches.
Supports runtime settings for stream window length (5/10/30 minutes) and memory chart scale (linear/log).