Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 7 new columns ({'run_id', 'queue_depth', 'event_id', 'event_time', 'component_name', 'event_type', 'severity'}) and 7 missing columns ({'deployment_env', 'traffic_tier', 'agent_name', 'region', 'status', 'agent_type', 'reliability_profile'}).
This happened while the csv dataset builder was generating data using
hf://datasets/Tekhnika/agentic-ai-observability-free/sample_output/events.csv (at revision ad108a272d1a2b55239459ed234b606395925234), [/tmp/hf-datasets-cache/medium/datasets/14445453005017-config-parquet-and-info-Tekhnika-agentic-ai-obser-9875a9b1/hub/datasets--Tekhnika--agentic-ai-observability-free/snapshots/ad108a272d1a2b55239459ed234b606395925234/sample_output/agents.csv (origin=hf://datasets/Tekhnika/agentic-ai-observability-free@ad108a272d1a2b55239459ed234b606395925234/sample_output/agents.csv), /tmp/hf-datasets-cache/medium/datasets/14445453005017-config-parquet-and-info-Tekhnika-agentic-ai-obser-9875a9b1/hub/datasets--Tekhnika--agentic-ai-observability-free/snapshots/ad108a272d1a2b55239459ed234b606395925234/sample_output/events.csv (origin=hf://datasets/Tekhnika/agentic-ai-observability-free@ad108a272d1a2b55239459ed234b606395925234/sample_output/events.csv), /tmp/hf-datasets-cache/medium/datasets/14445453005017-config-parquet-and-info-Tekhnika-agentic-ai-obser-9875a9b1/hub/datasets--Tekhnika--agentic-ai-observability-free/snapshots/ad108a272d1a2b55239459ed234b606395925234/sample_output/runs.csv (origin=hf://datasets/Tekhnika/agentic-ai-observability-free@ad108a272d1a2b55239459ed234b606395925234/sample_output/runs.csv)]
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1890, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 760, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
event_id: int64
run_id: int64
agent_id: int64
event_time: string
event_type: string
severity: string
component_name: string
queue_depth: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1200
to
{'agent_id': Value('int64'), 'agent_name': Value('string'), 'agent_type': Value('string'), 'deployment_env': Value('string'), 'region': Value('string'), 'status': Value('string'), 'traffic_tier': Value('string'), 'reliability_profile': Value('string')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1739, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1892, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 7 new columns ({'run_id', 'queue_depth', 'event_id', 'event_time', 'component_name', 'event_type', 'severity'}) and 7 missing columns ({'deployment_env', 'traffic_tier', 'agent_name', 'region', 'status', 'agent_type', 'reliability_profile'}).
This happened while the csv dataset builder was generating data using
hf://datasets/Tekhnika/agentic-ai-observability-free/sample_output/events.csv (at revision ad108a272d1a2b55239459ed234b606395925234), [/tmp/hf-datasets-cache/medium/datasets/14445453005017-config-parquet-and-info-Tekhnika-agentic-ai-obser-9875a9b1/hub/datasets--Tekhnika--agentic-ai-observability-free/snapshots/ad108a272d1a2b55239459ed234b606395925234/sample_output/agents.csv (origin=hf://datasets/Tekhnika/agentic-ai-observability-free@ad108a272d1a2b55239459ed234b606395925234/sample_output/agents.csv), /tmp/hf-datasets-cache/medium/datasets/14445453005017-config-parquet-and-info-Tekhnika-agentic-ai-obser-9875a9b1/hub/datasets--Tekhnika--agentic-ai-observability-free/snapshots/ad108a272d1a2b55239459ed234b606395925234/sample_output/events.csv (origin=hf://datasets/Tekhnika/agentic-ai-observability-free@ad108a272d1a2b55239459ed234b606395925234/sample_output/events.csv), /tmp/hf-datasets-cache/medium/datasets/14445453005017-config-parquet-and-info-Tekhnika-agentic-ai-obser-9875a9b1/hub/datasets--Tekhnika--agentic-ai-observability-free/snapshots/ad108a272d1a2b55239459ed234b606395925234/sample_output/runs.csv (origin=hf://datasets/Tekhnika/agentic-ai-observability-free@ad108a272d1a2b55239459ed234b606395925234/sample_output/runs.csv)]
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
agent_id int64 | agent_name string | agent_type string | deployment_env string | region string | status string | traffic_tier string | reliability_profile string |
|---|---|---|---|---|---|---|---|
1 | agent_1 | support | staging | europe | healthy | critical | stable |
2 | agent_2 | research | staging | global | healthy | medium | volatile |
3 | agent_3 | research | production | global | degraded | low | stable |
4 | agent_4 | copilot | staging | north_america | watch | low | volatile |
5 | agent_5 | research | staging | asia_pacific | watch | medium | fragile |
6 | agent_6 | ops | production | asia_pacific | degraded | medium | fragile |
7 | agent_7 | ops | beta | global | paused | low | stable |
8 | agent_8 | sales | sandbox | global | healthy | low | volatile |
9 | agent_9 | ops | sandbox | north_america | healthy | high | recovering |
10 | agent_10 | research | beta | global | watch | low | stable |
11 | agent_11 | support | staging | global | paused | medium | recovering |
12 | agent_12 | ops | production | europe | watch | medium | stable |
13 | agent_13 | support | production | europe | watch | critical | fragile |
14 | agent_14 | support | beta | global | healthy | low | volatile |
15 | agent_15 | research | staging | global | healthy | critical | stable |
16 | agent_16 | support | sandbox | global | watch | critical | fragile |
17 | agent_17 | ops | staging | europe | healthy | high | stable |
18 | agent_18 | support | staging | north_america | watch | low | stable |
19 | agent_19 | ops | staging | asia_pacific | degraded | critical | stable |
20 | agent_20 | copilot | production | europe | watch | high | recovering |
21 | agent_21 | copilot | beta | north_america | watch | high | recovering |
22 | agent_22 | ops | beta | north_america | healthy | high | volatile |
23 | agent_23 | copilot | production | north_america | watch | critical | stable |
24 | agent_24 | support | staging | north_america | watch | medium | recovering |
25 | agent_25 | research | staging | asia_pacific | paused | medium | fragile |
26 | agent_26 | research | staging | global | degraded | critical | volatile |
27 | agent_27 | ops | production | north_america | paused | low | recovering |
28 | agent_28 | sales | beta | global | healthy | high | volatile |
29 | agent_29 | sales | staging | global | degraded | critical | stable |
30 | agent_30 | research | sandbox | global | watch | low | volatile |
31 | agent_31 | ops | staging | north_america | healthy | critical | recovering |
32 | agent_32 | sales | production | north_america | paused | low | recovering |
33 | agent_33 | research | sandbox | global | paused | high | volatile |
34 | agent_34 | ops | beta | europe | healthy | medium | recovering |
35 | agent_35 | research | sandbox | asia_pacific | paused | critical | stable |
36 | agent_36 | support | sandbox | global | paused | critical | fragile |
37 | agent_37 | research | production | global | watch | critical | stable |
38 | agent_38 | ops | beta | asia_pacific | healthy | critical | stable |
39 | agent_39 | support | staging | europe | watch | critical | recovering |
40 | agent_40 | ops | staging | asia_pacific | paused | critical | stable |
41 | agent_41 | ops | production | asia_pacific | degraded | low | fragile |
42 | agent_42 | ops | sandbox | europe | paused | critical | volatile |
43 | agent_43 | support | staging | global | degraded | medium | recovering |
44 | agent_44 | ops | production | europe | paused | medium | fragile |
45 | agent_45 | support | sandbox | europe | degraded | critical | volatile |
46 | agent_46 | ops | staging | north_america | watch | medium | fragile |
1,107 | null | null | null | null | null | null | null |
138 | null | null | null | null | null | null | null |
943 | null | null | null | null | null | null | null |
395 | null | null | null | null | null | null | null |
822 | null | null | null | null | null | null | null |
634 | null | null | null | null | null | null | null |
9 | null | null | null | null | null | null | null |
437 | null | null | null | null | null | null | null |
107 | null | null | null | null | null | null | null |
1,045 | null | null | null | null | null | null | null |
442 | null | null | null | null | null | null | null |
106 | null | null | null | null | null | null | null |
267 | null | null | null | null | null | null | null |
348 | null | null | null | null | null | null | null |
18 | null | null | null | null | null | null | null |
220 | null | null | null | null | null | null | null |
11 | null | null | null | null | null | null | null |
772 | null | null | null | null | null | null | null |
504 | null | null | null | null | null | null | null |
157 | null | null | null | null | null | null | null |
515 | null | null | null | null | null | null | null |
730 | null | null | null | null | null | null | null |
105 | null | null | null | null | null | null | null |
372 | null | null | null | null | null | null | null |
482 | null | null | null | null | null | null | null |
405 | null | null | null | null | null | null | null |
189 | null | null | null | null | null | null | null |
321 | null | null | null | null | null | null | null |
471 | null | null | null | null | null | null | null |
570 | null | null | null | null | null | null | null |
282 | null | null | null | null | null | null | null |
797 | null | null | null | null | null | null | null |
655 | null | null | null | null | null | null | null |
380 | null | null | null | null | null | null | null |
149 | null | null | null | null | null | null | null |
203 | null | null | null | null | null | null | null |
537 | null | null | null | null | null | null | null |
823 | null | null | null | null | null | null | null |
210 | null | null | null | null | null | null | null |
109 | null | null | null | null | null | null | null |
276 | null | null | null | null | null | null | null |
120 | null | null | null | null | null | null | null |
983 | null | null | null | null | null | null | null |
430 | null | null | null | null | null | null | null |
940 | null | null | null | null | null | null | null |
895 | null | null | null | null | null | null | null |
215 | null | null | null | null | null | null | null |
452 | null | null | null | null | null | null | null |
425 | null | null | null | null | null | null | null |
1,017 | null | null | null | null | null | null | null |
250 | null | null | null | null | null | null | null |
969 | null | null | null | null | null | null | null |
374 | null | null | null | null | null | null | null |
550 | null | null | null | null | null | null | null |
End of preview.
Agentic AI Observability
Free sample for AI agent reliability dashboards, anomaly exploration, and observability-oriented analytics workflows.
What is included
- agents.csv: 46 rows, 8 columns
- events.csv: 5590 rows, 8 columns
- runs.csv: 1863 rows, 8 columns
Why this dataset is useful
- Good starter sample for an agent reliability dashboard or observability notebook.
- Useful for validating run-level and event-level analytics in Python, SQL, and BI tools.
- Lightweight enough for quick experiments while still matching the core workflow of the full starter pack.
Starter use cases
- Agent reliability baseline using run and event data.
- Observability dashboard for event severity, run behavior, and agent health patterns.
Schema overview
agents.csv
- Rows: 46
- Columns: agent_id, agent_name, agent_type, deployment_env, region, status, traffic_tier, reliability_profile
events.csv
- Rows: 5590
- Columns: event_id, run_id, agent_id, event_time, event_type, severity, component_name, queue_depth
runs.csv
- Rows: 1863
- Columns: run_id, agent_id, started_at, duration_ms, run_status, failure_risk_score, slo_breach_flag, anomaly_window_flag
Free vs full version
- Free Kaggle sample: reduced rows, reduced columns, starter notebook, and enough linked observability tables to validate the core workflow.
- Full version: full row volume, richer feature coverage, tool and feedback tables, and extra starter assets for dashboard, SQL, and anomaly-analysis work.
Upgrade to full version
- Full version: https://tekhnikalab.gumroad.com/l/agentic-ai-observability
- Upgrade if you need the full linked schema plus starter assets that get you to a dashboard, SQL project, or anomaly baseline faster.
Notes
- Contains generated data only and no real personal data.
- Designed as a lightweight free sample for evaluation and discovery.
- Downloads last month
- 19