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[SARC-328] Implémenter les alertes : Nombre de jobs CPU/GPU (actives ou inactives) sur un cluster sur une période X #128
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[SARC-328] Implémenter les alertes : Nombre de jobs CPU/GPU (actives …
notoraptor e6a0fb0
Rebase and update comments.
notoraptor d403fdb
Fix a column name
notoraptor 5953724
Select sub-dataframe with given cluster names to compute stats, then …
notoraptor 6d4db7d
- Rename files
notoraptor 6d829bd
Compute statistics for each cluster separately.
notoraptor 0520262
Use file_regression for tests.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,129 @@ | ||
| import logging | ||
| import sys | ||
| from datetime import datetime, timedelta | ||
| from typing import List, Optional | ||
|
|
||
| import pandas | ||
|
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||
| from sarc.config import MTL | ||
| from sarc.jobs.series import compute_time_frames, load_job_series | ||
|
|
||
| logger = logging.getLogger(__name__) | ||
|
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||
|
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| def check_nb_jobs_per_cluster_per_time( | ||
| time_interval: Optional[timedelta] = timedelta(days=7), | ||
| time_unit=timedelta(days=1), | ||
| cluster_names: Optional[List[str]] = None, | ||
| nb_stddev=2, | ||
| verbose=False, | ||
| ): | ||
| """ | ||
| Check if we have scraped enough jobs per time unit per cluster on given time interval. | ||
| Log a warning for each cluster where number of jobs per time unit is lower than a limit | ||
| computed using mean and standard deviation statistics from this cluster. | ||
|
|
||
| Parameters | ||
| ---------- | ||
| time_interval: timedelta | ||
| If given, only jobs which ran in [now - time_interval, time_interval] will be used for checking. | ||
| Default is last 7 days. | ||
| If None, all jobs are used. | ||
| time_unit: timedelta | ||
| Time unit in which we must check cluster usage through time_interval. Default is 1 day. | ||
| cluster_names: list | ||
| Optional list of clusters to check. | ||
| If empty (or not specified), use all clusters available among jobs retrieved with time_interval. | ||
| nb_stddev: int | ||
| Amount of standard deviation to remove from average statistics to compute checking threshold. | ||
| For each cluster, threshold is computed as: | ||
| max(0, average - nb_stddev * stddev) | ||
| verbose: bool | ||
| If True, print supplementary info about clusters statistics. | ||
| """ | ||
|
|
||
| # Parse time_interval | ||
| start, end, clip_time = None, None, False | ||
| if time_interval is not None: | ||
| end = datetime.now(tz=MTL) | ||
| start = end - time_interval | ||
| clip_time = True | ||
|
|
||
| # Get data frame | ||
| df = load_job_series(start=start, end=end, clip_time=clip_time) | ||
|
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| # Split data frame into time frames using `time_unit` | ||
| tf = compute_time_frames(df, frame_size=time_unit) | ||
|
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| # List all available timestamps. | ||
| # We will check each timestamp for each cluster. | ||
| timestamps = sorted(tf["timestamp"].unique()) | ||
|
|
||
| # List clusters | ||
| if cluster_names: | ||
| cluster_names = sorted(cluster_names) | ||
| else: | ||
| cluster_names = sorted(df["cluster_name"].unique()) | ||
|
|
||
| # Iter for each cluster. | ||
| for cluster_name in cluster_names: | ||
| # Select only jobs for current cluster, | ||
| # group jobs by timestamp, and count jobs for each timestamp. | ||
| f_stats = ( | ||
| tf[tf["cluster_name"] == cluster_name] | ||
| .groupby(["timestamp"])[["job_id"]] | ||
| .count() | ||
| ) | ||
|
|
||
| # Create a dataframe with all available timestamps | ||
| # and associate each timestamp to 0 jobs by default. | ||
| c = ( | ||
| pandas.DataFrame({"timestamp": timestamps, "count": [0] * len(timestamps)}) | ||
| .groupby(["timestamp"])[["count"]] | ||
| .sum() | ||
| ) | ||
| # Set each timestamp valid for this cluster with real number of jobs scraped in this timestamp. | ||
| c.loc[f_stats.index, "count"] = f_stats["job_id"] | ||
|
|
||
| # We now have number of jobs for each timestamp for this cluster, | ||
| # with count 0 for timestamps where no jobs run on cluster, | ||
|
|
||
| # Compute average number of jobs per timestamp for this cluster | ||
| avg = c["count"].mean() | ||
| # Compute standard deviation of job count per timestamp for this cluster | ||
| stddev = c["count"].std() | ||
| # Compute threshold to use for warnings: <average> - nb_stddev * <standard deviation> | ||
| threshold = max(0, avg - nb_stddev * stddev) | ||
|
|
||
| if verbose: | ||
| print(f"[{cluster_name}]", file=sys.stderr) | ||
| print(c, file=sys.stderr) | ||
| print(f"avg {avg}, stddev {stddev}, threshold {threshold}", file=sys.stderr) | ||
| print(file=sys.stderr) | ||
|
|
||
| if threshold == 0: | ||
| # If threshold is zero, no check can be done, as jobs count will be always >= 0. | ||
| # Instead, we log a general warning. | ||
| msg = f"[{cluster_name}] threshold 0 ({avg} - {nb_stddev} * {stddev})." | ||
| if len(timestamps) == 1: | ||
| msg += ( | ||
| f" Only 1 timestamp found. Either time_interval ({time_interval}) is too short, " | ||
| f"or this cluster should not be currently checked" | ||
| ) | ||
| else: | ||
| msg += ( | ||
| f" Either nb_stddev is too high, time_interval ({time_interval}) is too short, " | ||
| f"or this cluster should not be currently checked" | ||
| ) | ||
| logger.warning(msg) | ||
| else: | ||
| # With a non-null threshold, we can check each timestamp. | ||
| for timestamp in timestamps: | ||
| nb_jobs = c.loc[timestamp]["count"] | ||
| if nb_jobs < threshold: | ||
| logger.warning( | ||
| f"[{cluster_name}][{timestamp}] " | ||
| f"insufficient cluster scraping: {nb_jobs} jobs / cluster / time unit; " | ||
| f"minimum required for this cluster: {threshold} ({avg} - {nb_stddev} * {stddev}); " | ||
| f"time unit: {time_unit}" | ||
| ) | ||
58 changes: 58 additions & 0 deletions
58
tests/functional/usage_alerts/test_alert_cluster_scraping.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,58 @@ | ||
| import functools | ||
| import re | ||
|
|
||
| import pytest | ||
|
|
||
| from sarc.alerts.usage_alerts.cluster_scraping import check_nb_jobs_per_cluster_per_time | ||
|
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||
| from ..jobs.test_func_load_job_series import MOCK_TIME | ||
| from .common import _get_warnings | ||
|
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||
| get_warnings = functools.partial( | ||
| _get_warnings, | ||
| module="sarc.alerts.usage_alerts.cluster_scraping:cluster_scraping.py", | ||
| ) | ||
|
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||
|
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| @pytest.mark.freeze_time(MOCK_TIME) | ||
| @pytest.mark.usefixtures("read_only_db", "tzlocal_is_mtl") | ||
| @pytest.mark.parametrize( | ||
| "params", | ||
| [ | ||
| # Check with default params. In last 7 days from now (mock time: 2023-11-22), | ||
| # there is only 2 jobs from 1 cluster in 1 timestamp. So, threshold will be 0. | ||
| dict(verbose=True), | ||
| # Check with no time interval (i.e. all jobs). | ||
| dict(time_interval=None, verbose=True), | ||
| # Check with a supplementary cluster `another_cluster` which is not in data frame. | ||
| dict( | ||
| time_interval=None, | ||
| cluster_names=[ | ||
| "fromage", | ||
| "mila", | ||
| "patate", | ||
| "raisin", | ||
| "another_cluster", | ||
| ], | ||
| verbose=True, | ||
| ), | ||
| # Check above case with 2 clusters ignored. | ||
| dict( | ||
| time_interval=None, | ||
| cluster_names=[ | ||
| "mila", | ||
| "raisin", | ||
| "another_cluster", | ||
| ], | ||
| ), | ||
| ], | ||
| ) | ||
| def test_check_nb_jobs_per_cluster_per_time(params, capsys, caplog, file_regression): | ||
| check_nb_jobs_per_cluster_per_time(**params) | ||
| file_regression.check( | ||
| re.sub( | ||
| r"WARNING +sarc\.alerts\.usage_alerts\.cluster_scraping:cluster_scraping.py:[0-9]+ +", | ||
| "", | ||
| f"{capsys.readouterr().err}\n{caplog.text}", | ||
| ) | ||
| ) |
9 changes: 9 additions & 0 deletions
9
...e_alerts/test_alert_cluster_scraping/test_check_nb_jobs_per_cluster_per_time_params0_.txt
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58 changes: 58 additions & 0 deletions
58
...e_alerts/test_alert_cluster_scraping/test_check_nb_jobs_per_cluster_per_time_params1_.txt
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72 changes: 72 additions & 0 deletions
72
...e_alerts/test_alert_cluster_scraping/test_check_nb_jobs_per_cluster_per_time_params2_.txt
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5 changes: 5 additions & 0 deletions
5
...e_alerts/test_alert_cluster_scraping/test_check_nb_jobs_per_cluster_per_time_params3_.txt
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