def test_multiple_jobs_submission(scheduler, region, pcluster_config_reader, clusters_factory, test_datadir):
scaledown_idletime = 4
# Test jobs should take at most 9 minutes to be executed.
# These guarantees that the jobs are executed in parallel.
max_jobs_execution_time = 9
cluster_config = pcluster_config_reader(scaledown_idletime=scaledown_idletime)
cluster = clusters_factory(cluster_config)
remote_command_executor = RemoteCommandExecutor(cluster)
scheduler_commands = get_scheduler_commands(scheduler, remote_command_executor)
logging.info("Executing test jobs on cluster")
remote_command_executor.run_remote_script(test_datadir / "cluster-check.sh", args=["submit", scheduler])
logging.info("Monitoring asg capacity and compute nodes")
asg_capacity_time_series, compute_nodes_time_series, timestamps = get_compute_nodes_allocation(
scheduler_commands=scheduler_commands,
region=region,
stack_name=cluster.cfn_name,
max_monitoring_time=minutes(max_jobs_execution_time) + minutes(scaledown_idletime) + minutes(5),
)
logging.info("Verifying test jobs completed successfully and in the expected time")
_assert_test_jobs_completed(remote_command_executor, max_jobs_execution_time * 60)
logging.info("Verifying auto-scaling worked correctly")
_assert_scaling_works(
asg_capacity_time_series=asg_capacity_time_series,
compute_nodes_time_series=compute_nodes_time_series,
expected_asg_capacity=(0, 3),
expected_compute_nodes=(0, 3),
)
def _test_job_dependencies(remote_command_executor, region, stack_name, scaledown_idletime):
logging.info("Testing cluster doesn't scale when job dependencies are not satisfied")
slurm_commands = SlurmCommands(remote_command_executor)
result = slurm_commands.submit_command("sleep 60", nodes=1)
job_id = slurm_commands.assert_job_submitted(result.stdout)
result = remote_command_executor.run_remote_command("sbatch -N 1 --wrap='sleep 1' -d afterok:{0}".format(job_id))
dependent_job_id = slurm_commands.assert_job_submitted(result.stdout)
# Wait for reason to be computed
time.sleep(3)
assert_that(_get_job_info(remote_command_executor, job_id)).contains(
"JobState=PENDING Reason=Nodes_required_for_job_are_DOWN,_DRAINED"
"_or_reserved_for_jobs_in_higher_priority_partitions"
)
assert_that(_get_job_info(remote_command_executor, dependent_job_id)).contains("JobState=PENDING Reason=Dependency")
jobs_execution_time = 1
estimated_scaleup_time = 5
estimated_scaledown_time = 20
asg_capacity_time_series, compute_nodes_time_series, timestamps = get_compute_nodes_allocation(
scheduler_commands=slurm_commands,
region=region,
stack_name=stack_name,
max_monitoring_time=minutes(jobs_execution_time)
+ minutes(scaledown_idletime)
+ minutes(estimated_scaleup_time)
+ minutes(estimated_scaledown_time),
)
assert_that(max(asg_capacity_time_series)).is_equal_to(1)
assert_that(max(compute_nodes_time_series)).is_equal_to(1)
assert_that(asg_capacity_time_series[-1]).is_equal_to(0)
assert_that(compute_nodes_time_series[-1]).is_equal_to(0)
def assert_scaling_worked(
scheduler_commands,
region,
stack_name,
scaledown_idletime,
expected_max,
expected_final,
assert_asg=True,
assert_scheduler=True,
):
jobs_execution_time = 1
estimated_scaleup_time = 5
max_scaledown_time = 10
asg_capacity_time_series, compute_nodes_time_series, _ = get_compute_nodes_allocation(
scheduler_commands=scheduler_commands,
region=region,
stack_name=stack_name,
max_monitoring_time=minutes(jobs_execution_time) +
minutes(scaledown_idletime) + minutes(estimated_scaleup_time) +
minutes(max_scaledown_time),
)
with soft_assertions():
if assert_asg:
asg_capacity_time_series_str = f"asg_capacity_time_series={asg_capacity_time_series}"
assert_that(max(asg_capacity_time_series)).described_as(
asg_capacity_time_series_str).is_equal_to(expected_max)
assert_that(asg_capacity_time_series[-1]).described_as(
asg_capacity_time_series_str).is_equal_to(expected_final)
if assert_scheduler:
compute_nodes_time_series_str = f"compute_nodes_time_series={compute_nodes_time_series}"
assert_that(max(compute_nodes_time_series)).described_as(
compute_nodes_time_series_str).is_equal_to(expected_max)
assert_that(compute_nodes_time_series[-1]).described_as(
compute_nodes_time_series_str).is_equal_to(expected_final)
def test_multiple_jobs_submission(scheduler, region, pcluster_config_reader,
clusters_factory, test_datadir):
scaledown_idletime = 4
# Test jobs should take at most 9 minutes to be executed.
# These guarantees that the jobs are executed in parallel.
max_jobs_execution_time = 9
cluster_config = pcluster_config_reader(
scaledown_idletime=scaledown_idletime)
cluster = clusters_factory(cluster_config)
remote_command_executor = RemoteCommandExecutor(cluster)
scheduler_commands = get_scheduler_commands(scheduler,
remote_command_executor)
logging.info("Executing sleep job to start a dynamic node")
result = scheduler_commands.submit_command("sleep 1")
job_id = scheduler_commands.assert_job_submitted(result.stdout)
retry(wait_fixed=seconds(30),
stop_max_delay=seconds(500))(_assert_job_state)(
scheduler_commands, job_id, job_state="COMPLETED")
logging.info("Executing test jobs on cluster")
remote_command_executor.run_remote_script(test_datadir /
"cluster-check.sh",
args=["submit", scheduler])
logging.info("Monitoring ec2 capacity and compute nodes")
ec2_capacity_time_series, compute_nodes_time_series, timestamps = get_compute_nodes_allocation(
scheduler_commands=scheduler_commands,
region=region,
stack_name=cluster.cfn_name,
max_monitoring_time=minutes(max_jobs_execution_time) +
minutes(scaledown_idletime) + minutes(5),
)
logging.info(
"Verifying test jobs completed successfully and in the expected time")
_assert_test_jobs_completed(remote_command_executor,
max_jobs_execution_time * 60)
logging.info("Verifying auto-scaling worked correctly")
_assert_scaling_works(
ec2_capacity_time_series=ec2_capacity_time_series,
compute_nodes_time_series=compute_nodes_time_series,
expected_ec2_capacity=(0, 3),
expected_compute_nodes=(0, 3),
)
logging.info("Verifying no error in logs")
assert_no_errors_in_logs(remote_command_executor, scheduler)
def assert_scaling_worked(scheduler_commands, region, stack_name,
scaledown_idletime, expected_max, expected_final):
jobs_execution_time = 1
estimated_scaleup_time = 5
max_scaledown_time = 10
asg_capacity_time_series, compute_nodes_time_series, _ = get_compute_nodes_allocation(
scheduler_commands=scheduler_commands,
region=region,
stack_name=stack_name,
max_monitoring_time=minutes(jobs_execution_time) +
minutes(scaledown_idletime) + minutes(estimated_scaleup_time) +
minutes(max_scaledown_time),
)
assert_that(max(asg_capacity_time_series)).is_equal_to(expected_max)
assert_that(max(compute_nodes_time_series)).is_equal_to(expected_max)
assert_that(asg_capacity_time_series[-1]).is_equal_to(expected_final)
assert_that(compute_nodes_time_series[-1]).is_equal_to(expected_final)
def _test_job_dependencies(remote_command_executor, region, stack_name,
scaledown_idletime):
logging.info(
"Testing cluster doesn't scale when job dependencies are not satisfied"
)
slurm_commands = SlurmCommands(remote_command_executor)
result = slurm_commands.submit_command("sleep 60", nodes=1)
job_id = slurm_commands.assert_job_submitted(result.stdout)
result = remote_command_executor.run_remote_command(
"sbatch -N 1 --wrap='sleep 1' -d afterok:{0}".format(job_id))
dependent_job_id = slurm_commands.assert_job_submitted(result.stdout)
# Wait for reason to be computed
time.sleep(3)
assert_that(_get_job_info(remote_command_executor, job_id)).contains(
"JobState=PENDING Reason=Nodes_required_for_job_are_DOWN,_DRAINED"
"_or_reserved_for_jobs_in_higher_priority_partitions")
assert_that(_get_job_info(
remote_command_executor,
dependent_job_id)).contains("JobState=PENDING Reason=Dependency")
jobs_execution_time = 1
estimated_scaleup_time = 5
estimated_scaledown_time = 20
asg_capacity_time_series, compute_nodes_time_series, timestamps = get_compute_nodes_allocation(
scheduler_commands=slurm_commands,
region=region,
stack_name=stack_name,
max_monitoring_time=minutes(jobs_execution_time) +
minutes(scaledown_idletime) + minutes(estimated_scaleup_time) +
minutes(estimated_scaledown_time),
)
assert_that(max(asg_capacity_time_series)).is_equal_to(1)
assert_that(max(compute_nodes_time_series)).is_equal_to(1)
assert_that(asg_capacity_time_series[-1]).is_equal_to(0)
assert_that(compute_nodes_time_series[-1]).is_equal_to(0)
