def perform_one_session(policy, results=None):
global log
log = logging.getLogger('pk')
config = pk_config.config()
log.info('--- session starts ---')
log.info('(I) Collecting inputs for nodes starts')
inputs = collect_inputs_for_nodes(policy)
set_policy_inputs_for_nodes(policy, inputs)
for x in inputs.keys():
log.info('(I) => "{0}": {1}'.format(x, inputs[x]))
log.info('(Q) Evaluating queries and alerts for nodes starts')
if results:
queries, alerts = add_query_results_and_alerts_to_nodes(
policy, results)
else:
queries, alerts = prom.evaluate_data_queries_and_alerts_for_nodes(
config['prometheus_endpoint'], policy)
for attrname, attrvalue in queries.iteritems():
log.info('(Q) => "{0}" is "{1}".'.format(attrname, attrvalue))
for attrname, attrvalue in alerts.iteritems():
log.info('(A) => "{0}" is "{1}".'.format(attrname, attrvalue))
log.info('(P) Policy evaluation for nodes starts')
perform_policy_evaluation_on_worker_nodes(policy)
log.info('(S) Scaling of nodes starts')
perform_worker_node_scaling(policy)
for attrname, attrvalue in alerts.iteritems():
prom.alerts_remove(attrname)
for oneservice in policy.get('scaling', dict()).get('services', dict()):
service_name = oneservice.get('name')
log.info('(I) Collecting inputs for service "{0}" starts'.format(
service_name))
inputs = collect_inputs_for_containers(policy, service_name)
set_policy_inputs_for_containers(policy, service_name, inputs)
for x in inputs.keys():
log.info('(I) => "{0}": {1}'.format(x, inputs[x]))
log.info('(Q) Evaluating queries and alerts for service "{0}" starts'.
format(service_name))
if results:
queries, alerts = add_query_results_and_alerts_to_service(
policy, results, service_name)
else:
queries, alerts = prom.evaluate_data_queries_and_alerts_for_a_service(
config['prometheus_endpoint'], policy, service_name)
for attrname, attrvalue in queries.iteritems():
log.info('(Q) => "{0}" is "{1}".'.format(attrname, attrvalue))
for attrname, attrvalue in alerts.iteritems():
log.info('(A) => "{0}" is "{1}".'.format(attrname, attrvalue))
log.info('(P) Policy evaluation for service "{0}" starts'.format(
service_name))
perform_policy_evaluation_on_a_docker_service(policy, service_name)
log.info('(S) Scaling of service "{0}" starts'.format(service_name))
perform_service_scaling(policy, service_name)
for attrname, attrvalue in alerts.iteritems():
prom.alerts_remove(attrname)
log.info('--- session finished ---')
return
def perform_one_session(policy, results=None):
global log
log = logging.getLogger('pk')
config = pk_config.config()
log.info('--- session starts ---')
log.info('(M) Maintaining worker nodes starts')
k8s.down_nodes_maintenance(config['k8s_endpoint'],
config['docker_node_unreachable_timeout'])
for onenode in policy.get('scaling', dict()).get('nodes', []):
node_name = onenode.get('name')
log.info('(I) Collecting inputs for node {} starts'.format(node_name))
inputs = collect_inputs_for_nodes(policy, onenode)
set_policy_inputs_for_nodes(policy, inputs, onenode)
for x in inputs.keys():
log.info('(I) => "{0}": {1}'.format(x, inputs[x]))
log.info('(Q) Evaluating queries and alerts for node {} starts'.format(
node_name))
if results:
queries, alerts = add_query_results_and_alerts_to_nodes(
policy, results, onenode)
else:
queries, alerts = prom.evaluate_data_queries_and_alerts_for_nodes(
config['prometheus_endpoint'], policy, onenode)
for attrname, attrvalue in queries.iteritems():
log.info('(Q) => "{0}" is "{1}".'.format(attrname, attrvalue))
for attrname, attrvalue in alerts.iteritems():
log.info('(A) => "{0}" is "{1}".'.format(attrname, attrvalue))
if 'm_opt_advice' in onenode.get('scaling_rule', ''):
log.info('(O) Creating sample for the optimizer starts')
sample = optim.generate_sample(queries, inputs)
log.info('(O) Sending sample for the optimizer starts')
optim.calling_rest_api_sample(sample)
log.info('(P) Policy evaluation for nodes starts')
perform_policy_evaluation_on_worker_nodes(policy, onenode)
log.info('(S) Scaling of nodes starts')
perform_worker_node_scaling(onenode)
for attrname, attrvalue in alerts.iteritems():
prom.alerts_remove(attrname)
for oneservice in policy.get('scaling', dict()).get('services', []):
service_name = oneservice.get('name')
log.info('(I) Collecting inputs for service "{0}" starts'.format(
service_name))
inputs = collect_inputs_for_containers(policy, service_name)
set_policy_inputs_for_containers(policy, service_name, inputs)
for x in inputs.keys():
log.info('(I) => "{0}": {1}'.format(x, inputs[x]))
log.info('(Q) Evaluating queries and alerts for service "{0}" starts'.
format(service_name))
if results:
queries, alerts = add_query_results_and_alerts_to_service(
policy, results, service_name)
else:
queries, alerts = prom.evaluate_data_queries_and_alerts_for_a_service(
config['prometheus_endpoint'], policy, service_name)
for attrname, attrvalue in queries.iteritems():
log.info('(Q) => "{0}" is "{1}".'.format(attrname, attrvalue))
for attrname, attrvalue in alerts.iteritems():
log.info('(A) => "{0}" is "{1}".'.format(attrname, attrvalue))
log.info('(P) Policy evaluation for service "{0}" starts'.format(
service_name))
perform_policy_evaluation_on_a_k8s_deploy(policy, service_name)
log.info('(S) Scaling of service "{0}" starts'.format(service_name))
perform_service_scaling(policy, service_name)
for attrname, attrvalue in alerts.iteritems():
prom.alerts_remove(attrname)
log.info('--- session finished ---')
return
def alerts_init():
alert = yaml.safe_load(request.stream)
log.info('(A) Resetting alerts based on external request.')
prom.alerts_remove(None)
return jsonify(dict(response='OK'))