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feat(runtime/kubernetes): Proper load balancing of k8s
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We can load balance k8s based on number of pending pods,
use one with 0, or least pods.

Signed-off-by: Denys Fedoryshchenko <denys.f@collabora.com>
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nuclearcat committed Nov 26, 2024
1 parent e86fe6b commit 3e3317c
Showing 1 changed file with 37 additions and 2 deletions.
39 changes: 37 additions & 2 deletions kernelci/runtime/kubernetes.py
Original file line number Diff line number Diff line change
Expand Up @@ -45,10 +45,45 @@ def generate(self, job, params):
params['k8s_job_name'] = k8s_job_name
return template.render(params)

def _fetch_load(self, ctxname):
"""
Fetch load with retry and workaround due repeating errors
"""
kubernetes.config.load_kube_config(context=ctxname)
core_v1 = kubernetes.client.CoreV1Api()
pods = None
for _ in range(3):
try:
pods = core_v1.list_namespaced_pod(namespace='default')
break
except kubernetes.client.rest.ApiException as error:
print(f'Error listing pods in {ctxname}: {error}')
continue

if not pods:
print(f'No pods found in {ctxname}, returning 1000')
return 1000

load = len([pod for pod in pods.items if pod.status.phase == 'Pending'])
return load

def _get_clusters_load(self):
"""Get the load of all clusters (number of pods in Pending state)"""
load = {}
for ctxname in self.config.context:
load[ctxname] = self._fetch_load(ctxname)
# We found free cluster, return it, no need to check others
if load[ctxname] == 0:
break
return load

def submit(self, job_path):
# if context is array, pick any random context to load-balance
# if context is array, we have multiple k8s build clusters
# TBD: Implement caching to not check load for each job?
if isinstance(self.config.context, list):
self.kcontext = random.choice(self.config.context)
# get the cluster with the least load
load = self._get_clusters_load()
self.kcontext = min(load, key=load.get)
else:
self.kcontext = self.config.context
kubernetes.config.load_kube_config(context=self.kcontext)
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