tasks: check allocatable resources

* Adds task calling k8s api to check if there are sufficient
  allocatable resources available in any nodes of the cluster.

Signed-off-by: Dinos Kousidis <dinos.kousidis@cern.ch>

reana_commons/config.py

@@ -63,3 +63,12 @@
         'reana_job_controller.json')
 }
 """REANA Workflow Controller address."""
+
+K8S_MINIMUM_CAPACITY_CPU = 1
+"""Minimum allocatable cpu capacity in cluster to start new workflows."""
+
+K8S_MINIMUM_CAPACITY_MEMORY = 1000000
+"""Minimum allocatable memory capacity in cluster to start new workflows."""
+
+K8S_MINIMUM_CAPACITY_PODS = 109
+"""Minimum allocatable pod capacity in cluster to start new workflows."""

reana_commons/tasks.py

@@ -14,6 +14,9 @@
 from kubernetes.client.rest import ApiException
 
 from reana_commons.api_client import JobControllerAPIClient
+from reana_commons.config import (K8S_MINIMUM_CAPACITY_CPU,
+                                  K8S_MINIMUM_CAPACITY_MEMORY,
+                                  K8S_MINIMUM_CAPACITY_PODS)
 from reana_commons.k8s.api_client import current_k8s_corev1_api_client
 
 log = logging.getLogger(__name__)
@@ -49,9 +52,31 @@ def stop_workflow(workflow_uuid, job_list):
 def reana_ready():
     """Check if reana can start new workflows."""
     try:
-        import wdb
-        wdb.set_trace()
-        current_k8s_corev1_api_client.read_node_status('minikube')
+        import random
+        import time
+        time.sleep(10)
+        return random.random() > 0.5
+        is_ready = False
+        node_info = current_k8s_corev1_api_client.list_node()
+        for node in node_info.items:
+            # One check could be based on the predefined conditions about the
+            # node status: MemoryPressure, OutOfDisk, KubeletReady
+            #              DiskPressure, PIDPressure,
+            for condition in node.status.conditions:
+                if not condition.status:
+                    return False
+            allocatable_capacity = node.status.allocatable
+            # Another could be based on watermarks set in the configuration
+            # an issue here is allocatable_capacity does not live update,
+            # and there are cluster monitoring tools available like heapster
+            # that expose an API with the real time data. So the lines below
+            # are not meaningful.
+            if int(allocatable_capacity['cpu']) > K8S_MINIMUM_CAPACITY_CPU and \
+                    int(allocatable_capacity['pods']) > K8S_MINIMUM_CAPACITY_PODS and \
+                    int(allocatable_capacity['memory'][:-2]) > K8S_MINIMUM_CAPACITY_MEMORY:
+                is_ready = True
+                break
+        return is_ready
     except ApiException as e:
         print(str(e))
     return True