Skip to content

Instantly share code, notes, and snippets.

Created December 6, 2019 15:47
Show Gist options
  • Save tommyblue/6283d957b0c10813774eee8233a88a76 to your computer and use it in GitHub Desktop.
Save tommyblue/6283d957b0c10813774eee8233a88a76 to your computer and use it in GitHub Desktop.
#!/usr/bin/env python3
Replaces all instances of a cluster in a region.
This only works if all instances are managed by scaling group
import argparse
import functools
import logging
import os
import time
import boto3
CLUSTER = "" # Name of the cluster
REGION = "" # The region where the cluster is running
ASG_NAME = "" # Name of the autoscaling group
def main():
ecs_client = boto3.client("ecs", REGION)
asg_client = boto3.client("autoscaling", REGION)
# Can't replace if desired instances is different from running
if _get_desired_capacity(asg_client) != _get_running_instances():
logging.critical("Can't replace instances if autoscaling activity is ongoing")
os._exit(1)"Finding the number of desired instances in the autoscaling group")
desired_instances = _get_desired_capacity(asg_client)"Set the running instances status as 'DRAINING'")
_set_running_instances_as_draining(ecs_client)"Modifying the autoscaling group doubling the desired instances")
_set_desired_capacity(asg_client, desired_instances*2)"Waiting for the new instances to be launched")
if not _wait_instances(desired_instances*2):
os._exit(1)"Waiting all tasks in the draining instances to be stopped")
_wait_draining_instances_are_empty(ecs_client)"Bringing back the desired count in the asg to its initial value")
_set_desired_capacity(asg_client, desired_instances)"Waiting for the drained instances to be shutdown")
if not _wait_instances(desired_instances):
def _get_desired_capacity(asg_client) -> int:
resp = asg_client.describe_auto_scaling_groups(AutoScalingGroupNames=[ASG_NAME])
if len(resp['AutoScalingGroups']) != 1:
logging.critical("Too many ASG! {}".format(resp))
desired = resp['AutoScalingGroups'][0]["DesiredCapacity"]
return desired
def _set_running_instances_as_draining(ecs_client):
all_instances = ecs_client.list_container_instances(cluster=CLUSTER)['containerInstanceArns']
def _set_desired_capacity(asg_client, desired_instances):
@with_sleep(sleep_time=30, max_attempts=20)
def _wait_instances(desired_instances):
running = _get_running_instances()
if running == desired_instances:"Done!")
return True
def _get_running_instances() -> int:
instances = _describe_container_instances()
return len(instances['containerInstances'])
@with_sleep(sleep_time=30, max_attempts=20)
def _wait_draining_instances_are_empty(ecs_client):
tasks_per_instance = _get_tasks_per_instance(ecs_client, status=["DRAINING"])
if sum(tasks_per_instance.values()) == 0:
return True
def _get_tasks_per_instance(ecs_client, status=None):
tasks_list = ecs_client.list_tasks(cluster=CLUSTER)
return _tasks_per_instance(
ecs_client, tasks_list['taskArns'], status=status)
def _describe_container_instances():
ecs_client = boto3.client("ecs", REGION)
containers_response = ecs_client.list_container_instances(cluster=CLUSTER)
cluster_instances = _describe_container_instances(
cluster=CLUSTER, containerInstances=containers_response['containerInstanceArns'])
return cluster_instances
def _tasks_per_instance(ecs_client, tasks_list: list, status=None) -> dict:
Receives an `instances` dictionary with the instances arn as key and 0 as values, returns
a dictionary where the arn is replaced with the id and the value is the number of tasks
running on that instance
if status is None:
status = ["ACTIVE"]
instances = get_instances_dict(ecs_client, CLUSTER)
tasks_desc = ecs_client.describe_tasks(cluster=CLUSTER, tasks=tasks_list)
for t in tasks_desc['tasks']:
instances[t['containerInstanceArn']] += 1
response = ecs_client.describe_container_instances(
cluster=CLUSTER, containerInstances=list(instances.keys()))
instances_as_ids = {
i['ec2InstanceId']: instances[i['containerInstanceArn']]
for i in response['containerInstances'] if i['status'] in status
return instances_as_ids
def with_sleep(sleep_time=5, max_attempts=3):
def sleep_decorator(func):
def wrapper_sleep(*args, **kwargs):
attempts = 0
while True:
attempts += 1
ret = func(*args, **kwargs)
if ret is not None:
return ret
if attempts > max_attempts:
"Still not ready after %s seconds, please investigate." % (sleep_time*max_attempts))
return False
return wrapper_sleep
return sleep_decorator
if __name__ == '__main__':
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment