eks-rolling-update 1.0.147

EKS Rolling Update is a utility for updating the launch configuration or template of worker nodes in an EKS cluster.

EKS Rolling Update

EKS Rolling Update is a utility for updating the launch configuration or template of worker nodes in an EKS cluster.

• Intro
• Requirements
• Installation
• Usage
• Configuration
• Contributing
• License

Intro

EKS Rolling Update is a utility for updating the launch configuration or template of worker nodes in an EKS cluster. It updates worker nodes in a rolling fashion and performs health checks of your EKS cluster to ensure no disruption to service. To achieve this, it performs the following actions:

• Pauses Kubernetes Autoscaler (Optional)
• Finds a list of worker nodes that do not have a launch config or template that matches their ASG
• Scales up the desired capacity
• Ensures the ASGs are healthy and that the new nodes have joined the EKS cluster
• Cordons the outdated worker nodes
• Suspends AWS Autoscaling actions while update is in progress
• Drains outdated EKS outdated worker nodes one by one
• Terminates EC2 instances of the worker nodes one by one
• Detaches EC2 instances from the ASG one by one
• Scales down the ASG to original count (in case of failure)
• Resumes AWS Autoscaling actions
• Resumes Kubernetes Autoscaler (Optional)

Requirements

• kubectl installed
• KUBECONFIG environment variable set, or config available in ${HOME}/.kube/config per default
• AWS credentials configured

IAM Requirements

The following IAM permissions are required:

autoscaling:DescribeAutoScalingGroups
autoscaling:TerminateInstanceInAutoScalingGroup
autoscaling:SuspendProcesses
autoscaling:ResumeProcesses
autoscaling:UpdateAutoScalingGroup
autoscaling:CreateOrUpdateTags
autoscaling:DeleteTags
ec2:DescribeLaunchTemplates
ec2:DescribeInstance

Installation

From PyPi

pip3 install eks-rolling-update

From source

virtualenv -p python3 venv
source venv/bin/activate
pip3 install -r requirements.txt

Usage

usage: eks_rolling_update.py [-h] --cluster_name CLUSTER_NAME [--plan]

Rolling update on cluster

optional arguments:
  -h, --help            show this help message and exit
  --cluster_name CLUSTER_NAME, -c CLUSTER_NAME
                        the cluster name to perform rolling update on
  --plan, -p            perform a dry run to see which instances are out of
                        date

Example:

eks_rolling_update.py -c my-eks-cluster

Configuration

Environment Variable	Description	Default
K8S_AUTOSCALER_ENABLED	If True Kubernetes Autoscaler will be paused before running update	False
K8S_AUTOSCALER_NAMESPACE	Namespace where Kubernetes Autoscaler is deployed	"default"
K8S_AUTOSCALER_DEPLOYMENT	Deployment name of Kubernetes Autoscaler	"cluster-autoscaler"
K8S_AUTOSCALER_REPLICAS	Number of replicas to scale back up to after Kubernentes Autoscaler paused	2
ASG_DESIRED_STATE_TAG	Temporary tag which will be saved to the ASG to store the state of the EKS cluster prior to update	eks-rolling-update:desired_capacity
ASG_ORIG_CAPACITY_TAG	Temporary tag which will be saved to the ASG to store the state of the EKS cluster prior to update	eks-rolling-update:original_capacity
ASG_ORIG_MAX_CAPACITY_TAG	Temporary tag which will be saved to the ASG to store the state of the EKS cluster prior to update	eks-rolling-update:original_max_capacity
ASG_WAIT_FOR_DETACHMENT	If True, waits for detachment to fully complete (draining connections etc) after terminating instance and detaching	True
ASG_USE_TERMINATION_POLICY	Use ASG termination policy (instance terminate/detach handled by ASG according to configured termination policy)	False
CLUSTER_HEALTH_WAIT	Number of seconds to wait after ASG has been scaled up before checking health of the cluster	90
CLUSTER_HEALTH_RETRY	Number of attempts to validate the health of the cluster after ASG has been scaled	1
GLOBAL_MAX_RETRY	Number of attempts of a health or termination check	12
GLOBAL_HEALTH_WAIT	Number of seconds to wait before retrying a health check	20
BETWEEN_NODES_WAIT	Number of seconds to wait after removing a node before continuing on	0
RUN_MODE	See Run Modes section below	1
DRY_RUN	If True, only a query will be run to determine which worker nodes are outdated without running an update operation	False
EXCLUDE_NODE_LABEL_KEYS	List of space-delimited keys for node labels. Nodes with a label using one of these keys will be excluded from the node count when scaling the cluster.	"spotinst.io/node-lifecycle"
EXTRA_DRAIN_ARGS	Additional space-delimited args to supply to the kubectl drain function, e.g --force=true. See kubectl drain -h	""
MAX_ALLOWABLE_NODE_AGE	The max age each node allowed to be. This works with RUN_MODE 4 as node rolling is updating based on age of node	6
INSTANCE_WAIT_FOR_STOPPING	Wait for terminated instances to be in stopping or shutting-down state as well as terminated or stopped	False
BATCH_SIZE	Instances to scale the ASG by at a time. When set to 0, batching is disabled.	0

Run Modes

There are a number of different values which can be set for the RUN_MODE environment variable.

1 is the default.

Mode Number	Description
1	Scale up and cordon the outdated nodes of each ASG one-by-one, just before we drain them.
2	Scale up and cordon the outdated nodes of all ASGs all at once at the beginning of the run.
3	Cordon the outdated nodes of all ASGs at the beginning of the run but scale each ASG one-by-one.
4	Roll EKS nodes based on age instead of launch config (works with MAX_ALLOWABLE_NODE_AGE with default 6 days value).

Each of them have different advantages and disadvantages.

• Scaling up all ASGs at once may cause AWS EC2 instance limits to be exceeded
• Only cordoning the nodes on a per-ASG basis will mean that pods are likely to be moved more than once
• Cordoning the nodes for all ASGs at once could cause issues if new pods needs to start during the process

Batching

EKS Rolling Update can batch scale-out the ASG to progressively reach the desired instance count before it begins draining the nodes.

This is intended for use in cases where a large ASG scale-out may result in instances failing to register with EKS. Such a scenario is more likely to occur with larger ASGs where (for example) a 100 instance ASG may be asked to scale to 200 (temporarily). Users may find that some instances never register, and this causes EKS Rolling Update to hang indefinitely waiting for the registered EKS node count to match the instance count.

If this happens, you may want to consider batching.

For example, if the ASG will be scaled from 100 instances to 200 instances, specifying a batch size of 10 will result in the ASG first scaling to 110, then 120, 130, etc instances until 200 is reached. Once the desired count is reached, the tool will proceed with the normal draining/scale-in operations.

Examples

• Plan

$ python eks_rolling_update.py --cluster_name YOUR_EKS_CLUSTER_NAME --plan

• Apply Changes

$ python eks_rolling_update.py --cluster_name YOUR_EKS_CLUSTER_NAME

• Cluster Autoscaler

If using cluster-autoscaler, you must let eks-rolling-update know that cluster-autoscaler is running in your cluster by exporting the following environment variables:

$ export  K8S_AUTOSCALER_ENABLED=1 \
          K8S_AUTOSCALER_NAMESPACE="CA_NAMESPACE" \
          K8S_AUTOSCALER_DEPLOYMENT="CA_DEPLOYMENT_NAME"

• Disable operations on cluster-autoscaler

$ unset K8S_AUTOSCALER_ENABLED

• Configure tool via .env file

Rather than using environment variables, you can use a .env file within your working directory to load updater settings. e.g:

$ cat .env
DRY_RUN=1

Docker

Although no public Docker image is currently published for this project, feel free to use the included Dockerfile to build your own image.

make docker-dist version=1.0.DEV

After building the image, run using the command

docker run -ti --rm \
  -e AWS_DEFAULT_REGION \
  -v "${HOME}/.aws:/root/.aws" \
  -v "${HOME}/.kube/config:/root/.kube/config" \
  eks-rolling-update:latest \
  -c my-cluster

Pass in any additional environment variables and options as described elsewhere in this file.

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

License

This project is licensed under the Apache 2.0 License - see the LICENSE file for details