I have a Scale Set I provisioned in Azure through Terraform.
(A scale set is an implicit availability set with 5 fault domains and 5 update domains.[ [1]])
I need to find out which Fault Domain each instance is in, so that I can configure my application cluster based on this, for improved redundancy.
So far, I have found only a single post remotely addressing thisenter link description here.
More context:
I can switch to regular VMs rather than a scale set if there is absolutely no other way.
I use ansible's dynamic inventory (azure_rm.py) which I have already customised to work with Scale Sets. If the solution can leverage this, extra kudos :)
My application allows me to define topology (datacentre, rack, etc.) and I am deploying it in a single Azure datacentre. Maybe I have missed a different solution?
Many many thanks,
–Jeff
I have solved this by using the 169.254.169.254 'virtual IP' that allows a VM in the could to read its own metadata.
Specifically, I am running:
curl -H Metadata:true --silent "http://169.254.169.254/metadata/instance/compute/platformFaultDomain?api-version=2017-03-01&format=text"
in an Ansible task, and then using Ansible's local facts to make this available as an Ansible variable on the host.
Related
We are using ECS Fargate containers to deploy all of our services (~10) and want to follow Blue/Green Deployment.
We have deployed all the services under BLUE flag where target groups are pointing to the services.
In CICD, New Target groups are created and having slightly different forward rules to allow testing without any issue.
Now, my System is running with 2 kind of target groups, services and task definition -
tg_blue, service_blue, task_blue → pointing to old containers and serving live traffic
tg_green, service_green, task_green → pointing to new containers and do not have any traffic.
All above steps are done in Terraform.
Now, I want to switch the traffic and here I am stuck, How to Switch the Traffic and How the next Deployment will look like?
I would go for AWS native solution if no important reasons against. I have on my mind CodeDeploy. It switches in automatic way between TGroups.
Without CDeploy, you need to implement weighted balancing among two TGroups and adjust them later on. That is extra work.
Whole flow is quite good explained on this YT video.
I have successfully deployed a multi master Kubernetes cluster using the repo https://github.com/kubernetes-sigs/kubespray and everything works fine. But when I stop/terminate a node in the cluster, new node is not joining to the cluster.I had deployed kubernetes using KOPS, but the nodes were created automatically, when one deletes. Is this the expected behaviour in kubespray? Please help..
It is expected behavior because kubespray doesn't create any ASGs, which are AWS-specific resources. One will observe that kubespray only deals with existing machines; they do offer some terraform toys in their repo for provisioning machines, but kubespray itself does not get into that business.
You have a few options available to you:
Post-provision using scale.yml
Provision the new Node using your favorite mechanism
Create an inventory file containing it, and the etcd machines (presumably so kubespray can issue etcd certificates for the new Node
Invoke the scale.yml playbook
You may enjoy AWX in support of that.
Using plain kubeadm join
This is the mechanism I use for my clusters, FWIW
Create a kubeadm join token using kubeadm token create --ttl 0 (or whatever TTL you feel comfortable using)
You'll only need to do this once, or perhaps once per ASG, depending on your security tolerances
Use the cloud-init mechanism to ensure that docker, kubeadm, and kubelet binaries are present on the machine
You are welcome to use an AMI for doing that, too, if you enjoy building AMIs
Then invoke kubeadm join as described here: https://kubernetes.io/docs/setup/independent/high-availability/#install-workers
Use a Machine Controller
There are plenty of "machine controller" components that aim to use custom controllers inside Kubernetes to manage your node pools declaratively. I don't have experience with them, but I believe they do work. That link was just the first one that came to mind, but there are others, too
Our friends over at Kubedex have an entire page devoted to this question
Well, for the last 2 days I battled this documentation:
https://learn.microsoft.com/en-au/azure/aks/static-ip
and
https://learn.microsoft.com/en-au/azure/aks/ingress-own-tls
First of all I ensured that I had my aks k8s cluster upgraded to 1.11.5, so there is no question about having the static IP in a different resource group.
Overall, I could not get the static IP really working. With dynamic everything sounds fine, but I cannot add a A record for a dynamic IP.
I managed to deploy everything successfully, but any curl ip.. does not work. I did run exec -ti locally, and locally everything is fine.
Could someone please point me to a GitHub config or article that has this configuration running? As a disclaimer I know azure very well, so well the service principal assignments are well done, etc. However, I am new, only a few months on k8s.
Thanks in advance for any suggestion.
I can share logs if needed but believe I did check everything from dns to ingress routes. I am worried that this doc is not good and I am just loosing my time.
Answering myself this question, after quite a journey, for when I get older and I forget what I've done, and maybe my nephew will save some hours someday.
First, it's important:
In the values provided to nginx-ingress chart template, there are 2 annotations that are important:
service.beta.kubernetes.io/azure-load-balancer-resource-group: "your IP's resource group"
externalTrafficPolicy: "Local"
Here are all the values documented: https://github.com/helm/charts/blob/master/stable/nginx-ingress/values.yaml
The chart can be deployed near your service's namespace, it should not be in kube-system (with my current knowledge I don't find a reason to have it in system).
Second, could be misleading
There is a delay of ~30+ seconds (in my case) from the moment when IP appeared in the kubectl get services --watch and till the moment curl -i IP was able to answer the call. So, if you have automation or health probes then ensure that you have 1 - 2 mins added to wait. Or maybe take better nodes, bare metal machines.
Look at GCE and DO for the same setup as might help:
https://cloud.google.com/community/tutorials/nginx-ingress-gke
https://www.digitalocean.com/community/tutorials/how-to-set-up-an-nginx-ingress-with-cert-manager-on-digitalocean-kubernetes
The guys at DO, are good writes as well.
Good luck!
Based on your comments, it seems that you are trying to override the externalIPs but use the default value of the helm chart for controller.service.type which is LoadBalancer. What you might want to do is to keep controller.service.type to LoadBalancer and set controller.service.loadBalancerIP with your static IP instead of overriding externalIPs.
Here some documentation from microsoft.
I am building a micro-services project using docker.
one of my micro-services is a listener that should get data from various number of sources.
What i'm trying to achieve is the ability to start and stop getting data from sources dynamically.
For example in this drawing, i have 3 sources connected to 3 dockers.
My problem starts because i need to create another docker instance when a new source is available. In this example lets say source #4 is now available and i need to get his data (I know when a new source became available) but i want it to be scaled automatically (with source #4 information for listening)
I came up with two solutions, each has advantages and disadvantages:
1) Create a docker pool of a large number of docker running the listener service and every time a new source is available send a message (using rabbitmq but i think less relevant) to an available docker to start getting data.
in this solution i'm a little bit afraid of the memory consumption of the docker images running for no reason - but it is not a very complex solution.
2) Whenever a new source is becoming available create a new docker (with different environment variables)
With this solution i have a problem creating the docker.
At this moment i have achieved this one, but the service that is starting the dockers (lets call it manager) is just a regular nodejs application that is executing commands on the same server - and i need it to be inside a docker container also.
So the problem here is that i couldn't manage create an ssh connection from the main docker to create my new Docker.
I am not quite sure that both of my solutions are on track and would really appreciate any suggestions for my problem.
Your question is a bit unclear, but if you just want to scale a service horizontally you should look into a container orchestration technology that will allow you that - For example Kubernetes. I recommend reading the introduction.
All you would need to do for adding additional service containers is to update the number of desired replicas in the Deployment configuration. For more information read this.
Using kubernetes (or short k8s) you will benefit from deployment automation, self healing and service discovery as well as load balancing capabilities in addition to the horizontal scalability.
There are other orchestration alternatives, too ( e.g. Docker Swarm), but I would recommend to look into kubernetes first.
Let me know if that solves your issue or if you have additional requirements that weren't so clear in your original question.
Links for your follow up questions:
1 - Run kubectl commands inside container
2 - Kubernetes autoscaling based on custom metrics
3 - Env variables in Pods
I want to import a number of private virtual machines that only I can launch using the ARM REST API.
How do I do that? I cannot find instructions.
This question is a little unclear - do you have a number of already pre-defined virtual machine images that you want to start up, is it multiple copies of the same machine for a load balanced scenario or something else?
Also, you say "Only I can launch" what do you mean by that? By definition, when you describe your resources using Azure Resource Manager, you're essentially making a desired state configuration that you then deploy to Azure, and it will create all those machines for you.
If it's simply a question of creating the configuration file, you can try out cool stuff such as http://Armviz.io to set up your stuff. Alternatively, if you already have a group of resources that you'd like to capture into a script - go here:
http://capturegroup.azurewebsites.net