We are migrating some windows components (.net 4.5) to Linux containers (.net core). Existing system is a file processor, which watches a shared location and processes file from there. We can't force existing system to start dropping file at some other location, so new containerised application has to access from same shared location. Can a windows share be seen from docker containers? If yes, then how can I use Kubernete deployment file to achieve it?
Please advise.
Regards,
This feature is not working by default, but yes, you can do this. Here is the project which allows you to do this in a proper way. After volume driver setup, you can use Windows share as PersistentVolume in your Kubernetes cluster.
*Updates
Also you can use windows share as nfs volume in Kubernetes. Here you can find some examples of using nfs in Kubernetes
Related
I'm using docker desktop (4.X) over win10 pro. We are building Windows applications and using Windows containers.
On our setup, the folder C:\ProgramData\Docker(images/windowsfilter/tmp & co) can grow up to hundreds of GB, and i need to move this folder to an alternative location.
Again, i am using WINDOWS CONTAINERS (i do not care about wsl2 or hyper-v specific solutions)
I tried moving / creating a junction between
C:\ProgramData\ Docker => D:\DockerData, but windows containers backend does not start.
If i switch back to linux containers, everything is working fine (and i know how to move WSL2 vhdx, if needed, but again, i DO NOT NEED THAT information).
Moving HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Windows NT\CurrentVersion\ProfileList\ProgramData location BEFORE installing docker desktop, works, but it is not an acceptable solution
I tried configuring data-root directory in %USERPROFILE%.docker\windows-daemon.json, But it does not work, windows containers backend does not start.
Please give me a reliable way to move the C:\ProgramData\Docker folder to another location.
Unfortunately, when utilizing Windows Containers, it is not yet feasible to relocate the C:ProgramDataDocker folder to another location. This is so that container images and other data can be stored in this directory, which the Docker for Windows service is hard-coded to utilize.
You might try using a symbolic link to reroute the C:ProgramDataDocker folder to an other place as a solution. This may not be a reliable approach, though, as the Docker for Windows service might not handle the symbolic link correctly, which would prevent the service from starting.
New to Docker/K8s. I need to be able to mount all the containers (across all pods) on my K8s cluster to a shared file system, so that they can all read from and write to files on this shared file system. The file system needs to be something residing inside of -- or at the very least accessible to -- all containers in the K8s cluster.
As far as I can tell, I have two options:
I'm guessing K8s offers some type of persistent, durable block/volume storage facility? Maybe PV or PVC?
Maybe launch a Dockerized Samba container and give my others containers access to it somehow?
Does K8s offer this type of shared file system capability or do I need to do something like a Dockerized Samba?
NFS is a common solution to provide you the file sharing facilities. Here's a good explanation with example to begin with. Samba can be used if your file server is Windows based.
You are right you can use the File system in the backend with Access Mode ReadWriteMany.
ReadWirteMany will allow the container to mount to a single PVC and write on it.
You can also use the NFS system as suggested by the gohm'c, for NFS you can set up the GlusterFS or MinIO containers.
Read more about the Access mode ReadWriteMany : https://kubernetes.io/docs/concepts/storage/persistent-volumes/#access-modes
I have created a simple PHP api application that works with a mysql database to store data. I have been experimenting with Kubernetes on my Windows 10 machine through Minikube.
I have just about got my head round the ideas involved, yet I’m not sure about how to implement this properly. So far I have used Kompose to create a set of yaml files from an existing docker-compose file. This has been half successful.
To get my application code into a pod hosting PHP, I have been using hostPath to share from my local machine. I mount to the minikube machine and share from there. I was having trouble sharing by other means. The application code is hosted in a github repo.
My questions are:
Is mounting my application code into a pod (assuming this is similar to what happens in docker) the correct way to do this? I’m not clear exactly what information is held on an image retrieved from the docker hub. Although I have read up on containers isolating the build environment from your machine.
How does this approach to translate into a production environment hosted on a cloud? I see there are various storage types. I had for example, wanted to try deploying on AWS just to see how this would work in practice.
I’m really looking for guidance to go from the tutorials found on the web working on my machine, to something that could be done for a customer hosted on the cloud. This might scale up to a more microservices style architecture over time.
The approach you are describing is mostly for development setups, where you want to mount your code into the container as a volume so you don't have to rebuild every time your code changes. Typically done with a docker-compose file.
For production setups, you want the docker image to correctly work and only mount volumes to data you want to persist, typically databases are the core example. For this EKS is deeply integrated into the AWS infrastructure and will create EBS volumes on demand. You don't need to provision any volume or even care for most cases (unless you need multiple read-write volumes needed for scaling).
For a PHP application you really should not persist any data in the pod, because it will create other issues when you need to scale the application. Also, a good approach for managing files that need to persist is S3 (AWS simple storage service).
So generally speaking, you need a deployment per application a service to access each pod on that application and then an ingress object to route traffic from the internet to each pod.
Your application docker image is really the core. You just build it with your code inside. Make sure to pass configuration using environment variable or configuration file so you can connect to the database.
Now for kubernetes, for each compoment (e.g. PHP application, MySQL) you will most likely create a deployment k8s manifest that points to the docker image and add some configuration environment variables.
For production, you will need persistence volume. On aws you can simply use EBS-backed volumes
To get traffic from Internet to your PHP application, you will need to add one or more k8s components:
K8s Service manifest that exposes your PHP deployment/pod on a stable address. If you only have q or very few services, you can use LoadBalancer which on cloud like AWS will create an ALB/ELB (might need to add annotation to your service)
An ingress which is just a reverse proxy (contour, nginx, traefik). On cloud environment it will map to an ALB/ELB. The advantage of this is that you can have a single ALB for all your services i.e. save money. Also you can configure routing path or TLS termination in one place.
How should applications be scripted/automatically deployed when in LXD containers?
For example is best way to deploy applications in LXD containers to use a bash script (which deploys an application)? How to execute this bash script inside the container by executing a command on the host?
Are there any tools/methods of doing this in a similar way to Docker recipes?
In my case, I use Ansible to:
build the LXD containers (web, database, redis for example).
connect to the containers and deploy the services and code needed.
you can build your own images for example with the services and/or code already deployed and build specific containers from this images.
I was doing this from before LXD had Ansible support (Ansible 2.2) i prefer to use ssh instead of lxd connection, when i connect to the containers to deploy services/code. they comes with a profile where i had setup my ssh public key (to have direct ssh connection by keys ... no passwords)
Take a look at my open source project on bitbucket devops_lxd_containers It includes:
Scripts to build lxd image templates including Apache, tomcat, haproxy.
Scripts to demonstrate custom application image builds such as Apache hosting and key/value content and haproxy configured as a router.
Code to launch the containers and map ports so they are accessible to the larger network
Code to configure haproxy as layer 7 proxy to route http requests between boxes and containers based on uri prefix routing. Based on where it previously deployed and mapped ports.
At the higher level it accepts a data drive spec and will deploy an entire environment compose of many containers spread across many hosts and hook them all up to act as a cohesive whole via a layer 7 proxy.
Extensive documentation showing how I accomplished each major step using code snippets before automating.
Code to support zero-outage upgrades using the layer7 ability to gracefully bleed off old connections while accepting new connections at the new layer.
The entire system is built on the premise that image building is best done in layers. We build a updated Ubuntu image. From it we build a hardened Ubuntu image. From it we build a basic Apache image. From it we build an application specific image like our apacheKV sample. The goal is to never rebuild any more than once and to re-use the common functionality such as the basicJDK as the source for all JDK dependent images so we can avoid having duplicate code in any location. I have strived to keep Image or template creation completely separate from deployment and port mapping. The exception is that I could not complete creation of the layer 7 routing image until we knew everything about how other images would be mapped.
I've been using Hashicorp Packer with the ansible provisioner using ansible_connection = lxd
Some notes here for constructing a template
When iterating through local files on your host system you may need to be using ansible_connection = local (e.g for stat & friends)
Using local_action in ansible with the lxd connection is still
action inside the container when using stat (but not with include_vars & lookup function for files)
Using lots of debug messages in Ansible is helpful to know which local environment ansible is actually operating in.
I'm surprised no one here mentioned Canonicals own tool for managing LXD.
https://juju.is
it is super simple, well supported, and the only caveat is it requires you turn off ipv6 at the LXD/LXC side of things (in the network bridge)
snap install juju --classic
juju bootstrap localhost
from there you can learn about juju models, deploy machines or prebaked images like ubuntuOS
juju deploy ubuntu
I'm using Kubernetes deployment with persistent volume to run my application, like this example;
https://github.com/kubernetes/kubernetes/tree/master/examples/mysql-wordpress-pd
, but when I try to add more replicas or autoscale, all the new pods try to connect to the same volume.
How can I simultaneously auto create new volumes for each new pod., like statefulsets(petsets) are able to do it.
The conclusion I reached for K8S 1.6 is you can't. However, you can use NFS. If, like CrateDB, your cluster can create a folder for each node under the volume mount, then you can auto-scale. So, I auto-scale CrateDB as a Deployment using this configuration:
https://github.com/erik777/kubernetes-cratedb
which relies on an nfs-server, which I deploy as an RC with PVC/PV:
SAME_BASE/kubernetes-nfs-server
It is on my TODO list to exlpore distributed file systems such as GluterFS. For K8S Deployments, your choice of file system is your remedy.
You can also engage the scalability and storage SIGs in the K8S community to help prioritize this use-case. Adding the capability to K8S removes the requirement for a clustering solution to handle node separation in a shared volume, as well as prevent the introduction of additional points of failure between the clustered app and the PV.
GITHUB kubernetes/community
Hopefully, we can see a K8S OTB solution by 2.0.
(NOTE: Had to change 2 of the GITHUB links because I don't have "10 reputation")