Can I replicate data between Kubernetes PV into two separate clusters situated in different data centers?
I have a cluster with associated PV running in Primary site. I have a separate cluster running in DR site.
How do I continuously replicate data in primary site to DR site so that when application is running from from DR? The data written to PR PVs are available in DR.
Application writes files to the PV like xls, csv etc.
I can use any OSS storage orchestrator like openebs, rook, storageos etc.
Database is outside of kubernetes.
Forget Kubernetes for some time. End of the day, you are talking sync files between two storages. Mounting it into Kubernetes as PV is just your choice. So it can be as simple as a rsync setup between two storages?
Narain is right. Kubernetes doesn't contain any functionality that would allow you to synchronize two PVs used by two different clusters. So you would need to find your own solution to synchronize those two filesystems. It can be an existing solution like lsyncd, proposed in this thread or any custom solution like the above mentioned rsync which can be wrapped into a simple bash script and run periodically in cron.
You can replicate same PV across different nodes within same cluster using openEBS Replicated Volumes as long as you are using a proper openebs engine.
https://openebs.io/docs/#replicated-volumes
Related
I am new to launching ES for the production environment. I want to create production-ready ElasticSearch clusters having master nodes and data and backup nodes and etc. I read tutorials on the internet regarding this matter including the official document but I cannot get my head around the topic in the official document it's running multiple clusters under one machine what if that machine goes down for some reason? where are the master nodes playing in that scenario? where are the backup nodes? to protect against data loss?
I want to know if there are any straightforward solutions that I can use for deploying the ES on multiple machines serving the same purpose (for one project with specific data types) that can be easily distributed and fault-tolerant?
Running multiple containers on a single host makes sense if you have a lot of resources on a given host that you want to partition up and use efficiently. then you can have multiple hosts with multiple Elasticsearch containers forming a cluster
If you do that, look at using allocation awareness to make sure shards are adequately balanced so that the loss of a single host will mean you maintain your data
I'm starting to learn Kubernetes recently and I've noticed that among the various tutorials online there's almost no mention of Volumes. Tutorials cover Pods, ReplicaSets, Deployments, and Services - but they usually end there with some example microservice app built using a combination of those four. When it comes to databases they simply deploy a pod with the "mongo" image, give it a name and a service so that other pods can see it, and leave it at that. There's no discussion of how the data is written to disk.
Because of this I'm left to assume that with no additional configuration, containers are allowed to write files to disk. I don't believe this implies files are persistent across container restarts, but if I wrote a simple NodeJS application like so:
const fs = require("fs");
fs.writeFileSync("test.txt", "blah");
const value = fs.readFileSync("test.txt", "utf8");
console.log(value);
I suspect this would properly output "blah" and not crash due to an inability to write to disk (note that I haven't tested this because, as I'm still learning Kubernetes, I haven't gotten to the point where I know how to put my own custom images in my cluster yet -- I've only loaded images already on Docker Hub so far)
When reading up on Kubernetes Volumes, however, I came upon the Ephemeral Volume -- a volume that:
get[s] created and deleted along with the Pod
The existence of ephemeral volumes leads me to one of two conclusions:
Containers can't write to disk without being granted permission (via a Volume), and so every tutorial I've seen so far is bunk because mongo will crash when you try to store data
Ephemeral volumes make no sense because you can already write to disk without them, so what purpose do they serve?
So what's up with these things? Why would someone create an ephemeral volume?
Container processes can always write to the container-local filesystem (Unix permissions permitting); but any content that goes there will be lost as soon as the pod is deleted. Pods can be deleted fairly routinely (if you need to upgrade the image, for example) or outside your control (if the node it was on is terminated).
In the documentation, the types of ephemeral volumes highlight two major things:
emptyDir volumes, which are generally used to share content between containers in a single pod (and more specifically to publish data from an init container to the main container); and
injecting data from a configMap, the downward API, or another data source that might be totally artificial
In both of these cases the data "acts like a volume": you specify where it comes from, and where it gets mounted, and it hides any content that was in the underlying image. The underlying storage happens to not be persistent if a pod is deleted and recreated, unlike persistent volumes.
Generally prepackaged versions of databases (like Helm charts) will include a persistent volume claim (or create one per replica in a stateful set), so that data does get persisted even if the pod gets destroyed.
So what's up with these things? Why would someone create an ephemeral volume?
Ephemeral volumes are more of a conceptual thing. The main need for this concept is driven from microservices and orchestration processes, and also guided by 12 factor app. But why?
Because, one major use case is when you are deploying a number of microservices (and their replicas) using containers across multiple machines in a cluster you don't want a container to be reliant on its own storage. If containers rely on their on storage, shutting them down and starting new ones affects the way your app behaves, and this is something everyone wants to avoid. Everyone wants to be able to start and stop containers whenever they want, because this allows easy scaling, updates, etc.
When you actually need a service with persistent data (like DB) you need a special type of configuration, especially if you are running on a cluster of machines. If you are running on one machine, you could use a mounted volume, just to be sure that your data will persist even after container is stopped. But if you want to just load balance across hundreds of stateless API services, ephemeral containers is what you actually want.
I have this idea for what I think should happen with my project, but I want to check in and see if this works on a theoretical level first. Basically I am working on a Django site that is run on Kubernetes, but am struggling a little bit about which way I should set up my replicationSet/statefulSet to manage uploaded content (images).
My biggest concern is trying to find out how to scale and maintain uploaded content. My first idea is that I need to have a single volume that has these files written to it, but can I have multiple pods write to the same volume that way while scaling?
From what I have gathered, it doesn't seem to work that way. It sounds more like each pod, or at least each node, would have it's own volume. But would a request for an image reach the volume it is stored on? Or should I create a custom backend program to move things around so that it is served off of a NGINX server like my other static content?
FYI - this its my first scalable project lol. But I am really just trying to find the best way to manage uploads... or a way in general. I would appreciate any explanations, thoughts, or fancy diagrams on how something like this might work!
Hello I think you should forget kubernetes a bit and think of the architecture and capabilities of your Django application. I guess you have built a web app, that offers some 'upload image' functionality, and then you have code that 'stores' this image somewhere. On the very simple scenario if you run your app on your laptop, the you web app, is configured to save this content to a local folder, a more advanced example is that you deploy your application to a VM or a cloud vm e.g an AWS EC2 instance, and your app is saving the files to the local storage of this EC2 instance. The question is twofold - what happens if we have 2 instances of your web app deployed - can the be configured and run - so that they 'share' the same folder to save the images? I guess this is what you want, other wise your app would not scale horizontally , each user would have to hit each individual instance - in order to upload or retrieve specific images. So having that in mind that is a design decision of your application, which I am pretty sure you have already worked it out, the you need to think - how can I share a folder? a bucket so that all my instances of my web app can save files? If you spinned 3 different vms, on any cloud, you would have to use some kind of clour storage, so that all three instances point to the same physical storage location, or an NFS drive or you could save your data to a cloud storage service S3!
Having all the above in mind, and clearly understanding that you need to decouple your application from the notion of locale storage especially if you want to make it as as stateless as it gets (whatever that means to you), having your web app, which is packaged as a docker container and deployed in a kubernetes cluster as a pod - and saving files to the local storage is not going to get any far, since each pod, each docker container will use the underlying kubernetes worker (vm) storage to save files, so another instance will be saving files on some other vm etc etc.
Kubernetes provides this kind of abstraction for applications (pods) that want to 'share' within the kubernetes cluster, some local storage and of course persist it. Something that I did not add above is that pod and worker storage (meaning if you save files in the kubernetes worker or pod) once this vm / instance is restarted you will loose your data. So you want something durable.
To cut a long story short,
1) you can either to deploy your application / pod along with a Persistent Volume Claim assuming that your kubernetes cluster supports it. What is happening is that you can mount to your pod some kind of folder / storage which will be backed up by whatever is available to your cluster - some kind of NFS store. https://kubernetes.io/docs/concepts/storage/persistent-volumes/
2) You can 'outsource' this need to share a common local storage to some external provider, e.g a common case use an S3 bucket, and not tackle the problem on kubernetes - just keep and provision the app within kubernetes.
I hope I gave you some basic ideas.
Note: Kubernetes 1.14 now (March 2019) comes with Durable Local Storage Management is Now GA, which:
Makes locally attached (non-network attached) storage available as a persistent volume source.
Allows users to take advantage of the typically cheaper and improved performance of persistent local storage kubernetes/kubernetes: #73525, #74391, #74769 kubernetes/enhancements: #121 (kep)
That might help securing a truly persistent storage for your case.
As noted by x-yuri in the comments:
See more with "Kubernetes 1.14: Local Persistent Volumes GA", from Michelle Au (Google), Matt Schallert (Uber), Celina Ward (Uber).
you could use ipfs https://pypi.org/project/django-ipfs-storage/
creating a container with this image https://hub.docker.com/r/ipfs/go-ipfs/ in the same pod you can ref as 'localhost'
Is it possible to failover the traffic from a mysql k8s deployment running in one datacenter to a deployment running in another datacenter along with its storage?
If yes , Do we need to spread the same k8s cluster on multiple datacenters or we have to run separate k8s clusters in each datacenter?
How k8s will ship or manage the storage volume across the datacenters? Do we need a special type of cloud storage for that purpose?
note: I just qouted mysql as an example of application that needs to store some data , it can be anything stateful that needs to carry over its data volumes. it is not that kind of HA like mysql-HA , it is just starting serving the application as it is from somewhere else automatically along with its data. any application that stores data to volume.
How can we achieve HA for our stateful application across the datacenters using k8s.
Thanks
You don't need to use Kubernetes to achieve HA.
I would recommend using MySQL Replication(i.e. Master/Slave configuration) to achieve HA. More info in the docs on how to set replication up.
In one data center, you would have a Master, and in your other data center, you would have the slave. You can even have multiple slaves in multiple data centers.
If problems arise on the master, you can automatically failover to a slave using the mysqlfailover utility. This way you have your data in 2 data centers that is in sync.
I'm not sure if this exactly fits your use cases, but it is one option for enabling HA on your MySQL database.
I'm currently using RethinkDB across cloud servers by manually joining each server at setup. I'm interested in moving over to a Swarm approach to make scaling and failover easier. The current approach is cumbersome to scale.
In the current manual approach, I simply create a local folder on each server for RDB and mount as a volume to store its data. However, using a Swarm means that I'd need to handle volumes more dynamically. Each container will need a distinct volume to keep data separate in case of errors.
Any recommendations on how to handle this scenario? A lot of the tutorials I've seen so far mention Flocker to manage persistent storage, but I can't see that being handled dynamically.
Currently I am struggling with a situation like this. I've created a temporary fix with GlusterFS.
What you do is install GlusterFS on all the Docker nodes and mount the folders. This way the data exists on all the nodes. But this is less than ideal if you have a lot of writes. This could be slow because of the way Gluster treats your data replication to prevent data loss. It is solid, but I have some issues with the speed.
In your case I would suggest looking into Flocker. Flocker is a volume plugin that migrates your data when a container moves to another host. I haven't had any experience with it, but in my case the concept of Flocker renders useless, I need my data in multiple containers on multiple hosts (Read only) This is where Gluster came into play