Hi all we are looking for practically and tested guide or reference for kubernetes master high availability or other solution for master node fail over.
There are definitely folks running Kubernetes HA masters in production following the instructions for High Availability Kubernetes Clusters. As noted at the beginning of that page, it's an advanced use case and requires in-depth knowledge of how the Kubernetes master components work.
Related
I have some questions according to https://docs.konghq.com/2.0.x/clustering
I’ll really appreciated if someone help me.
1)according to Clustering Reference I need a load balancer , could you please introduce me a free one which I can use in front of my Kong nodes?
2)I still don’t know is it better to implement kong nodes in different VMs or in Docker using docker-compose file for a fully production environment ?
Best Regards,
I think both your questions are highly dependent of your tech stack / architecture.
Regarding the load balancing question, I can think of several options for different options:
DNS Load Balancing, which depends on client side load balancing
Services in an Kubernetes/OpenShift environment, which provide load balancing across a bunch of pods
AWS Load Balancers, if you deploy Kong directly on EC2 machines. (I am sure other cloud providers have simar concepts)
Whether you deploy Kong on a VM or as a Docker Container is quite hard to answer. It depends on your tech stack you already have in place and on your requirements (see https://docs.konghq.com/2.0.x/sizing-guidelines/). However, I would not recommend to use docker-compose for this use case. If you decide for a Docker-based solution you should take a look at container management solutions such as Kubernetes or OpenShift. There you have solved the management of your Kong containers (such as how many replicas are running and what happens if one replica is failing) and you have solved the load balancing issue (by using Kubernetes/OpenShift services objects).
Currently hazelcast is using cloud discovery for communication.
So if there are 4 kubernetes pods and each of them is having in-memory hazelcast. whenever hazelcast cache is updated in one of the pod, it gets updated in one of the other pod. but in case both of these pods get downscaled and get terminated, the data which is only in these 2 pods is lost. Can we have something like redis where we can provide server, port of the hazelcast cluster and it will be independent of kubernetes pod
Please check the following Blog Post ("Scale without Data Loss!" section) to read how to scale Hazelcast cluster on Kubernetes to avoid data loss.
Also, you can check the official README of hazelcast/hazelcast-kubernetes plugin. There is a section dedicated to scaling there.
I need an HA redis solution instead of a single instance. Should I use cluster or Sentinel? I have tried to find out the difference between them, there is no official document about this, thanks a lot.
Well, for a HA redis solution , it depends upon the number of nodes you want to configure.
According to offical Redis documentation on Redis-cluster and Redis-sentinel both provides HA Solution but.....
Redis Sentinel provides high availability for Redis. In practical terms this means that using Sentinel you can create a Redis deployment that resists without human intervention to certain kind of failures.
Redis Cluster provides a way to run a Redis installation where data is automatically sharded across multiple Redis nodes.
Redis Cluster also provides some degree of availability during partitions, that is in practical terms the ability to continue the operations when some nodes fail or are not able to communicate. However the cluster stops to operate in the event of larger failures (for example when the majority of masters are unavailable).
For more information please refer the official docs :)
Cheers
For a large online application, use k8s to run it. The scale maybe daily activity user 500,000.
The application inside k8s need messaging feature - Pub/Sub, there are these options:
Kafka
RabbitMQ
Redis
Kafka
It needs zookeeper and good to run on os depends on disk I/O. So if install it into k8s cluster, how? The performance will be worse?
And, if keep Kafka outside of the k8s cluster, connect Kafka from application inside the k8s cluster, how about that performance? They are in the different layer, won't be slow?
RabbitMQ
It's slow than Kafka, but for a daily activity user 500,000 application, is it good enough? If so, maybe it's a good choice.
Redis
It's another option. Maybe the most simple one. But from the internet I got that it will lose message sometimes. If true, that's terrible.
So, the most important thing is, use Kafka(also with zookeeper) on k8s, good or not in this use case?
Yes, running Kafka on Kubernetes is great. Check out this example: https://github.com/Yolean/kubernetes-kafka. It includes ZooKeeper and Kafka as StatefulSets.
PS. Running any of the services in your question on Kubernetes will be pleasant. You can Google the name of the service and "kubernetes" and find example manifests. Many examples here: https://github.com/kubernetes/charts.
For Kafka, you can find some suggestion here. Kubernetes 1.7+ supports local persistent volume, which may be good for Kafka deployment.
You can also take a look to the following project :
https://github.com/EnMasseProject/barnabas
It's about running Kafka on Kubernetes and OpenShift as well. It provides deploying with StatefulSets with persistent volumes or just in memory (for developing or just testing purpose). It provides deploying for Kafka Connect and Prometheus metrics as well.
Another simple configuration of Kafka/Zookeeper on Kubernetes in DigitalOcean with external access:
https://github.com/StanislavKo/k8s_digitalocean_kafka
You can connect to Kafka from outside of AWS/DO/GCE by regular binary protocol. Connection is PLAINTEXT or SASL_PLAINTEXT (user/password).
Kafka cluster is StatefulSet, so you can scale cluster easily.
For end to end devops automation I want to have an environment on demand. For this I need to Spun up and environment on kubernetes which is eventually hosted on GCP.
My Use case
1. Developer Checks in the code in feature branch
2. Environment in Spun up on Google Cloud with Kubernetes
3. Application gets deployed on Kubernetes
4. Gets tested and then the environment gets destroyed.
I am able to do everything with Spinnaker except #2. i.e create Kube Cluster on GCP using Spinnaker.
Any help please
Thanks,
Amol
I'm not sure Spinnaker was meant for doing what the second point in your list. Spinnaker assumes a collection of resources (VM's or a Kubernetes cluster) and then works with that. So instead of spinning up a new GKE cluster Spinnaker makes use of existing clusters. I think it'd be better (for you costs as well ;) if you seperate the environments using Kubernetes namespaces.