How to configure Redis in Spring XD distributed runtime? - redis

The Spring XD documentation (http://docs.spring.io/spring-xd/docs/1.0.0.RC1/reference/html/) recommends Zookeeper to be run in ensemble so that Zookeeper is highly available. There is not lot of details about Redis about high availability.
If I were to run 2 XD admin instances and say 4 Container instances, I see 3 options
should I run a Redis instance in each server that runs container or admin? In that case does the Distributed runtime work properly with different Redis instances handling transport of different modules?
OR
should I run 1 Redis instance in a separate server and configure all XD instances to talk to this instance? In this case 1 instance of Redis is not highly available
OR
should I configure Redis cluster or Redis Sentinel high availability? I am not sure how XD or any other client will connect to a cluster or HA.
Thanks

I would suggest that you run a single Redis instance, there are some settings for persistence that you can change that may meet your requirements.
http://redis.io/topics/persistence
We will be adding support for Redis Sentinal, certainly in the Spring XD 1.1 release, but possibly in a maintenance release depending on what library changes we need to pick up. Spring Data Redis and Spring Boot have recent updates to support Redis Sentinal.
If you are using Redis as a message transport and want higher guarantees, I would switch to using Rabbit HA configuration of the MessageBus.
Cheers,
Mark

Related

How can I setup Redis Cluster mode or master slave mode in PCF?

This is regarding the use case where we are trying to use the Redis in PCF (Pivotal Cloud Foundry). In our use case, we will refresh the Redis cache daily once or twice with the required data and then API will query Redis and then provide the response.
One thing of particular concern for us is that we want API queries to happen from Redis only that means Redis to be available at all times. But whenever we are refreshing the Redis DB, Redis would not be able to serve the APIs since it is refreshing the keys. To avoid that we wanted to setup a Redis in cluster mode or master-slave mode so if one instance is being written another can be read from.
How can we setup Redis cluster or master-slave mode in PCF and then fulfil our requirement?
Please provide any other suggestions as well that you may have.
At the time I write this, the Redis for Pivotal Platform product does not support clustering. See Availability, in the docs here -> https://docs.pivotal.io/redis/2-3/erc.html#offerings.
All Redis for Pivotal Platform services are single VMs without clustering capabilities. This means that planned maintenance jobs (e.g., upgrades) can result in 2–10 minutes of downtime, depending on the nature of the upgrade. Unplanned downtime (e.g., VM failure) also affects the Redis service.
Redis for Pivotal Platform has been used successfully in enterprise-ready apps that can tolerate downtime. Pre-existing data is not lost during downtime with the default persistence configuration. Successful apps include those where the downtime is passively handled or where the app handles failover logic.
If you require clustered Redis, you'd need to look at a different offering. Redis Labs has some offerings that integrate with PCF, you could use a Cloud Provider's Redis offering, or you could host your own.
If the solution you use isn't integrated into PCF, you can create a user-provided service with cf cups and provide the Redis credentials to your application that way. It will function just like a Redis service instance created through the marketplace.

Redis Enterprise Cluster aware client

Can anyone explain to me what is aware client in Redis Enterprise ?
I found this post: Redis Enterprise Clustering Command Error 'CLUSTER'
I try to use Redis Enterprise Cluster with docker.
I create 3 docker redis nodes with two shards for better scalability.
So what exactly is that aware client and what is the difference between non-cluster aware ?
Also, what is regular OSS cluster ?
Thank You..
"Cluster Aware" means a Redis client that supports the OSS Cluster API (https://redis.io/topics/cluster-spec). For example, the Ruby client https://github.com/redis/redis-rb#cluster-support supports it.
A non-aware client is a client that only supports connecting to Redis in single-instance mode (and perhaps Sentinel), such as the Python client https://github.com/andymccurdy/redis-py.
The Enterprise Cluster can be used by both types of clients regardless of how the database is deployed (i.e. clustered or not).
To clear some more of the confusion:
OSS Cluster - a mode of deployment and API (i.e. not single-instance)
Enterprise Cluster - a product

Is it a good way to run Kafka on Kubernetes?

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.

Redis Cluster configuration for CacheManager.NET

I have a basic question about Redis connection parameters from CacheManager.NET perspective. In case when we have Redis cluster with a master and 2 slaves, and with quorum of sentinel processes, should we provide the IP:PORT combinations pointing to the sentinel processes OR the actual Redis server processes.
As suggested in https://seanmcgary.com/posts/how-to-build-a-fault-tolerant-redis-cluster-with-sentinel, it is advisable to ask the sentinel process about the actual master before making the connection. And probably that goes in line with Jedis which provides JedisSentinelPool to do the initial lookup.
Essentially what we want is that the load balancing on reads (via CacheManager.NET) and the writes should go to the current master node of the cluster.
CacheManager relies on StackExchange.Redis for the Redis implementation. Therefor, whatever this client library supports, CacheManager does, too.
Unfortunately, sentinel support is not implemented, there are issues on github for years regarding that
That being said, I did some testing with a Multi Master/Slave + Sentinel setup. Added all the non-sentinel nodes as endpoints to the Multiplexer configuration and it kinda works because the Redis Client knows how to handle multiple master/slave instances.
In the process of switching to another master, the client might throw exceptions that it cannot write to a readonly slave and such. CacheManager might retry those calls and after a short amount of time, when the leader election is done, the call should go through.
But this is not 100% stable and I would not put that in production, as "official" support is still missing...
Alternative to running with sentinels, you could run Redis in Cluster mode which should just work, or behind a proxy which deals with all that master/slave stuff.
Twemproxy is one alternative.
I still have to add support for Twemproxy to CacheManager, as many features are simply not available, like Lua scripting or get a list of servers or flush commands...
This will come in 1.0.2
Hope that helps.

Is automatic failover built into Redis 2.8?

I am planning on adding Redis to our application as a session and cache store. I have been looking at how to make Redis highly available on an on-premise hosted solution.
The standard approach appears to be to set up Redis as a 3 node replica and use Sentinel for the monitoring and automatic failover.
Redis 2.8 introduces Redis cluster. Does that mean it brings in automatic failover etc and we no longer need to use Sentinel?
No, Cluster and Failover are different scenarios. Also Cluster is in 3.0, not 2.8.
The standard (and minimum) setup for HA is a master and one slave (aka "a pod"), with a separate set of three nodes which run Sentinel and monitor the pod.
This is to ensure failover of the server. However, either your client library has to support using Sentinel to discover master and reconnect on failure, you implement it in your code, or you set up a TCP load balancer and a sentinel monitoring daemon to update your load balancer configuration when a failover occurs at which point the client code doesn't know or care about sentinel.
Cluster isn't there to provide HA, it is there for server-side sharding of data. For Cluster you're looking at 6-7 nodes minimum (3 master, 3 slave, 1 spare) as well as Cluster support in the client and restrictions about commands and Lua script which need to access multiple keys.