I am new to redis, still reading doc, hope you could help me here.
I need a 2-stage database solution:
At local devices, there is a database cluster. It has several primaries and several replicas. To my understanding each primary or replica normally has a portion of the whole data set. This is called data sharding.
At cloud, there is another database replica. This cloud replica backs up the whole data set.
I like to use free redis for this solution, not enterprise version.
Is this achievable? From what I read so far, it seems that there is no problem if the cloud replica is just like local replica to back up a portion of data set. So I want to know whether I can use the cloud database to back up the whole cluster.
Thanks!
Nothing prevents you from having a replica hosted in the cloud, but each Redis cluster node is either a master responsible of a set of key slots (shards) or a replica of a master; in a multi-master scenario there is no way to have a single replica covering different master nodes.
With the goal of having your entire cluster data replicated in the cloud, you should configure and host there one additional Redis replica per each master node. To avoid those new replicas to ever become masters themselves, you can set their cluster-replica-no-failover configuration property accordingly in their redis.conf files:
cluster-replica-no-failover yes
In all cases, please note that replication is not a backup solution and you may want to pair your setup with a proper Redis persistence mechanism.
If I understand your questions clearly, your master dataset(in shards) are located on premise and the replicas(slave) are hosted on cloud. There is nothing preventing you from backing up your slaves(open source redis) on the cloud. Redis doesn't care where the slaves are situated provided the master can reach them. Master-slave replication is available on redis enterprise with no such restriction. You might have a little problem implementing master-master replication on redis open source but that is outside the scope of this question
Currently I'm working on a distributed test execution and reporting system. I'm planning to use Redis PUB/SUB as a message queue and message distribution system.
I'm new to Redis, so I'm trying to read as many docs as I can and play around with it. One of the most important topics is high availability. As I said, I'm not an expert, but I'm aware of the possible options - using Sentinel, replication, clustering, etc.
What's not clear for me is how the Pub/Sub feature and the HA options are related each other. What's the best practice to build a reliable messaging system with Redis? By reliable I mean if my Redis message broker is down there should be some kind of a backup node (a slave?) that should be able to take over this role.
Is there a purely server-side solution? Or do I need to create a smart wrapper around the Redis client to handle this? Will a Sentinel-driven setup help me?
Doing pub sub in Redis with failover means thinking about additional factors in the client side. A key piece to understand is that subscriptions are per-connection. If you are subscribed to a channel on a node and it fails, you will need to handle reconnect and resubscribe. Because subscriptions are done at the connection level it is not something which can be replicated.
Regarding the details as to how it works and what you can expect to see, along with ways around it see a post I made earlier this year at https://objectrocket.com/blog/how-to/reliable-pubsub-and-blocking-commands-during-redis-failovers
You can lower the risk surface by subscribing to slaves and publishing to the master, but you would then need to have non-promotable slaves to subscribe to and still need to handle losing a slave - there is just as much chance to lose a given slave as there is a master.
IMO, PUB/SUB is not a good choice, may be disque (comes from antirez, author of the Redis) fits better:
Disque, an in-memory, distributed job queue
I understand redis sentinel is a way of configuring HA (high availability) among multiple redis instances. As I see, there is one redis instance actively serving the client requests at any given time. There are two additional servers are on standby (waiting for a failure to happen, so one of them can be in action again).
Is it waste of resources?
Is there a better way of using full use of the resources available?
Is Redis clustering an alternative to Redis sentinel?
I already looked up redis documentation for sentinel and clustering, can somebody having experience explain please.
UPDATE
OK. In my real deployment scenario I have two servers dedicated for redis. I have another server my Jboss server is running. The application running in Jboss is configured to connect to redis master server(M).
Failover scenario
Ideally, I think when Master cache server fails (either Redis process goes down or machine failure) the application in Jboss needs to connect to Slave cache server. How would I configure the redis servers to achieve this?
+--------+ +--------+
| Master |---------| Slave |
| | | |
+--------+ +--------+
Configuration: quorum = 1
First, lets talk sentinel.
Sentinel manages the failover, it doesn't configure Redis for HA. It is an important distinction. Second, the diagram you posted is actually a bad setup - you don't want to run Sentinel on the same node as the Redis nodes it is managing. When you lose that host you lose both.
As to "Is it waste of resources?" it depends on your use case. You don't need three Redis nodes in that setup, you only need two. Three increases your redundancy, but is not required. If you need the added redundancy then it isn't a waste of resources. If you don't need redundancy then you just run a single Redis instance and call it good - as running more would be "wasted".
Another reason for running two slaves would be to split reads. Again, if you need it then it wouldn't be a waste.
As to "Is there a better way of using full use of the resources available?" we can't answer that as it is far too dependent on your specific scenario and code. That said if the amount of data to store is "small" and the command rate is not exceedingly high, then remember you don't need to dedicate a host to Redis.
Now for "Is Redis clustering an alternative to Redis sentinel?".
It really depends entirely on your use case. Redis Cluster is not an HA solution - it is a multiple writer/larger-than-ram solution. If your goal is just HA then it likely won't be suitable for you. Redis Cluster comes with limitations, particularly around multi-key operations, so it isn't necessarily a straightforward "just use cluster" operation.
If you think having three hosts running Redis (and three running sentinel) is wasteful, you'll likely hold Cluster to be even more so as it does require more resources.
The questions you've asked are probably too broad and opinion-based to survive as written. If you have a specific case/problem you are working out please update with that so we can provide specific assistance and information.
Update for specifics:
For proper failover management in your scenario I would go with 3 sentinels, one running on your JBoss server. If you have 3 JBoss nodes then go with one on each. I'd have a Redis pod (master+slave) on separate nodes, and let sentinel manage the failover.
From there it is a matter of wiring up JBoss/Jedis to use Sentinel for it's information and connection management. As I don't use those a quick search turns up that Jedis has the support for it, you just need to configure it correctly. Some examples I found are at Looking for an example of Jedis with Sentinel and https://github.com/xetorthio/jedis/issues/725 which talk about JedisSentinelPool being the route for using a pool.
When Sentinel executes a failover the clients will be disconnected and Jedis will (should?) handle the reconnection by asking the Sentinels who the current master is.
This is not direct answer to your question, but think, it's helpful information for Redis newbies, like me. Also this question appears as the first link in google when searching the "Redis cluster vs sentinel".
Redis Sentinel is the name of the Redis high availability solution...
It has nothing to do with Redis Cluster and is intended to be used by
people that don't need Redis Cluster, but simply a way to perform
automatic fail over when a master instance is not functioning
correctly.
Taken from the Redis Sentinel design draft 1.3
It's not obviuos when you are new to Redis and implementing failover solution. Official documentations about sentinel and clustering doens't compare to each other, so it's hard to choose the right way without reading tons of documentations.
The recommendation, everywhere, is to start with an odd number of instances, not using two or a multiple of two. That was corrected, but lets correct some other points.
First, to say that Sentinel provides failover without HA is false. When you have failover, you have HA with the additional benefit of application state being replicated. The distinction is that you can have HA in a system without replication (it's HA but it's not fault tolerant).
Second, running a sentinel on the same machine as its target redis instance is not a "bad setup": if you lose your sentinel, or your redis instance, or the whole machine, the results are the same. That's probably why every example of such configurations shows both running on the same machine.
Additional info to above answers
Redis Cluster
One main purpose of the Redis cluster is to equally/uniformly distribute
your data load by sharding
Redis Cluster does not use consistent hashing, but a different form of sharding where every key is conceptually part of what is called as hash slot
There are 16384 hash slots in Redis Cluster, Every node in a Redis Cluster is responsible for a subset of the hash slots, so, for example, you may have a cluster with 3 nodes,
where:
Node A contains hash slots from 0 to 5500,
Node B contains hash slots from 5501 to 11000,
Node C contains hash slots from 11001 to 16383
This allows us to add and remove nodes in the cluster easily. For example, if we want to add a new node D, we need to move some hash slot from nodes A, B, C to D
Redis cluster supports the master-slave structure, you can create slaves A1,B1, C2 along with master A, B, C when creating a cluster, so when master B goes down slave B1 gets promoted as master
You don't need additional failover handling when using Redis Cluster and you should definitely not point Sentinel instances at any of the Cluster nodes.
So in practical terms, what do you get with Redis Cluster?
1.The ability to automatically split your dataset among multiple nodes.
2.The ability to continue operations when a subset of the nodes are experiencing failures or are unable to communicate with the rest of the cluster.
Redis Sentinel
Redis supports multiple slaves replicating data from a master node.
This provides a backup for data in master node.
Redis Sentinel is a system designed to manage master and slave. It runs as separate program. The minimum number of sentinels required in an ideal system is 3. They communicate among themselves and make sure that the Master is alive, if not alive they will promote one of the slaves as master, so later when the dead node spins up it will be acting as a slave for the new master
Quorum is configurable. Basically it is the number of sentinels that need to agree as the master is down. N/2 +1 should agree. N is the number of nodes in the Pod (note this setup is called a pod and is not a cluster)
So in practical terms, what do you get with Redis Sentinel?
It will make sure that Master is always available (if master goes down, the slave will be promoted as master)
Reference :
https://fnordig.de/2015/06/01/redis-sentinel-and-redis-cluster/
https://redis.io/topics/cluster-tutorial
This is my understanding after banging my head throughout the documentation.
Sentinel is a kind of hot standby solution where the slaves are kept replicated and ready to be promoted at any time. However, it won't support any multi-node writes. Slaves can be configured for read operations. It's NOT true that Sentinel won't provide HA, it has all the features of a typical active-passive cluster ( though that's not the right term to use here ).
Redis cluster is more or less a distributed solution, working on top of shards. Each chunk of data is being distributed among masters and slaves nodes. A minimum replication factor of 2 ensures that you have two active shards available across master and slaves.
If you know the sharding in Mongo or Elasticsearch, it will be easy to catch up.
Redis can operate in partitioned cluster (with many masters and slaves of those masters) or a single instance mode (single master with replica slaves).
The link here says:
When using Redis in single instance mode, in which a single Redis server manages the entire unpartitioned database, Redis Sentinel is used to manage its availability
It also says:
A Redis cluster, in which data is partitioned among multiple primary instances, manages availability by itself and requires no extra components.
So HA can be ensured in the 2 mentioned scenarios. Hope this clears the doubts. Redis cluster and sentinels are not alternative to each other. They are just used to ensure HA in different cases of partitioned or non-partitioned master.
Redis Sentinel performs the failover promoting replicas when they see a master is down. You typically want an odd number of sentinel nodes. For the example of one master and one replica, 3 sentinels should be used so there can be a consensus on the decision. Ideally the 3rd sentinel is on a 3rd server so the decision is not skewed (depending on failure). Sentinel takes care of changing the master/replica config settings on your nodes so that promotion and syncing occurs in the correct order and you don’t overwrite data by bringing on an old failed master that now contains older data.
Once you have your sentinel nodes set up to perform failovers, you need to ensure you are pointing to the correct instance. See an example of HAProxy configuration for this. HAProxy performs health checks and will point to the new master if a failure occurs.
Clustering will allow you to scale horizontally and can help handle high loads. It does take a bit of work to set up and configure up front.
There is an open source fork of Redis, “KeyDB” that has eliminated the need for sentinel nodes with an active-replica option. This allows the replica node to accept reads and writes. When a failover occurs HAProxy stops reads/writes with the failed node and just uses the remaining active node which is already sync’d. Timestamping enables the failed nodes to rejoin automatically and resync without losing data when they come back online. Setup is simple and for higher traffic you don’t need special upfront setup to direct reads to the replica node and read/writes to the master. See example of active replication here. KeyDB is also multi-threaded which for some applications might be an alternative to clustering, but really depends on what your needs are.
There is also an example of setting up clustering manually and with the create-cluster tool. These are the same steps if you are using Redis (replace 'keydb' with 'redis' in instruction)
I'm developing project with redis.My redis configuration is normal redis setup configuration.
I don't know how should I do redis configuration? Master-Slave? Cluster?
Do you have anything suggestion redis configuration for production?
Standard approach would be to have one master and at least one slave. Depending on your I/O requirements and number of ops/sec, you can always have multiple read-only slaves. Slaves can be read from but not written to. So you'll want to design your application to take advantage of doing round-robin requests to the slaves and writes only to the single master.
Depending on your data storage/backup requirement, you can set fsync for append-only mode to be every second. So while this means you can lose up to one second worth of data, it's really much less than that because your slaves serve as hot backups, and they will have the data within milliseconds.
You'll at least want to do a BGSAVE every hour to get a dump.rdp produced. You can then save this file live while the server is still running, and store it to some off-site backup facility.
But if you're just using Redis as a standard memcache replacement and don't care about data, then you can ignore all of this. Much of it will be changing in Redis Cluster in the 3.0 version.
It depends on what your Read/Writes requirements are. Could you give us more informations on that matter ?
I think 10,000 people use instant my application.I persist member login token on redis.It's important for me.If I don't write redis, member don't login on application.
Even a Redis single instance will be enough to process 10K users (start redis-bench to the throughput available), so just to be sure use a Master/Slave configuration with autopromotion of the slave if the master goes down.
Since you want persistence, use RDB (maybe along with AOF), see this topic on Redisio.
I'm interested in SignalR + Redis solution for implementing a server application that is scalable. And my concern is that Redis cluster is not production ready yet! So my question is:
Is Redis a bottleneck in SignalR + Redis when it comes to scaling out? If it is, is there any Linux-based solution that solves the problem?
On a single redis server you can easily handle up to 10K concurrent clients using pubsub. If you are still evaluating what to use, this should be more than you need at your current stage.
Redis cluster is supposed to be production ready by the end of the year or early 2014. You can actually download it and try it already. Lots of people are using it now and reporting the odd bug. The creator of redis is focused on making the cluster work and as of now it is very mature.
By using the proxy you could have up to 1000 nodes simultaneously, with over 10K clients on pubsub, so 10 million of concurrent users. The limit of the cluster is theoritecally of 16384 nodes, but a maximum of 1000 is recommended right now.
Unless you are of facebook scale, you can probably use redis for your case use (and even when you are twitter scale, given twitter uses redis intensively for storing all the timelines on redis)
I've been asked to add some references on a comment, so here you are the relevant links:
On the number of concurrent connections per redis process http://redis.io/topics/clients
On how twitter is using redis http://highscalability.com/blog/2013/7/8/the-architecture-twitter-uses-to-deal-with-150m-active-users.html
On cluster size/specs http://redis.io/topics/cluster-spec
Is Redis a bottleneck in SignalR + Redis when it comes to scaling out? If it is, is there any Linux-based solution that solves the problem?
I don't think so. Check the below article on how to scale out using Redis
http://www.asp.net/signalr/overview/performance-and-scaling/scaleout-with-redis