I am currently working on trying to use zookeeper in a two node cluster. I have my own cluster formation algorithm running on the nodes based on configuration. We only need Zookeeper's distributed DB functionality.
Is it possible to use Zookeeper in a two node cluster ? Do you know of any solutions where this has been done ?
Can we still retain the zookeepers DB functionality without forming a quorum ?
Note: Fault tolerance is not the main concern in this project. If one of the nodes go down we have enough code logic to run without the zookeeper service. We use the zookeeper to share data when both the nodes are alive.
Would greatly appreciate any help.
Zookeeper is a coordination system which is basically used to coordinate among nodes. When writes are occurred to such a distributed system, in ordered to coordinate and agree upon values which are being stored, all the writes are gone through master (aka leader). Reads can occur through any node. Zookeeper requires a master/leader to be elected per a quorum in order to serve write requests consistently. Zookeeper make use of the ZAB protocol as the consensus algorithm.
In order to elect a leader, a quorum should ideally have an odd number of nodes (Otherwise, a node will not be able to win majority and become the leader). In your case, with two nodes, zookeeper will not possibly be able to elect a leader for a long time since both nodes will be candidates and wait for the other node to vote for it. Even though they elect a leader, your ensemble will not work properly in network patitioning situations.
As I said, zookeeper is not a distributed storage. If you need to use it in a distributed manner (more than one node), it need to form a quorum.
As I see, what you need is a distributed database. Not a distributed coordination system.
Related
In a cluster scenario with data replication > 1, why is that we must always consume from a master/leader of a partition instead of being able to consume from a replica/follower node that contains a replica of this master node?
I understand the Kafka will always route the request to a master node(of that particular partition/topic) but doesn't this affect scalability (since all requests go to a single node)? Wouldnt it be better if we could read from any node containing the replica information and not necessarily the master?
Partition leader replicas, from which you can write/read data, are evenly distributed among available brokers. Anyway, you may also want to leverage the "fetch from closest replica" functionality, which is described in KIP-392, and available since Kafka 2.4.0.
I'm planning to build a Kafka Cluster using two servers, and host Zookeeper on these two servers as well.
The Question is, since Kafka requires Zookeeper to run, what is the best cluster build for zookeeper to implement Kafka Cluster on two servers?
for eg. I'm currently running two zookeepers on both servers and one Kafka on each server, and in the Kafka configuration they point to all Zookeepers.
Is there a better way to do this?
First of all, you don't have to setup Zookeper and Kafka in the same server. One of the roles of Zookeeper is electing controller. (one of the brokers which is responsible for maintaining the leader/follower relationship for all the partitions) For election; majority of Zookeper nodes must be alive. In your case even one Zookeeper instance is down, you cannot select controller. So there is no difference between having one Zookeper or two. That's why it is recommended to have at least 3 nodes in Zookeeper cluster. By this way you can handle failure of one Zookeeper node.
An addition to this, it is highly recommended to have at least three brokers in your Kafka cluster to maintain both consistency and high availability. (link1, link2)
UPDATE:
As long as you are limited to only two servers, then you can consider sacrificing from high availability by set up your broker by setting min.insync.replicas=2 and having topics with replication.factor=2. If HA is more important than data loss, then you can use min.insync.replicas=1 (default) broker config with again topic replication.factor=2. In this circumstance, your options are these IMHO. (Having one or two Zookeepers is not important as I mentioned above)
I am often faced with the same problem as you do #frisky5 where i would like to achieve a "suboptimal" HA system using only 2 nodes, and thus workarounds are always needed with cloud-native frameworks that rely on the assumption that clusters will have lot of nodes available.
That ain't always the case in real life, is it ;) ?
That being said, i see you essentially having 2 options:
Externalize zookeeper configuration on a replicated storage system using 2 nodes (e.g. DRBD)
Replicate Kafka data volumes entirely on the second nodes and use 2 one-node Kafka clusters that you switch on and off depending on who is the current master node.
I would go for the first option. In that case you would have 2 Kafka servers and one zookeeper server whose ip needs to be static (virtual ip). When the zookeeper node goes down, it is restarted one the second node with same VIP, but it needs to access the synchronized data folder.
I am not too familiar with zookeepers internals and i can't tell you whether it will go in conflict when starting up on a data store who "wasn't its own" but i would guess it makes sense for you to test it using a simple rsync setup.
Another way to achieve consensus if you are using a k3s based kubernetes cluster would be to rely on internal k8s distributed consensus mechanics to "tell Kafka" which node is the leader. This works for the postgresoperator by chruncydata because Patroni is cool ( https://patroni.readthedocs.io/en/latest/kubernetes.html ) 😎 but i am not sure if Kafka/zookeeper are that flexible and can communicate with a rest API to set their locks ...
Once you have achieved this intermediate step, then you can use a PostgreSQL db as external source of truth for k3s and then it is as simple as syncing the postgres data folder between the machines (easily done with rsync). The beauty of this approach is that it is way more generic and could be used for other systems too.
Let me know what do you think about these two approaches and whether you manage to setup a test environment. If you do on GitHub i can help you out with implementation
I have a two node redhat system with an identical set of services on each. I am looking for a way to determine which service is "in charge" and which is a "running backup". So for example; service-A exists and is running on both nodes but only one should be processing data while the other sleeps until the first crashes. Same for other services in the set.
Zookeeper's leader election capability looked like it would suffice; the whole ephemeral and sequential znode approach looked good on paper. I imagined that I would also need a zookeeper service running on each node for redundancy in the face of node failure, for example.
But the documentation points out issues with multiple zookeeper's requiring at least 3 instances in order to guarantee a quorum to elect the lead zookeeper among all other zookeepers. As I only have two nodes this looks like a deal-breaker.
So before I drop the zookeeper approach, I thought I ask if there were some configuration option to zookeeper to allow a two node system to work. Otherwise I'm off to find the next best fit for my problem.
You can run Zookeeper with just two instances. However, it gives you no benefit of fault tolerance because the quorum is till 2 in that case. Any one of them failing will result in Zookeeper ensemble rejecting client requests. That's why the default configuration for an ensemble is 3 Zookeeper instances because having 2 instances is no better than having 1 so why go through the trouble of creating 2? It actually creates more points of failures because when either instance dies, your Zookeeper ensemble halts and having either one of two to fail is more likely to have just one to fail.
I'm looking to start using Kafka for a system and I'm trying to cover all use cases.
Normally it would be run as a cluster of brokers running on virtual servers (replication factor 3-5). but some customers though don't care about resilience and a broker failure needing a manual reboot of the whole system is fine with them, they just care about hardware costs.
So my question is, are there any issues with using Kafka as a single broker system for small installations with low throughput?
Cheers
It's absolutely OK to use a single Kafka broker. Note, however, that with a single broker you won't have a highly available service meaning that when the broker fails you will have a downtime.
Your replication-factor will be limited to 1 and therefore all of the partitions of a topic will be stored on the same node.
For a proof-of-concept or non-critical dev work, a single node cluster works just fine. However having a cluster has multiple benefits. It's okay to go with a single node cluster if the following are not important/relevant for you.
scalability [spreads load across multiple brokers to maintain certain throughput]
fail-over [guards against data loss in case one/more node(s) go down]
availability [system remains reachable and functioning even if one/more node(s) go down]
I have a simple Kafka cluster of 3 brokers and 3 zk nodes.
If I wipe out 2/3 zk nodes and bring them back (even new "clean" ones), everything recovers as zk re-syncs.
If I wipe out all 3 zk nodes and restart them "clean" (think docker containers or AWS auto-scaling group instances), the brokers are confused. All of the data structures in zk (basic paths, brokers, topics, etc.) are gone, since I have a blank zk.
How can I recover from this scenario? I am (potentially) willing to live with lost topics (since we automate topic creation), but the brokers (unlike with startup) do not "know" that zk is blank and so do not reinitialize (set up structures, register brokers, etc.). Conversely, I could back up zk and restore it, as long as I know what to backup/restore.
The key element is fully automated, though. In cloud-native, I cannot rely on a human doing the restore or checking.
I'm not sure that managing Zookeeper nodes (or Kafka brokers for that matter) with autoscaling is such a good idea.
For one Zookeeper maintains the topic information (and if you are not using the latest Kafka builds or are sill using the old consumer API it also maintains the consumer offsets).
In addition to that topic partitions are statically assigned to brokers, so if you bring down the current Kafka brokers and spawn new nodes you have to be very careful and start brokers with the same broker.id and data otherwise Kafka might get confused.
Third regarding Zookeeper you have to be careful not to create a cluster of a pair number of nodes otherwise the consensus algorithm will not be able to elect a leader due to missing majority in the voting phase.
Having said all that I think that doing a backup and restore of one of the Zookeeper nodes should work. It would be even easier if you set up things so that at least one of the nodes cannot be turned off (or alternative you use a persistent storage for that one).
This way you ensure that one of the Zookeeper nodes will always have the latest data and it will take care of replicating it to the other nodes.