Zookeeper Experts.
The question that I am asking might be basic to you, but I am new to ZK, and I haven't mastered the tool yet so forgive me. With that in mind here is my question.
Suppose I have a ZK Cluster of 5 Servers, and I have a quorum of 3. Now this guarantees that the servers won't go into split-brain scenarios, if they are located into two physically separate DC or machines right.
However, what I want to know is if the Quorum is set to three it means that the Leader server, will need to wait until at least 2 server replicate the written data, total of 3 replicated data. But what if a client connects to the server that is not part of the Quorum any of the 2 servers, isn't that means it gets the old data ?
First, you cannot "set" the quorum. It is automatically calculated from the configuration, using N/2+1 (the majority) where N is the number of zookeeper server *.
A Zookeeper server that is not part of a Quorum become unavailable and cannot server data to clients so no risk of seeing old data.
Related
What I have zookeeper setup which is running on server1, server2 and server3 and similarly kafka also running in server1, server2 and server3.
Setup are running in kubernetes.
Problem statement:
In case one zookeeper setup get down entire setup will get down, because kafka is depended to zookeeper. am i right?
If Q1 correct - Is there any way to make setup like if one zookeeper server will get down then kafka should run as it is?
How to expose kafka port in kubernetes setup ?
what is the recommended way to persist data in kubernetes for production server ?
I fail to see how Zookeeper questions are related to k8s... But you definitely should set affinity rules such that Zookeeper and Kafka are not on the same physical servers or sharing same disks
If one Zookeeper out of three goes down, you'll end up with a split brain event in that no single Zookeeper knows which should be responsible for leadership. This effectively can crash or corrupt Kafka, yes.
To mitigate that risk, you can choose to run 5 Zookeepers, in which case you can lose up to 3 servers to reach the same state. The Definitive Guide book covers these concepts in the first few chapters
Regarding the other questions - NodePorts and PVCs, generally speaking.
Use one of the popular Kafka Operators on Github and you'll not need to think too hard about setting those properties
You still must manually perform Kafka admin tasks in any installation... You can use extra services like Cruise Control if you want to reduce that workload, though
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 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.
I am going to use kafka as messaging system. Still missing the following dots in my mind.
How many brokers can I have on one machine ?
Does it make sense to have more #replicas (partition replication) than #broker in kafka ?
Is it possible to add additional zookeeper server(on other machine) to scale without shutting down/restarting the current service ?
You could have more than one broker per machine but there is usually not any good reason to have more than one.
I can not think of a good reason to have more #replicas specified than #brokers.
Your Zookeeper servers should optimally be on separate machines and be and odd number of nodes. There is a tradeoff between write latency and resiliency here. 3 Zookeepers are common where write latency is very important. 5 or even 7 nodes can be used for more resiliency.