Configuring kafka connect with multi brokers - kubernetes

Steps
I have used two kafka brokers and I have started zookeeper,kafka server and kafka connect services.
I have one source type kafka connector which can be used for getting data from Database.
If i start the connector[connector 1] by using the rest API, then it will hit any one kafka server [Server 1] using load balancer.After that server 1 will store and running the connector.But server 2 does not know the connector [connector 1] which is running in the server 1.
Expectation
So if the kafka server 1 is down, then the another kafka server 2 should be able to run the connector in the failed kafka server 1.
While starting the connector, kafka server should know how many connectors are in running, so that if any one broker failed to do the job then another server will be able to continue the job.
Reality
Another Kafka server 2 which is not doing the job as per the requirement.
is there any thing to make it by configuration setup with kafka?.
Kindly suggest me some ideas.
Kafka Server 1
Kafka Server 2

It appears that you have started all processes in single pods.
You should run Kafka, Zookeeper, and Connect all as separate services in different pods.
I suggest you refer the Confluent or Strimzi sites to find Kafka Kubernetes Helm Charts / Operators
But to answer the question - You could give one or more broker to connect-distributed.properties bootstrap.server value. Then each broker is connected to as part of the Kafka cluster, and will reconnect in the event that one broker is unavailable
"Kakfa servers" (brokers) do not run Connectors
If you want to run a cluster of connect workers, you also need to setup their rest.advertised.listener address so that they can communicate with each other.

Related

Snowflake Kafka connector doubts and questions

I am using 3 server cluster for the Kafka Configuration, with Snowflake connector REST API to push the data to Snowflake database: All are 3 different VMs running on AWS
1.In this, does we require 3 kafka individual server zookeeper-services needs to be up and running in cluster else only 1 is enough, as if it needs to be executed in all the 3 servers zookeeper services, does it require different port configurations like for ex:
1.a:zookeeper.connect=xx.xx.xx.xxx:2181, xx.xx.xx.xxx:2182, xx.xx.xx.xxx:2183 else it should be 2181 in all the servers.properties file
1.b:PLAINTEXT://localhost:9091 in server1, PLAINTEXT://localhost:9092 and PLAINTEXT://localhost:9093 (Even in this it should be localhost else IP Address) that needs to be given?
1.c:server.1=<zookeeper_1_IP>:2888:3888, server.1=<zookeeper_2_IP>:2888:3888, server.1=<zookeeper_3_IP>:2888:3888 (Over here on each server the 2888:3888 needs to be same right?)
1.d:Clientport=2181 needs to be the same across the services in all 3 VMs else it needs to be different?
1.e:Does the listeners = PLAINTEXT://your.host.name:9092 on each server should have separate port like
VM-Server1:9092, VM-Server2:9093, VM-Server3:9094. Else the master server-IP should be given in the worker-nodes that is Server2 and Server3 else the own server IP of that worker-node
What should be the configuration for connector in regards with REST-API for the configuration item "tasks.max":"1". As I am going with 3 server cluster for Kafka and would be starting the 3 distribute-connector on all the 3 machines
I am getting duplicates, if I am starting the services of distributed connector in the 2nd server, how these duplicate records can be avoided. But yes if its only 1 distributed-connector is running the services, then there are no duplicates. Please advice, as the lag gets increased if only 1 distributed-connector services is up and running.
Create /data/zookeeper/myid file and give value 1 for zookeeper1 , 2 for zookeeper2 and 3for zookeeper3. Is this necessary when you are in different VM?
The distributed-connector services once started executing for sometime and then it gets disconnected
Any other parameter for the 3 server cluster architecture and best practices which needs to be followed
Kafka and Zookeeper
You only need one Kafka broker and Zookeeper server, although having more would provide fault tolerance. You don't need to manually create anything in Zookeeper such as myid files.
The ports don't need to be the same, but it is obviously easier to draw a network diagram and automate the configuration if they are.
Regarding Kafka listeners, read this post. For Zookeeper, follow its documentation if you want to create a cluster.
Or use Amazon MSK / Confluent Cloud, etc. instead of EC2, and this is all done for you.
Kafka Connect
tasks.max can be as much as you want, but if you have a source connector, then multiple threads will probably cause duplicates, yes.

How to expand confluent cloud kafka cluster?

I have set up a confluent cloud multizone cluster and it got created with just one bootstrap server. There was no setting for choosing number of servers while creating the cluster. Even after creation, I can’t edit the number of bootstrap servers.
I want to know how to increase the number of servers in confluent cloud kafka cluster.
Under the hood, the Confluent Cloud cluster is already running multiple brokers. Depending on your cluster configuration (specifically, whether you're running Standard or Dedicated, and what region and cloud you're in), the cluster will have between six and several dozen brokers.
The way a Kafka client bootstrap server config works is that the client reaches out to the bootstrap server and requests a list of all brokers, and then uses those broker endpoints to actually produce/consume from Kafka (reference: https://jaceklaskowski.gitbooks.io/apache-kafka/content/kafka-properties-bootstrap-servers.html)
In Confluent Cloud, the provided bootstrap server is actually a load balancer in front of all of the brokers; when the client connects to the bootstrap server it'll receive the actual endpoints for all of the actual brokers, and then use that for subsequent connections.
So TL;DR, in your client, you only need to specify the one bootstrap server; under the hood, the Kafka client will connect to the (many) brokers running in Confluent Cloud, and it should all just work.
Source: I work at Confluent.

Can Kafka Connect consume data from a separate kerberized Kafka instance and then route to Splunk?

My pipeline is:
Kerberized Kafka --> Logstash (hosted on a different server) --> Splunk.
Can I replace the Logstash component with Kafka Connect?
Could you point me to a resource/guide where I can use kerberized Kafka as a source for my Kafka connect (which is hosted separately)?
From the documentation, what I understood is that if Kafka Connect is hosted on the same cluster as that of Kafka, that's quite possible. But I don't have that option right now, as our Kafka cluster is multi-tenant and hence not approved for additional processes on the cluster.
Kerberos keytabs aren't commonly machine/JVM specific, so yes, Kafka Connect should be able to be configured very similarly to Logstash since both are JVM processes using native Kafka protocol.
You shouldn't run Connect on the brokers anyway
If you can't add Kafka Connect to an existing Kafka cluster, you will have to spin up a separate Kafka Connect (Cluster or standalone).
I've written about it here: enter link description here

Kafka and Kafka Connect deployment environment

if I already have Kafka running on premises, is Kafka Connect just a configuration on top of my existing Kafka, or does Kafka Connect require it's own Server/Environment separate from that of my existing Kafka?
Kafka Connect is part of Apache Kafka, but it runs as a separate process, called a Kafka Connect Worker. Except in a sandbox environment, you would usually deploy it on a separate machine/node from your Kafka brokers.
This diagram shows conceptually how it runs, separate from your brokers:
You can run Kafka Connect on a single node, or as part of a cluster (for throughput and redundancy).
You can read more here about installation and configuration and architecture of Kafka Connect.
Kafka Connect is its own configuration on top of your bootstrap-server's configuration.
For Kafka Connect you can choose between a standalone server or distributed connect servers and you'll have to update the corresponding properties file to point to your currently running Kafka server(s).
Look under {kafka-root}/config and you'll see
You'll basically update connect-standalone or connect-distributed properties based on your need.

Kafka connect cluster setup or launching connect workers

I am going through kafka connect, and i am trying to get the concepts.
Let us say I have kafka cluster (nodes k1, k2 and k3) setup and it is running, now i want to run kafka connect workers in different nodes say c1 and c2 in distributed mode.
Few questions.
1) To run or launch kafka connect in distributed mode I need to use command ../bin/connect-distributed.sh, which is available in kakfa cluster nodes, so I need to launch kafka connect from any one of the kafka cluster nodes? or any node from where I launch kafka connect needs to have kafka binaries so that i will be able to use ../bin/connect-distributed.sh
2) I need to copy the my connector plugins to any kafka cluster node( or to all cluster nodes?) from where I do the step 1?
3) how does kafka copies these connector plugins to worker node before starting jvm process on the worker node? because the plugin is the one which has my task code and it needs to be copied to worker in order to start the process in worker.
4) Do i need to install anything in connect cluster nodes c1 and c2, like need to install java or any kafka connect related?
5) In some places it says use confluent platform but i would like to start it with apache kafka connect alone first.
can some one please through some light or even pointer to some resources would also help.
Thank you.
1) In order to have a highly available kafka-connect service you need to run at least two instances of connect-distributed.sh on two distinct machines that have the same group.id. You can find more details regarding the configuration of each worker here. For improved performance, Connect should be ran independently of the broker and Zookeeper machines.
2) Yes, you need to place all your connectors under plugin.path (normally under /usr/share/java/) on every machine that you are planning to run kafka-connect.
3) kafka-connect will load the connectors on startup. You don't need to handle this. Note that if your kafka-connect instance is running and a new connector is added, you need to restart the service.
4) You need to have Java installed on all your machines. For Confluent Platform particularly:
Java 1.7 and 1.8 are supported in this version of Confluent Platform
(Java 1.9 is currently not supported). You should run with the
Garbage-First (G1) garbage collector. For more information, see the
Supported Versions and Interoperability.
5) It depends. Confluent was founded by the original creators of Apache Kafka and it comes as a more complete distribution adding schema management, connectors and clients. It also comes with KSQL which is quite useful if you need to act on certain events. Confluent simply adds on top of the Apache Kafka distribution, it's not a modified version.
Answer given by Giorgos is correct. I ran few connectors and now I understand it better.
I am just trying to put it differently.
In Kafka connect there are two things involved one is Worker and second is connector.Below is on details about running distributed Kafka connect.
Kafka connect Worker is a Java process on which the connector/connect task will run. So first thing is we need to launch worker, to run/launch a worker we need java installed on that machine then we need Kafka connect related sh/bat files to launch worker and kafka libs which will be used by kafka connect worker, for this we will just simply copy/install Kafka in the worker machine, also we need to copy all the connector and connect-task related jars/dependencies in "plugin.path" as defined in the below worker properties file, now worker machine is ready, to start worker we need to invoke ./bin/connect-distributed.sh ./config/connect-distributed.properties, here connect-distributed.properties will have configuration for worker. The same thing has to be repeated in each machine where we need to run Kafka connect.
Now the worker java process is running in all machines, the woker config will have group.id property, the workers which have this same property value will be forming a group/cluster of workers.
Each worker process will expose rest endpoint (default http://localhost:8083/connectors), to launch/start a connector on the running workers, we need do http-post a connector config json, based on the given config the worker will start the connector and the number of tasks in the above group/cluster workers.
Example: Connect post,
curl -X POST -H "Content-Type: application/json" --data '{"name": "local-file-sink", "config": {"connector.class":"FileStreamSinkConnector", "tasks.max":"3", "file":"test.sink.txt", "topics":"connect-test" }}' http://localhost:8083/connectors