Debezium deployment with the new KafkaConnector feature (2023)

Our Kafka Connect story is not as "Kubernetes native" as it could have been for a long time. we had aKafkaConnectorNameResource for configuring Kafka Connectgroupbut still needed to use Kafka Connect REST API to create aconnectorin him. While that wasn't particularly difficult with something likereis, stood out because everything else could be done withkubectland that meant that connectors didn't fit our native Kubernetes vision. With the help of a community contribution, Strimzi now supports aKafka Connectorcustom feature and the rest of this blog post will explain how to use itDebéziumas an example. As if that wasn't enough, there are some amazing ASCII graphics to explain how it all fits together. Read on to learn more about this new Kubernetes-native way to manage connectors.

If you've never heard of Debezium, it's an open source project that you can applychange data collection(CDC) in your applications with Kafka.

But what is CDC? You probably have multiple databases in your organization; Silos full of business-critical data. While you can query these databases at any time, the essence of your business revolves around how this data changes. These modifications are triggered and triggered by real business events (eg a customer phone call or a successful payment or whatever). To reflect this, modern application architectures are often event-driven. And so after askingreal conditionof some tables is not enough; What these architectures need is a flow ofEvents that represent changesto these tables. That's CDC: capturing changes to state data as event data.

In particular, Debezium works with several popular DBMSs (MySQL, MongoDB, PostgreSQL, Oracle, SQL Server and Cassandra) and runs as a source connector within a Kafka Connect cluster. How Debezium works on the database side depends on which database you are using. For example, for MySQL it reads the commit log to find out what transactions are taking place, but for MongoDB it hooks into the native replication engine. In both cases, changes are rendered as JSON events by default (other serializations are also possible), which are sent to Kafka.

So, it goes without saying that Debezium provides a way to retrieve events from database applications (which may not expose event-based APIs) and make them available to Kafka applications.

So this is Debeziumesit is what it istut. Its function in this blog post is simply to be an example connector to use with theKafka Connectorthis is new in Strimzi 0.16.

Let's start with the instructions...

Let's follow in the footsteps ofDebezium-Tutorialto start a demo MySQL server.

First, we enable the database server in a Docker container:

Docker execution-AND --rm --NameMySQL- book page3306:3306\ -mi MYSQL_ROOT_PASSWORD=debts-mi MYSQL_USER=mysqluser\ -mi MYSQL_PASSWORT=mysqlpw debezium/ejemplo-mysql:1.0

After seeing the following, we know the server is ready:

...2020-01-24T12:20:18.183194Z 0[note] mysqld: listforConnections.Version:'5.7.29-log'Plug:'/var/ejecutar/mysqld/mysqld.calcetin'Porta: 3306 MySQL-Community-Server(GPL)

Then, in another terminal, we can run the command line client:

Docker execution-AND --rm --Namemysqlterm--ShortcutMySQL--rmmysql:5.7sh\ -C 'exec mysql -h"$MYSQL_PORT_3306_TCP_ADDR" \ -P"$MYSQL_PORT_3306_TCP_PORT" \ -uroot -p"$MYSQL_ENV_MYSQL_ROOT_PASSWORD"'

insideMySQL>we can go to the "Inventory" database and see the tables it contains:

mysql> use inventory;mysql> show tables;

(Video) Data Streaming for Microservices using Debezium (Gunnar Morling)

The output will look like this:

+---------------------+| tables_in_inventory |+-----------------------+| addresses || customers || Jewel || Commands || Products || products_in_hand |+----------------------------------------------- ----+ 6 linesEmlower (0,01 Sek)

Don't worry, this isn't great ASCII art.

You can take a look at this demo database if you like, but when you're done, leave this MySQL client running in its own terminal window for future reference.

Now we can follow some of themStrimzi Quick Start Guideto create a Kafka cluster running insideMinikube.

Start minikube first:

start minikube--Store=4096

With the command running, you can create a namespace for the resources we are going to create:

kubectl creates a Kafka namespace

Then install the cluster operator and associated features:

reis-EUhttps://github.com/strimzi/strimzi-kafka-operator/releases/download/0.16.1/strimzi-cluster-operator-0.16.1.yaml\|sed 's/namespace: .*/namespace: kafka/' \| apply kubectl-F--nortekafka

And launch a Kafka cluster and wait for it to terminate:

kubectl-nortekafka\to use-Fhttps://raw.githubusercontent.com/strimzi/strimzi-kafka-operator/0.16.1/examples/kafka/kafka-persistent-single.yaml\ &&kubectlhopekafka/mi-Cluster--for=Illness=List--The time is over=300er-nortekafka

Depending on your connection speed, this may take a while.

What we have so far looks like this

" minikube, namespace: kafka ──────ela argumenta ──────────────────────┘

Don't worry, ASCII art is much better than that!

What's missing from this image is Kafka Connect on the Minikube box.

The next step isCreate a Strimzi Kafka Connect imagewhich contains the Debezium MySQL connector and its dependencies.

First download and extract the Debezium MySQL connector file

curl https://repo1.maven.org/maven2/io/debezium/debezium-connector-mysql/1.0.0.Final/debezium-connector-mysql-1.0.0.Final-plugin.tar.gz\|Teerwxya

Prepare a .....DockerfileThis will add these connector files to the Strimzi Kafka Connect image

gato <<weekend>DockerfileFROM strimzi/kafka:0.16.1-kafka-2.4.0Usuario root:rootRUN mkdir -p /opt/kafka/plugins/debeziumCOPY ./debezium-connector-mysql/ /opt/kafka/plugins/debezium/USER 1001weekend

Then build the image from it.Dockerfileand push it to Dockerhub.

# You can use your own Dockerhub organizationExportDOCKER_ORG=build tjbentleydocker. -T p.sDOCKER_ORG}/conectar-debeziumdocker pushp.sDOCKER_ORG}/conectar-debezium

To make this a bit more realistic, let's use Kafka.config.providersMechanism to avoid having to pass secret information through the Kafka Connect REST interface (which uses unencrypted HTTP). We will use a KubernetesSecretcalledmy-sql-credentialsto store database credentials. This is provided as a secret volume in plug-in modules. We can then configure the connector with the path to this file.

Let's create the secret:

gato <<weekend> debezium-mysql-credentials.propertiesmysql_username: debeziummysql_password: dbzweekendkubectl-norteKafka create my-sql generic secret credentials\ --From file=debezium-mysql-credentials.propertiesrmdebezium-mysql-credentials.properties

Now we can create aKafkaConnectorNameCluster no Kubernetes:

gato <<weekend| kubectl -n kafka apply -f -apiVersion: kafka.strimzi.io/v1beta1kind: KafkaConnectmetadata: name: my-connect-cluster annotations: # use-connector-resources configure this KafkaConnect # to use KafkaConnector resources to avoid # having to call the connect REST API directly strimzi.io/use-connector-resources: "true" specification: image:p.sDOCKER_ORG}/connect-debezium Replikate: 1 bootstrapServers: my-cluster-kafka-bootstrap:9093 tls: trustCertificates: - secretName: my-cluster-cluster-ca-cert certificado: ca.crt config: config.storage.replication.factor: 1 offset.storage.replication.factor: 1 status.storage.replication.factor: 1 config.providers: Archiv config.providers.file.class: org.apache.kafka.common.config.provider.FileConfigProvider externalConfiguration: volumes: - nombre : conector-config secreto: nombresecreto: mis-credenciales-sqlweekend

A few things are worth noting about the above resource:

(Video) Streaming Database Changes with Debezium by Gunnar Morling

insideMetadata.AnnotationsANDstrimzi.io/use-connector-resources: „true“The annotation tells the cluster operator thatKafka ConnectorResources are used to configure connectors within this Kafka Connect cluster.
ANDimage.spez.is the image we used to createStauer.
insideAttitudeWe used a replication factor of 1 because we created a Kafka cluster with a single agent.
insideexternal configurationWe refer to the secret we have just created.

The last piece is to create theKafka ConnectorFeature configured to connect to our "inventory" database in MySQL.

This is whatKafka ConnectorThe resource looks like this:

gato <<weekend| kubectl -n kafka apply -f -apiVersion: "kafka.strimzi.io/v1alpha1" Tipo: "KafkaConnector" Metadados: Nome: "inventory-connector" Tags: strimzi.io/cluster: my-connect-clusterspec: class: io .debezium.connector.mysql.MySqlConnector taskMax: 1 config: database.hostname: 192.168.99.1 database.port: "3306" database.user: "p.sfile:/opt/kafka/external-configuration/connector-config/debezium-mysql-credentials.properties:mysql_username}" Database.Password: "p.sfile:/opt/kafka/external-configuration/connector-config/debezium-mysql-credentials.properties:mysql_password}" database.server.id: "184054" database.server.name: "dbserver1" database.whitelist: "inventario" database.history.kafka.bootstrap.servers: "my-cluster-kafka-bootstrap:9092" database.history .kafka.topic: „esquema-cambios.inventario“ include.schema.changes: „verdadero“weekend

Emmetadata.tags,strimzi.io/clustername thatKafkaConnectorNameCluster in which this connector will be created.

ANDspecification className the connector Debezium MySQL andmaxtaskspezIt should be 1 because that's all this connector uses.

ANDspecification.configThe object contains the remainder of the connector's configuration.Debezium Documentationexplains the available properties, but some are particularly noteworthy:

I wearDatabase.Hostname: 192.168.99.1I use there as the IP address for the MySQL connectionMinikubewith the virtualbox VM driver If you use another VM driver withMinikubeYou may need a different IP address.
ANDDatabase.port: "3306"works because of-p 3306:3306Argument we use when we start the MySQL server.
AND${file:...}used for theDatabase.UserjDatabase. Passwordis a placeholder that will be replaced by the referenced property of the file specified in the secret we created.
ANDdatabase.whitelist: "inventar"Basically, Debezium is telling it to just watchInventData base.
ANDdatabase.history.kafka.topic: „schema-changes.inventory“Debezium is configured to useschema changes. inventoryTheme for saving database schema history.

A little while after creating this connector you can take a look at itIllness, to usekubectl -n kafka get kctr Inventory Connector -o yaml:

#...Illness: Conditions: - last transition period: "2020-01-24T14:28:32.406Z" Illness: "TRUE" Type: List connector status: connector: Illness: RUN worker_id: 172.17.0.9:8083 Name: stock connector Tasks: - I WENT: 0 Illness: RUN worker_id: 172.17.0.9:8083 Type: source observed generation: 3

This tells us that the connector is working within theKafkaConnectorNameCluster we created in the last step.

In summary, we now have the complete picture with the connector talking to MySQL:

"Minikube, name room: kafka │ │ │ │ │ └ └ └ │ │ ┃│ ┃│ ┃│ ┃│ ┃│ ┃│ ┃│ ┃│ ┃│ ┃│ ┃│ ┃│ ┃│ ┃│ ┃│ ┃│ └━━ └━━ └━━ └━━ └━━ └━━ ━ - ━ - ━ ─ Thivers ───┘

Okay, I admit it: I lied that the ASCII art is great.

If you list the topics, for example withkubectl -n kafka exec my-cluster-kafka-0 -c kafka -i -t -- bin/kafka-topics.sh --bootstrap-server localhost:9092 --listYou must see this:

__consumer_offsetsconnect-cluster-configsconnect-cluster-offsetsconnect-cluster-statusdbserver1dbserver1.inventory.addressesdbserver1.inventory.customersdbserver1.inventory.geomdbserver1.inventory.ordersdbserver1.inventory.productsdbserver1.inventory.products_on_handschema-changes.inventory

ANDconnect-cluster-*are the usual Kafka Connect internal threads. Debezium made a theme for the server itself (Dice Bank Server1) and one for each table within theInventData base.

Let's start by consuming one of these change themes:

kubectl-nortekafkaexecutivemi-cluster-kafka-0-Ckafka-EU -T -- \bin/kafka-console-consumer.sh\ --bootstrap-servidorLocal server: 9092\ -- hedbserver1.inventory.clients

(Video) Bring Data from Source using Debezium with CDC into Kafka&S3Sink &Build Hudi Datalake | Hands on lab

This blocks waiting for logs/messages. To generate these messages, we need to make some changes to the database. Back in the terminal window, which we have left open while the MySQL command line client is running, we can make some changes to the data. Let's look at existing customers first:

mysql> SELECT * FROM customers;+------+------------+-----------+---------- -------------+| Identification | name | Last name | Email |+------+------------+-----------+------------- -- -------+| 1001 | Sally | Thomas | sally.thomas@acme.com || 1002 | George | Bailey | gbailey@foobar.com || 1003 | Edward | Wanderer | ed@walker.com || 1004 | Ana | Kretchmar | annek@noanswer.org |+------+------------+------------------+---- ------- ----+4 lines in total (0.00 sec)

now let's change thatFirst namefrom the last customer:

mysql> ATUALIZAR clientes SET first_name='Anne Marie' WHERE id=1004;

Changing the terminal window again, we should be able to see this rename event on the filedbserver1.inventory.clientsAND:

{"schema":{"type":"structure","fields":[{"type":"structure","fields":[{"type":"int32","optional":false,"field ":"id"},{"type":"string","optional":false,"field":"name"},{"type":"string","optional":false,"field": "lastname"},{"type":"string","optional":false,"field":"email"}],"optional":true,"firstname":"dbserver1.inventory.customers.Value" , "field":"before"},{"type":"struct","fields":[{"type":"int32","optional":false,"field":"id"},{" type ":"string","optional":false,"field":"firstname"},{"type":"string","optional":false,"field":"lastname"},{"type": "string","optional":false,"field":"email"}],"optional":true,"name":"dbserver1.inventory.customers.Value","field":"after"} ,{ "type":"struct","fields":[{"type":"string","optional":false,"field":"version"},{"type":"string","optional ": false,"field":"connector"},{"type":"string","optional":false,"field":"name"},{"type":"int64","optional": false, "field":"ts_ms"},{"type":"string","optional":true,"n ombre":"io.debezium.data.Enum","version":1,"pa rams":{"allow d":"true,last,false"},"default":"false","field": "snapshot"},{"type":"string","optional":false, "field":"db "},{"type":"string","optional":true,"field":"table "},{"type":"int64","optional":false,"field ":"server_id"} ,{"type":"string","optional":true,"field":"gtid"} ,{"type":"string","optional":false,"field": "file"},{ "type":"int64","optional":false,"field":"pos"},{ "type":"int32","optional":false,"field":"row "},{"type ":"int64","optional":true,"field":"thread"},{"type ":"string","optional":true,"field":"query"} ],"optional":false,"name":"io.debezium.connector.mysql.Source","field":"source "},{"type":"string","optional":false,"field ":"op"} ,{"type":"int64","optional":true,"field":"ts_ms"} ],"optional":false,"name":"dbserver1.inventory.customers.About "},"payload" :{"before":{"id":1004,"first_name":"Anne","last_name " :"Kretchmar","email":"annek@noanswer.org"},"depois ":{"id" :10 04,"first_name":"Anne Mary","last_name":"Kretchmar","email":"annek@noanswer.org"},"source":{"version ":"0.10.0.Final", " conector" :"mysql","name":"dbserver1","ts_ms":1574090237000,"snapshot":"false","db":"inventory","table ":"customers","server_id":223344 ," gtid":null,"file":"mysql-bin.000003","pos":4311,"row":0,"thread":3,"consulta ":null},"op":"u ", "ts_ms":1574090237089}}

That's a lot of JSON, but if we reformat it (e.g. with copy, paste andjq) We see:

{ "the plan": { "Type": "Structure", "Kampf": [ { "Type": "Structure", "Kampf": [ { "Type": "int32", "Optional": INCORRECT, "campo": "I WENT" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "First name" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "last name last name" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "E-mail" } ], "Optional": TRUE, "Name": "dbserver1.inventory.customers.value", "campo": "Before" }, { "Type": "Structure", "Kampf": [ { "Type": "int32", "Optional": INCORRECT, "campo": "I WENT" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "First name" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "last name last name" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "E-mail" } ], "Optional": TRUE, "Name": "dbserver1.inventory.customers.value", "campo": "after" }, { "Type": "Structure", "Kampf": [ { "Type": "Chain", "Optional": INCORRECT, "campo": "Execution" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "connector" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "Name" }, { "Type": "int64", "Optional": INCORRECT, "campo": "ts_ms" }, { "Type": "Chain", "Optional": TRUE, "Name": "io.debezium.data.Enum", "Execution": 1, "Parameter": { "permitted": "true, last, false" }, "Standard": "INCORRECT", "campo": "Snapshot" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "bd" }, { "Type": "Chain", "Optional": TRUE, "campo": "mesa" }, { "Type": "int64", "Optional": INCORRECT, "campo": "server_id" }, { "Type": "Chain", "Optional": TRUE, "campo": "E" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "File" }, { "Type": "int64", "Optional": INCORRECT, "campo": "pos" }, { "Type": "int32", "Optional": INCORRECT, "campo": "fila" }, { "Type": "int64", "Optional": TRUE, "campo": "hilo" }, { "Type": "Chain", "Optional": TRUE, "campo": "Advice" } ], "Optional": INCORRECT, "Name": "io.debezium.connector.mysql.Quelle", "campo": "source" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "op" }, { "Type": "int64", "Optional": TRUE, "campo": "ts_ms" } ], "Optional": INCORRECT, "Name": "dbserver1.inventory.clients.About" }, "Useful load": { "Before": { "I WENT": 1004, "First name": "Ana", "last name last name": "Kretchmar", "E-mail": "annek@noanswer.org" }, "after": { "I WENT": 1004, "First name": "Ana Maria", "last name last name": "Kretchmar", "E-mail": "annek@noanswer.org" }, "source": { "Execution": "1.0.0.Final", "connector": "mysql", "Name": "serverbd1", "ts_ms": 1574090237000, "Snapshot": "INCORRECT", "bd": "Invent", "mesa": "Customers", "server_id": 223344, "E": Null, "File": "mysql-bin.000003", "pos": 4311, "fila": 0, "hilo": 3, "Advice": Null }, "op": "Of", "ts_ms": 1574090237089 }}

ANDthe planThe object describes the actual event payload schema.

What is most interesting for this post is theuseful loadin itself. Working backwards, we have:

ts_msis the timestamp of when the change occurred
optells us that this was atuUpdate (an insert would beCand an exclusion would beD)
ANDsourcewhich tells us exactly which table was modified in which database on which server.
Beforejafterthey are self-explanatory and describe the line before and after the upgrade.

Of course, you can experiment with inserting and deleting rows in different tables (remember there is a theme for each table).

But so what?Dice Bank Server1what I lose? If we look at the news there (withkubectl -n kafka exec my-cluster-kafka-0 -c kafka -i -t --bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 --tema dbserver1 --desde-el-principio), we can see the records representing the DDL that was used (when the Docker image was created) to create the database. For example:

{ "the plan": { "Type": "Structure", "Kampf": [ { "Type": "Structure", "Kampf": [ { "Type": "Chain", "Optional": INCORRECT, "campo": "Execution" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "connector" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "Name" }, { "Type": "int64", "Optional": INCORRECT, "campo": "ts_ms" }, { "Type": "Chain", "Optional": TRUE, "Name": "io.debezium.data.Enum", "Execution": 1, "Parameter": { "permitted": "true, last, false" }, "Standard": "INCORRECT", "campo": "Snapshot" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "bd" }, { "Type": "Chain", "Optional": TRUE, "campo": "mesa" }, { "Type": "int64", "Optional": INCORRECT, "campo": "server_id" }, { "Type": "Chain", "Optional": TRUE, "campo": "E" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "File" }, { "Type": "int64", "Optional": INCORRECT, "campo": "pos" }, { "Type": "int32", "Optional": INCORRECT, "campo": "fila" }, { "Type": "int64", "Optional": TRUE, "campo": "hilo" }, { "Type": "Chain", "Optional": TRUE, "campo": "Advice" } ], "Optional": INCORRECT, "Name": "io.debezium.connector.mysql.Quelle", "campo": "source" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "database name" }, { "Type": "Chain", "Optional": INCORRECT, "campo": "ddl" } ], "Optional": INCORRECT, "Name": "io.debezium.conector.mysql.SchemaChangeValue" }, "Useful load": { "source": { "Execution": "1.0.0.Final", "connector": "mysql", "Name": "serverbd1", "ts_ms": 0, "Snapshot": "TRUE", "bd": "Invent", "mesa": "products_in_hand", "server_id": 0, "E": Null, "File": "mysql-bin.000003", "pos": 2324, "fila": 0, "hilo": Null, "Advice": Null }, "database name": "Invent", "ddl": "CRIA TABELA `products_in_hand` (\norte`product_id` int(11) NEIN NULO,\norte`amount` int(11) NOT NULL,\norteCLAVE PRINCIPAL (`product_id`),\norteRESTRICTION `products_on_hand_ibfk_1` FOREIGN KEY (`product_id`) REFERENCES `products` (`id`)\norte) ENGINE = DEFAULT CHARACTER SET InnoDB = latin1" }}

again we have athe planjuseful load. this time theuseful loadhat:

source, as in the old days,
database name, which tells us which database this record is for
ANDddlString tells us howproducts_on_handtable was created.

In this post, we learned that Strimzi now supports aKafka Connectorcustom resource that you can use to define connectors. We demonstrate this generic functionality using the Debezium connector as an example. When creating aKafka ConnectorFeature linked to ourKafkaConnectorNameclusters through thestrimzi.io/clusterday, we could observe changes in a MySQL database as records in a Kafka thread. And finally, we are left with a sense of disappointment at the broken promise of amazing ASCII art.

(Video) Kafka cdc implementation all starting barrier|| debezium || sink connector || source connector

FAQs

What is Debezium connector for Kafka Connect? ›

Debezium is a distributed platform that converts information from your existing databases into event streams, enabling applications to detect, and immediately respond to row-level changes in the databases. Debezium is built on top of Apache Kafka and provides a set of Kafka Connect compatible connectors.

Discover More Details ›

What is the difference between Kafka Connect and Debezium? ›

Debezium platform has a vast set of CDC connectors, while Kafka Connect comprises various JDBC connectors to interact with external or downstream applications. However, Debeziums CDC connectors can only be used as a source connector that captures real-time event change records from external database systems.

See Details ›

Can we use Debezium without Kafka? ›

Yet an alternative way for using the Debezium connectors is the embedded engine. In this case, Debezium will not be run via Kafka Connect, but as a library embedded into your custom Java applications.

Learn More Now ›

Why would you use Kafka connect? ›

Kafka Connect is a tool for scalably and reliably streaming data between Apache Kafka® and other data systems. It makes it simple to quickly define connectors that move large data sets in and out of Kafka.

Keep Reading ›

Why do we use Debezium? ›

The primary use of Debezium is to enable applications to respond almost immediately whenever data in databases change. Applications can do anything with the insert, update, and delete events. They might use the events to know when to remove entries from a cache. They might update search indexes with the data.

View Details ›

How Debezium works? ›

Debezium continuously monitors your databases and lets any of your applications stream every row-level change in the same order they were committed to the database. Use the event streams to purge a cache, update search indexes, generate derived views and data, keep other data sources in sync, and much more.

Explore More ›

When should I use Kafka connector? ›

Kafka Connectors are ready-to-use components, which can help us to import data from external systems into Kafka topics and export data from Kafka topics into external systems. We can use existing connector implementations for common data sources and sinks or implement our own connectors.

Tell Me More ›

What is real-time change replication with Kafka and Debezium? ›

Real-time change replication with Kafka and Debezium

Debezium is a CDC (Change Data Capture) tool built on top of Kafka Connect that can stream changes in real-time from MySQL, PostgreSQL, MongoDB, Oracle, and Microsoft SQL Server into Kafka, using Kafka Connect.

How do I manually deploy in Kubernetes? ›

Objectives

Package a sample web application into a Docker image.
Upload the Docker image to Artifact Registry.
Create a GKE cluster.
Deploy the sample app to the cluster.
Manage autoscaling for the deployment.
Expose the sample app to the internet.
Deploy a new version of the sample app.

Read The Full Story ›

What is alternative to Debezium? ›

Top Alternatives to Debezium

Kafka. Kafka is a distributed, partitioned, replicated commit log service. ...
Logstash. Logstash is a tool for managing events and logs. ...
Slick. It is a modern database query and access library for Scala. ...
DataGrip. ...
Spring Data. ...
Microsoft SQL Server Management Studio. ...
DBeaver. ...
dbt.

Keep Reading ›

Does Debezium affect database performance? ›

Debezium is a Database Change-Data-Capture (aka CDC) tool that is able to decode open source and proprietary database logs, normalize them to a standard payload format and push them into a series of Kafka topics.

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Is Debezium server high availability? ›

Debezium relies on the Kafka Connect framework to provide high availability but it does not provide something similar to a hot standby instance. It takes time for an existing connector to shut down and a new instance to come up - which might be acceptable for a few use-cases but unacceptable in others.

Learn More ›

What is the difference between Kafka and Kafka Connect? ›

Apache Kafka is a distributed streaming platform and kafka Connect is framework for connecting kafka with external systems like databases, key-value stores, search indexes, and file systems, using so-called Connectors.

Find Out More ›

Is Kafka Connect push or pull? ›

With Kafka consumers pull data from brokers. Other systems brokers push data or stream data to consumers. Messaging is usually a pull-based system (SQS, most MOM use pull). With the pull-based system, if a consumer falls behind, it catches up later when it can.

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What is the difference between Kafka streams and Kafka Connect? ›

Kafka Streams is an API for writing client applications that transform data in Apache Kafka. You usually do this by publishing the transformed data onto a new topic. The data processing itself happens within your client application, not on a Kafka broker. Kafka Connect is an API for moving data into and out of Kafka.

How do you test for Debezium? ›

For Debezium Testing, you can use Debezium Testcontainers that allows setting all the required components like Apache Kafka, Kafka Connect, and using Linux container image. It configures and deploys the Debezium connector and runs assertions against produced change data events.

Learn More Now ›

How do I update my Debezium connector? ›

Updating a Debezium MySQL connector with table whitelist option

Pause the connector.
Deleted the history topic (maybe this was the problem?).
Updated the config via API update config endpoint.
Resume the connector.

Nov 28, 2018

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How do you check Debezium? ›

You can use the JMX metrics provided by Apache Zookeeper, Apache Kafka, and Kafka Connect to monitor Debezium. To use these metrics, you must enable them when you start the Zookeeper, Kafka, and Kafka Connect services. Enabling JMX involves setting the correct environment variables.

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What are the drawbacks of Kafka Connect? ›

Limitations of Fault Tolerance with the Connector

The default retention time is 7 days. If the system is offline for more than the retention time, then expired records will not be loaded. Similarly, if Kafka's storage space limit is exceeded, some messages will not be delivered.

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How many connections can Kafka handle? ›

A maximum of 16384 GiB of storage per broker. A cluster that uses IAM access control can have up to 3000 TCP connections per broker at any given time. To increase this limit, you can adjust the listener.

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How do I know if Kafka Connect is running? ›

You can use the REST API to view the current status of a connector and its tasks, including the ID of the worker to which each was assigned. Connectors and their tasks publish status updates to a shared topic (configured with status. storage. topic ) which all workers in the cluster monitor.

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Why do we have 3 replications in Kafka? ›

A replication factor is the number of copies of data over multiple brokers. The replication factor value should be greater than 1 always (between 2 or 3). This helps to store a replica of the data in another broker from where the user can access it.

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How many modes exist in Kafka connect? ›

Standalone vs. Distributed Mode

There are two modes for running workers: Standalone mode: Useful for development and testing Kafka Connect on a local machine.

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Can we change replication factor Kafka? ›

You can increase or decrease the replication factor with the kafka-reassign-partitions tool. To do so, you create a reassignment plan in a JSON file that specifies the increased or decreased replicas.

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Should you deploy Kafka in Kubernetes? ›

As mentioned earlier, any single app on Kubernetes doesn't bring you much benefits. Kubernetes really shines when you use it to manage all your applications and infrastructure. Running Kafka brokers on Kubernetes is most beneficial if the line of business applications are running on Kubernetes too.

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How do I connect InfluxDB to Kafka? ›

Learn how to integrate Apache Kafka with InfluxDB using Kafka Connect and implement a Scala Avro message producer to test the setup.

Setup a docker development environment.
Run an InfluxDB Sink Kafka Connector.
Create a Kafka Avro producer in Scala (use the schema registry)
Generate some messages in Kafka.

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How do you deploy Kafka in production? ›

Get Started with Kafka Connect.
Kafka Connect 101.
Connect to Confluent Cloud.
Connect to External Systems.
Connect on z/OS.
Quick Start: Move Data In and Out of Kafka with Kafka Connect.
Single Message Transforms for Confluent Platform. DropHeaders. ...
Get Started With RBAC and Kafka Connect. Configure RBAC for a Connect Cluster.

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How do I get a list of deployments in Kubernetes? ›

Run kubectl get deployments to check if the Deployment was created. ...
To see the Deployment rollout status, run kubectl rollout status deployment/nginx-deployment . ...
Run the kubectl get deployments again a few seconds later. ...
To see the ReplicaSet ( rs ) created by the Deployment, run kubectl get rs .

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What is the difference between deployment and service in Kubernetes? ›

What's the difference between a Service and a Deployment in Kubernetes? A deployment is responsible for keeping a set of pods running. A service is responsible for enabling network access to a set of pods. We could use a deployment without a service to keep a set of identical pods running in the Kubernetes cluster.

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How do you troubleshoot Kubernetes deployment? ›

Troubleshooting your deployment in Kubernetes environment

Get nodes information and check the status of nodes is Ready kubectl get nodes -o wide.
Review the Persistent Volume and Persistent Volume Claim information and ensure they match with your deployment YAML ﬁles kubectl describe pv <pv name> -n <namespace>

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What is the best way to deploy Kubernetes? ›

If placing all of your data and workloads in a public cloud is acceptable, the easiest way to deploy and consume Kubernetes is through a hosted service provided by a major public cloud vendor.

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What is the difference between pod and deployment? ›

Their Role in Building and Managing Software

As we now know, a pod is the smallest unit of Kubernetes used to house one or more containers and run applications in a cluster, while deployment is a tool that manages the performance of a pod.

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What is the difference between deployment YAML and service YAML in Kubernetes? ›

Deployment vs service

A deployment is used to keep a set of pods running by creating pods from a template. A service is used to allow network access to a set of pods. Both services and deployments choose which pods they operate on using labels and label selectors. This is where the overlap is.

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Is there something better than Kafka? ›

ActiveMQ, RabbitMQ, Amazon Kinesis, Apache Spark, and Akka are the most popular alternatives and competitors to Kafka.

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What can I use instead of Kafka? ›

Top 10 Alternatives to Apache Kafka

Google Cloud Pub/Sub.
MuleSoft Anypoint Platform.
Confluent.
IBM MQ.
RabbitMQ.
Amazon MQ.
Azure Event Hubs.
KubeMQ.

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Is Debezium open source? ›

Debezium is an open source project that provides a low latency data streaming platform for change data capture (CDC). You setup and configure Debezium to monitor your databases, and then your applications consume events for each row-level change made to the database.

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What is the difference between Debezium server and Kafka Connect? ›

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What are common causes of poor performance in databases? ›

Database performance issues are a common cause of web application bottlenecks. Most of these problems boil down to a lack of indexing, inefficient queries, and the misuse of data types, which can all be easily fixed.

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Which database is best for performance? ›

Besides SQL language, SQL Server also includes Transact-SQL (T-SQL), which is Microsoft's extension to the SQL used to interact with relational databases. SQL Server is a good option for businesses that want to scale the performance, availability, and security seamlessly based on their requirements.

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Can I use Debezium without Kafka? ›

An alternative way for using the Debezium connectors is the embedded engine. In this case, Debezium won't be run via Kafka Connect, but as a library embedded into your custom Java applications.

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Does Debezium use Kafka? ›

Debezium is a distributed platform that converts information from your existing databases into event streams, enabling applications to detect, and immediately respond to row-level changes in the databases. Debezium is built on top of Apache Kafka and provides a set of Kafka Connect compatible connectors.

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Is Debezium fast? ›

React quickly

When all things are running smoothly, Debezium is fast. And that means your apps and services can react quickly. Debezium is built on top of Apache Kafka, which is proven, scalable, and handles very large volumes of data very quickly.

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What are different Kafka connectors? ›

Use Kafka Connectors to move data between Apache Kafka® and other external systems that you want to pull data from or push data to. You can download these popular connectors from Confluent Hub. JDBC Source and Sink Connector. Google BigQuery Sink Connector. JMS Source Connector.

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What is MongoDB Kafka connector? ›

The MongoDB Kafka connector is a Confluent-verified connector that persists data from Kafka topics as a data sink into MongoDB as well as publishes changes from MongoDB into Kafka topics as a data source.

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What is Debezium vs JDBC? ›

Debezium provides records with more information about the database changes, and JDBC Connector provides records which are more focused about converting the database changes into simple insert/upsert commands. Different topic naming.

Is Debezium a sink connector? ›

sink connectors, which propagate data from Kafka topics into other systems.

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What are the 4 major Kafka APIs? ›

Producer API -It allows an application to publish streams of records. Consumer API -It permits an application to subscribe to topics and process streams of records for consumption. Connector API -This API simply executes consumer APIs with existing applications.

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Does Kafka use HTTP or TCP? ›

Kafka uses a binary protocol over TCP. The protocol defines all APIs as request response message pairs. All messages are size delimited and are made up of the following primitive types.

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What is the difference between Kafka and Kafka connect? ›

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How to push data from Kafka to MongoDB? ›

Steps to set up the Kafka to MongoDB Connection

Step 1: Installing Kafka.
Step 2: Installing the Debezium MongoDB Connector for Kafka.
Step 3: Adding Jar Files to the Class-Path & Starting Confluent.
Step 4: Creating Configuration Files & Kafka Topics.
Step 5: Enabling the Connector.

Oct 7, 2021

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What is the alternative to Debezium? ›

Top Alternatives to Debezium

Kafka. Kafka is a distributed, partitioned, replicated commit log service. ...
Logstash. Logstash is a tool for managing events and logs. ...
Slick. It is a modern database query and access library for Scala. ...
DataGrip. ...
Spring Data. ...
Microsoft SQL Server Management Studio. ...
DBeaver. ...
dbt.

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What port does Kafka connect run on? ›

Since Kafka Connect is intended to be run as a service, it also supports a REST API for managing connectors. By default this service runs on port 8083 .