Prepare Important Exam with CCAAK Exam Dumps(2026)
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Confluent CCAAK Exam Syllabus Topics:
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NEW QUESTION # 26
Which ksqlDB statement produces data that is persisted into a Kafka topic?
- A. INSERT VALUES
- B. SELECT (Pull Query)
- C. SELECT (Push Query)
- D. CREATE TABLE
Answer: A
Explanation:
INSERT VALUES is used to write data directly into a Kafka topic through a ksqlDB stream or table. This data is persisted.
NEW QUESTION # 27
Kafka Connect is running on a two node cluster in distributed mode. The connector is a source connector that pulls data from Postgres tables (users/payment/orders), writes to topics with two partitions, and with replication factor two. The development team notices that the data is lagging behind.
What should be done to reduce the data lag*?
The Connector definition is listed below:
{
"name": "confluent-postgresql-source",
"connector class": "PostgresSource",
"topic.prefix": "postgresql_",
& nbsp;& nbsp;& nbsp;...
"db.name": "postgres",
"table.whitelist": "users.payment.orders",
"timestamp.column.name": "created_at",
"output.data format": "JSON",
"db.timezone": "UTC",
"tasks.max": "1"
}
- A. Increase the number of Connect Nodes.
- B. Increase the replication factor and increase the number of Connect Tasks.
- C. Increase the number of Connect Tasks (tasks max value).
- D. Increase the number of partitions.
Answer: C
Explanation:
The connector is currently configured with "tasks.max": "1", which means only one task is handling all tables (users, payment, orders). This can create a bottleneck and lead to lag. Increasing tasks.max allows Kafka Connect to parallelize work across multiple tasks, which can pull data from different tables concurrently and reduce lag.
NEW QUESTION # 28
Which valid security protocols are included for broker listeners? (Choose three.)
- A. SSL
- B. PLAINTEXT
- C. SASL
- D. GSSAPI
- E. SASL_SSL
Answer: A,B,E
NEW QUESTION # 29
The Consumer property 'auto offset reset' determines what to do if there is no valid offset for a Consumer Group.
Which scenario is an example of a valid offset and therefore the 'auto.offset.reset' does NOT apply?
- A. The Consumer Group started for the first time.
- B. The Consumer offset is less than the smallest offset in the partition (log start offset).
- C. The Consumer offset is greater than the last offset in the partition (log end offset).
- D. When an offset points to a message that has been removed by compaction but is still within the current partition.offset range.
Answer: D
Explanation:
In this scenario, the offset itself is still valid, even though the record at that offset was compacted away. The consumer can continue consuming from the next available record. Therefore, auto.offset.reset does NOT apply, because there is a valid offset present.
NEW QUESTION # 30
If the Controller detects the failure of a broker that was the leader for some partitions, which actions will be taken? (Choose two.)
- A. The Controller sends the new leader and ISR list changes to all producers and consumers.
- B. The Controller sends the new leader and ISR list changes to all brokers.
- C. The Controller waits for a new leader to be nominated by ZooKeeper.
- D. The Controller persists the new leader and ISR list to ZooKeeper.
Answer: B,D
Explanation:
The Controller updates ZooKeeper with the new leader and in-sync replica (ISR) information to maintain metadata consistency.
Brokers need this information to correctly route client requests and continue replication.
NEW QUESTION # 31
A company is setting up a log ingestion use case where they will consume logs from numerous systems. The company wants to tune Kafka for the utmost throughput.
In this scenario, what acknowledgment setting makes the most sense?
- A. acks=undefined
- B. acks=1
- C. acks=all
- D. acks=0
Answer: D
Explanation:
acks=0 provides the highest throughput because the producer does not wait for any acknowledgment from the broker. This minimizes latency and maximizes performance.
However, it comes at the cost of no durability guarantees - messages may be lost if the broker fails before writing them. This setting is suitable when throughput is critical and occasional data loss is acceptable, such as in some log ingestion use cases where logs are also stored elsewhere.
NEW QUESTION # 32
By default, what do Kafka broker network connections have?
- A. Encryption, but no authentication or authorization
- B. Encryption and authentication, but no authorization
- C. No encryption, no authorization, but have authentication
- D. No encryption, no authentication and no authorization
Answer: D
Explanation:
By default, Kafka brokers use the PLAINTEXT protocol for network communication. This means:
* No encryption - data is sent in plain text.
* No authentication - any client can connect without verifying identity.
* No authorization - there are no access control checks by default.
Security features like TLS, SASL, and ACLs must be explicitly configured.
NEW QUESTION # 33
Which tool is used for scalably and reliably streaming data between Kafka and other data systems?
- A. Kafka REST Proxy
- B. Kafka Schema Registry
- C. Kafka Streams
- D. Kafka Connect
Answer: D
Explanation:
Kafka Connect is the tool designed for scalable and reliable integration between Kafka and external data systems (e.g., databases, cloud storage, key-value stores). It supports source connectors (to pull data into Kafka) and sink connectors (to push data from Kafka).
NEW QUESTION # 34
Kafka broker supports which Simple Authentication and Security Layer (SASL) mechanisms for authentication? (Choose three.)
- A. SASL/SAML20
- B. SASL/OAUTHBEARER
- C. SASL/PLAIN
- D. SASL/GSSAPI (Kerberos)
- E. SASL/OTP
Answer: B,C,D
Explanation:
SASL/PLAIN - A simple username/password mechanism supported by Kafka.
SASL/GSSAPI (Kerberos) - Kafka supports Kerberos authentication through the GSSAPI mechanism.
SASL/OAUTHBEARER - Kafka supports OAUTHBEARER for token-based authentication.
NEW QUESTION # 35
How can load balancing of Kafka clients across multiple brokers be accomplished?
- A. Connectors
- B. Replicas
- C. Partitions
- D. Offsets
Answer: C
Explanation:
Partitions are the primary mechanism for achieving load balancing in Kafka. When a topic has multiple partitions, Kafka clients (producers and consumers) can distribute the load across brokers hosting these partitions.
NEW QUESTION # 36
What does Kafka replication factor provide? (Choose two.)
- A. Availability
- B. Security
- C. Performance
- D. Durability
Answer: A,D
Explanation:
Replication ensures that multiple copies of data exist across different brokers, so data is not lost if one broker fails.
With multiple replicas, Kafka can continue to serve data even if the leader or one replica fails, maintaining service availability.
NEW QUESTION # 37
A topic 'recurring payments' is created on a Kafka cluster with three brokers (broker id '0', '1', '2') and nine partitions. The 'min.insync replicas' is set to three, and producer is set with 'acks' as 'all'. Kafka Broker with id '0' is down.
Which statement is correct?
- A. Producers can write messages to all the partitions, because new leaders for the partitions will be elected.
- B. Consumers can read committed messages from partitions on broker id T, "2\
- C. Producers will only be able to write messages to the topic where the Leader for the partition is on Broker id T.
- D. Producers and consumers will have no impact on six of the nine partitions.
Answer: D
Explanation:
With 9 partitions spread across 3 brokers, each broker typically hosts 3 leaders (assuming even distribution). When Broker 0 fails, the partitions for which it was leader will elect new leaders on brokers 1 or 2 if enough in-sync replicas (ISRs) remain. But since min.insync.replicas=3 and only 2 brokers are up, no partition can meet the minimum in-sync replica requirement, so producers with acks=all will fail to write. However, for partitions where Broker 0 is not the leader, consumers can still read committed messages. Given that only 3 partitions likely had Broker 0 as leader, six partitions remain accessible for reads, but not writes.
NEW QUESTION # 38
What is the correct permission check sequence for Kafka ACLs?
What is the correct permission check sequence for Kafka ACLs?
- A. Deny ACL -> Deny -> Allow ACL -> Super Users
- B. Allow ACL -> Deny ACL -> Super Users -> Deny
- C. Super Users -> Deny ACL -> Allow ACL -> Deny
- D. Super Users -> Allow ACL -> Deny ACL-> Deny
Answer: D
Explanation:
Kafka checks permissions in the following sequence:
1. Super Users: If the user is a super user (defined via super.users), access is granted immediately.
2. Allow ACL: If there is a matching Allow ACL, Kafka proceeds to the next step.
3. Deny ACL: If there is a matching Deny ACL, access is denied (even if an Allow exists).
4. Deny: If no matching ACLs are found, access is denied by default.
This order ensures that super users bypass ACLs, denials override allows, and default is deny.
NEW QUESTION # 39
How can authentication for both internal component traffic and external client traffic be accomplished?
- A. Configure multiple brokers.
- B. Configure LoadBalancer.
- C. Configure multiple listeners on the broker.
- D. Configure multiple security protocols on the same listener.
Answer: C
Explanation:
Kafka supports multiple listeners, each with its own port, hostname, and security protocol. This allows you to:
* Use one listener for internal communication (e.g., brokers, ZooKeeper, Connect, etc.) with one type of authentication (e.g., PLAINTEXT or SASL).
* Use a separate listener for external clients (e.g., producers and consumers) with a different protocol (e.g., SSL or SASL_SSL).
NEW QUESTION # 40
What are important factors in sizing a ksqlDB cluster? (Choose three.)
- A. Number of Partitions
- B. Number of Queries
- C. Data Schema
- D. Topic Data Retention
- E. Data Encryption
Answer: A,B,C
Explanation:
The complexity of the schema (number of fields, data types, etc.) affects processing and memory usage.
Each ksqlDB persistent query consumes resources (CPU, memory), so more queries require more capacity.
More partitions increase parallelism, but also resource usage, especially in scaling and state management.
NEW QUESTION # 41
An employee in the reporting department needs assistance because their data feed is slowing down. You start by quickly checking the consumer lag for the clients on the data stream.
Which command will allow you to quickly check for lag on the consumers?
- A. bin/kafka-consumer-groups.sh
- B. bin/kafka-consumer-lag.sh
- C. bin/kafka-consumer-group-throughput.sh
- D. bin/kafka-reassign-partitions.sh
Answer: A
Explanation:
The kafka-consumer-groups.sh script is used to inspect consumer group details, including consumer lag, which indicates how far behind a consumer is from the latest data in the partition.
The typical usage is bin/kafka-consumer-groups.sh --bootstrap-server <broker> --describe --group <group_id>
NEW QUESTION # 42
Your organization has a mission-critical Kafka cluster that must be highly available. A Disaster Recovery (DR) cluster has been set up using Replicator, and data is continuously being replicated from source cluster to the DR cluster. However, you notice that the message on offset 1002 on source cluster does not seem to match with offset 1002 on the destination DR cluster.
Which statement is correct?
- A. The message was updated on source cluster, but the update did not flow into destination DR cluster and errored.
- B. The DR cluster is lagging behind updates; once the DR cluster catches up, the messages will match.
- C. The offsets for the messages on the source, destination cluster may not match.
- D. The message on DR cluster got over-written accidently by another application.
Answer: C
Explanation:
When using Confluent Replicator (or MirrorMaker), offsets are not preserved between the source and destination Kafka clusters. Messages are replicated based on content, but they are assigned new offsets in the DR (destination) cluster. Therefore, offset 1002 on the source and offset 1002 on the DR cluster likely refer to different messages, which is expected behavior.
NEW QUESTION # 43
A broker in the Kafka cluster is currently acting as the Controller.
Which statement is correct?
- A. It can have topic partitions.
- B. It is given precedence for replication to and from replica followers.
- C. It is responsible for sending leader information to all producers.
- D. All consumers are allowed to fetch messages only from this server.
Answer: A
Explanation:
The Controller broker is a regular broker that also takes on additional responsibilities for managing cluster metadata, such as leader elections and partition assignments. It still hosts topic partitions and participates in replication like any other broker.
NEW QUESTION # 44
A company has an existing Kafka cluster running without SSL/TLS enabled. The customer wants to enable SSL on brokers to secure data in transit, but they would like to give applications connecting to this cluster some time to migrate to using SSL connection instead of putting a hard stop.
Which solution will meet the customer's requirements?
- A. Create a new listener with SSL enabled.
- B. Modify the advertised listeners setting on brokers to use SSL.
- C. Enable SSL on the current Listener, and do not enable mTLS.
- D. Enable SSL on the current listener, and do not implement SSL on application side.
Answer: A
Explanation:
Kafka supports multiple listeners, allowing you to run PLAINTEXT and SSL simultaneously. By creating a new SSL-enabled listener (e.g., on a different port), existing applications can continue using PLAINTEXT while gradually migrating to the SSL listener. This approach avoids downtime and gives clients time to adapt without enforcing a hard cutover.
NEW QUESTION # 45
Where are Apache Kafka Access Control Lists stored'?
- A. ZooKeeper
- B. Schema Registry
- C. Broker
- D. Connect
Answer: A
Explanation:
In Apache Kafka (open-source), Access Control Lists (ACLs) are stored in ZooKeeper. Kafka brokers retrieve and enforce ACLs from ZooKeeper at runtime.
NEW QUESTION # 46
Which model does Kafka use for consumers?
- A. Push
- B. Publish
- C. Enrollment
- D. Pull
Answer: D
Explanation:
Kafka uses a pull model for consumers, where consumers poll the broker to retrieve messages at their own pace. This model gives consumers more control over flow and backpressure, improving scalability and reliability.
NEW QUESTION # 47
You want to increase Producer throughput for the messages it sends to your Kafka cluster by tuning the batch size ('batch size') and the time the Producer waits before sending a batch ('linger.ms').
According to best practices, what should you do?
- A. Increase 'batch.size' and increase 'linger.ms'
- B. Increase 'batch.size' and decrease 'linger.ms'
- C. Decrease 'batch.size' and increase 'linger.ms'
- D. Decrease 'batch.size' and decrease 'linger.ms'
Answer: A
Explanation:
Increasing batch.size allows the producer to accumulate more messages into a single batch, improving compression and reducing the number of requests sent to the broker.
Increasing linger.ms gives the producer more time to fill up batches before sending them, which improves batching efficiency and throughput.
This combination is a best practice for maximizing throughput, especially when message volume is high or consistent latency is not a strict requirement.
NEW QUESTION # 48
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