Confluent · CCAC
Validates the ability to operate and manage Apache Kafka on Confluent Cloud, covering core cloud concepts, Kafka operations, streaming pipelines, data governance, and cloud resilience.
Questions
630
Duration
90 minutes
Passing Score
70%
Difficulty
AssociateLast Updated
Feb 2026
Use this CCAC practice exam to prepare for Confluent Cloud Certified Operator (CCAC) with realistic questions, detailed explanations, and focused study modes. The practice bank includes 630 questions for Confluent CCAC, so you can review the exam steadily instead of relying on one long cram session.
As you practice, pay extra attention to patterns in your missed answers. Start with short sessions to identify weak areas, then move into timed quizzes once your accuracy is consistent.
The explanations are especially useful when you want to connect exam wording to the responsibilities and scenarios described in the official certification guidance. Use the free preview first, then unlock the full question bank when you are ready to build a complete study routine.
The Confluent Cloud Certified Operator (CCAC) certification validates a candidate's ability to operate and manage Apache Kafka workloads on Confluent Cloud. It covers the full operational lifecycle of cloud-native Kafka deployments, including cluster provisioning, configuration, monitoring, security, stream processing, and data governance. The certification is specifically oriented toward Confluent Cloud's managed service offerings—such as fully managed connectors, Cluster Linking, Schema Registry, and ksqlDB—rather than self-managed or on-premises deployments.
The exam is structured around seven weighted domains that span core cloud concepts through resilience and disaster recovery. With 60 multiple-choice questions delivered in 90 minutes and a passing threshold of 70%, the CCAC is positioned at the associate difficulty level, making it accessible to professionals with foundational Kafka knowledge who are transitioning into or actively working within Confluent Cloud environments. The certification is valid for two years, after which recertification is required.
This certification is best suited for cloud engineers, DevOps engineers, site reliability engineers (SREs), platform engineers, and Kafka administrators who are responsible for day-to-day operations of Confluent Cloud deployments. It is particularly relevant for professionals who manage topics, partitions, connectors, access controls, and streaming pipelines within Confluent Cloud rather than self-managed Kafka clusters.
Candidates should have hands-on experience deploying and managing Confluent Cloud clusters, working with the Confluent Cloud Console and CLI, and operating streaming data infrastructure in production environments. It is also appropriate for infrastructure engineers moving from traditional Kafka administration (CCAAK) toward fully managed cloud operations.
There are no formal prerequisites required to register for the CCAC exam. However, Confluent strongly recommends that candidates have practical experience operating Kafka clusters within Confluent Cloud before attempting the exam. Familiarity with core Apache Kafka concepts—such as topics, partitions, consumer groups, producers, offsets, and replication—is assumed and will not be taught as part of exam preparation.
Candidates are encouraged to complete Confluent's official training courses available through training.confluent.io, particularly those covering Confluent Cloud administration, Stream Governance, and connector management. Hands-on practice using Confluent Cloud's free tier or a trial environment is highly recommended to reinforce operational knowledge across all seven exam domains.
The CCAC exam consists of 60 multiple-choice questions to be completed within a 90-minute time limit. The exam is proctored and can be taken either remotely (from any location meeting internet, security, and privacy requirements) or at an authorized testing center worldwide. Remote delivery requires a webcam, as a proctor monitors the candidate throughout the session. All exams are administered in English.
Candidates receive their pass/fail results immediately upon completing the exam on the testing screen. The passing score is 70%. The exam costs $150 USD. Upon passing, candidates receive a Confluent digital badge and certificate, which can be shared directly to LinkedIn. The certification remains valid for two years from the date of passing.
Earning the CCAC certification demonstrates verified expertise in operating Confluent Cloud, which is increasingly adopted by enterprises building real-time data platforms and event-driven architectures. Roles that commonly list Confluent Cloud experience as a requirement or differentiator include Senior Data Engineer, Kafka Platform Engineer, Cloud Infrastructure Engineer, and SRE. The certification complements existing cloud certifications (AWS, GCP, Azure) by validating streaming data infrastructure skills that are not covered by general cloud provider exams.
The CCAC is positioned at the associate level and serves as a natural entry point before pursuing more advanced Confluent certifications such as the Confluent Certified Developer for Apache Kafka (CCDAK) or the Confluent Certified Administrator for Apache Kafka (CCAAK). The digital badge issued upon passing can be added to LinkedIn profiles and email signatures, providing visible credentialing for job searches and salary negotiations in a market where real-time data expertise commands a premium.
5 sample questions with answers and explanations. Start a practice session to test yourself across all 630 questions.
Preview — answers shown1. A streaming application uses ksqlDB to aggregate session-based user activity. Users are considered active as long as events arrive within 15 minutes of each other. After 15 minutes of inactivity, a new session should start. Which window type should be used? (Select one!)
Explanation
SESSION windows are specifically designed for activity-based grouping where sessions are defined by inactivity gaps. A session window with a 15-minute gap will group events that occur within 15 minutes of each other and start a new session after 15 minutes of inactivity. Tumbling windows use fixed time boundaries regardless of activity patterns. Hopping windows create overlapping fixed-duration windows, not activity-based sessions. Adding a GRACE PERIOD to tumbling windows handles late arrivals but doesn't create session-based grouping.
2. A development team creates a ksqlDB application that performs a stream-stream join between user click events and purchase events. Both streams are keyed by user_id. The join must capture correlations within a 30-minute window. What requirement must be met for this join to function correctly? (Select two!)
Multiple correct answersExplanation
Stream-stream joins in ksqlDB require both co-partitioning and a WITHIN clause. Co-partitioning ensures that records with the same key are in the same partition number across both topics, allowing the join operation to process matching records on the same ksqlDB node. The WITHIN clause is mandatory for stream-stream joins to define the time window for correlating events. Schema format does not need to match between streams. PRIMARY KEY is a table concept, not applicable to streams. While having the same partition count helps with co-partitioning, it is not strictly required if the join key produces compatible partition assignments.
3. A connector development team implements error handling for a Snowflake Sink connector. They configure errors.tolerance=all and specify errors.deadletterqueue.topic.name. After deploying, they observe that malformed records are being skipped but no dead letter queue topic is created. What is the most likely cause? (Select one!)
Explanation
Dead letter queue topics are not automatically created in Confluent Cloud. The topic specified in errors.deadletterqueue.topic.name must be created manually before starting the connector. Dead letter queues are supported for sink connectors, not source connectors. Setting errors.deadletterqueue.context.headers.enable to true adds error context headers but does not trigger DLQ topic creation. There is no delay for DLQ topic appearance since manual creation is required.
4. A platform team provisions a multi-zone Dedicated cluster with 2 CKUs on AWS. After several months of growth, they need to scale the cluster to 8 CKUs to handle increased throughput. They attempt to update the cluster using confluent kafka cluster update with --cku 8, but the operation fails. What is the most likely cause? (Select one!)
Explanation
Credit card billing in Confluent Cloud has a default limit of 4 CKUs per cluster (expandable to 152 CKUs by request to Confluent support). If the account uses credit card billing, attempting to scale directly from 2 CKUs to 8 CKUs would fail because 8 exceeds the 4 CKU limit. Invoice billing accounts allow up to 24 CKUs per cluster by default. Multi-zone clusters do not have a 6 CKU scaling limitation—they can scale to the billing account's CKU limit. While you can only reduce CKU count by 1 CKU at a time when scaling down, scaling up does not have this restriction. The cluster being in a provisioning state would produce a different error about an operation already in progress.
5. A data engineering team operates a Basic cluster with 250 topics and needs to add private networking support due to new security requirements. The cluster currently uses public internet connectivity. What approach should they take? (Select one!)
Explanation
Basic clusters do not support private networking and the networking type cannot be changed after cluster creation. Upgrading from Basic to Standard is supported, but Standard clusters also do not support private networking. Only Enterprise and Dedicated clusters support private networking options like VPC Peering and PrivateLink. The correct approach is to create a new Enterprise or Dedicated cluster with private networking configured during provisioning, then use Cluster Linking to migrate topics and data from the Basic cluster.
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