- Release Notes and Announcements
- Product Introduction
- Purchase Guide
- Getting Started
- Operation Guide
- Instance Management
- Creating Instance
- Naming with Consecutive Numeric Suffixes or Designated Pattern String
- Viewing Instance
- Upgrading Instance
- Downgrading Instance Configuration
- Terminating/Returning Instances
- Change from Pay-as-You-Go to Monthly Subscription
- Upgrading Instance Version
- Adding Routing Policy
- Public Network Bandwidth Management
- Connecting to Prometheus
- AZ Migration
- Setting Maintenance Time
- Setting Message Size
- Topic Management
- Consumer Group
- Monitoring and Alarms
- Smart Ops
- Permission Management
- Tag Management
- Querying Message
- Event Center
- Migration to Cloud
- Data Compression
- Instance Management
- CKafka Connector
- Practical Tutorial
- Practical Tutorial of CKafka Client
- Connector Practical Tutorial
- Connecting Flink to CKafka
- Connecting Schema Registry to CKafka
- Connecting Spark Streaming to CKafka
- Connecting Flume to CKafka
- Connecting Kafka Connect to CKafka
- Connecting Storm to CKafka
- Connecting Logstash to CKafka
- Connecting Filebeat to CKafka
- Multi-AZ Deployment
- Log Access
- Replacing Supportive Route (Old)
- Practice Tutorial for Cluster Bandwidth in High CPU Utilization Scenarios
- Practice Tutorial for Cluster Capacity Planning
- Troubleshooting
- API Documentation
- History
- Introduction
- API Category
- Making API Requests
- DataHub APIs
- ACL APIs
- Topic APIs
- BatchModifyGroupOffsets
- BatchModifyTopicAttributes
- CreateConsumer
- CreateDatahubTopic
- CreatePartition
- CreateTopic
- CreateTopicIpWhiteList
- DeleteTopic
- DeleteTopicIpWhiteList
- DescribeDatahubTopic
- DescribeTopic
- DescribeTopicAttributes
- DescribeTopicDetail
- DescribeTopicProduceConnection
- DescribeTopicSubscribeGroup
- FetchMessageByOffset
- FetchMessageListByOffset
- ModifyDatahubTopic
- ModifyTopicAttributes
- DescribeTopicSyncReplica
- Instance APIs
- Route APIs
- Other APIs
- Data Types
- Error Codes
- SDK Documentation
- General References
- Conducting Production and Consumption Pressure Testing on CKafka
- Configuration Guide for Common Parameters in CKafka
- Connecting to Legacy Self-Built Kafka
- Suggestions for CKafka Version Selection
- CKafka Data Reliability Description
- Connector
- FAQs
- Service Level Agreement
- Contact Us
- Glossary
- Release Notes and Announcements
- Product Introduction
- Purchase Guide
- Getting Started
- Operation Guide
- Instance Management
- Creating Instance
- Naming with Consecutive Numeric Suffixes or Designated Pattern String
- Viewing Instance
- Upgrading Instance
- Downgrading Instance Configuration
- Terminating/Returning Instances
- Change from Pay-as-You-Go to Monthly Subscription
- Upgrading Instance Version
- Adding Routing Policy
- Public Network Bandwidth Management
- Connecting to Prometheus
- AZ Migration
- Setting Maintenance Time
- Setting Message Size
- Topic Management
- Consumer Group
- Monitoring and Alarms
- Smart Ops
- Permission Management
- Tag Management
- Querying Message
- Event Center
- Migration to Cloud
- Data Compression
- Instance Management
- CKafka Connector
- Practical Tutorial
- Practical Tutorial of CKafka Client
- Connector Practical Tutorial
- Connecting Flink to CKafka
- Connecting Schema Registry to CKafka
- Connecting Spark Streaming to CKafka
- Connecting Flume to CKafka
- Connecting Kafka Connect to CKafka
- Connecting Storm to CKafka
- Connecting Logstash to CKafka
- Connecting Filebeat to CKafka
- Multi-AZ Deployment
- Log Access
- Replacing Supportive Route (Old)
- Practice Tutorial for Cluster Bandwidth in High CPU Utilization Scenarios
- Practice Tutorial for Cluster Capacity Planning
- Troubleshooting
- API Documentation
- History
- Introduction
- API Category
- Making API Requests
- DataHub APIs
- ACL APIs
- Topic APIs
- BatchModifyGroupOffsets
- BatchModifyTopicAttributes
- CreateConsumer
- CreateDatahubTopic
- CreatePartition
- CreateTopic
- CreateTopicIpWhiteList
- DeleteTopic
- DeleteTopicIpWhiteList
- DescribeDatahubTopic
- DescribeTopic
- DescribeTopicAttributes
- DescribeTopicDetail
- DescribeTopicProduceConnection
- DescribeTopicSubscribeGroup
- FetchMessageByOffset
- FetchMessageListByOffset
- ModifyDatahubTopic
- ModifyTopicAttributes
- DescribeTopicSyncReplica
- Instance APIs
- Route APIs
- Other APIs
- Data Types
- Error Codes
- SDK Documentation
- General References
- Conducting Production and Consumption Pressure Testing on CKafka
- Configuration Guide for Common Parameters in CKafka
- Connecting to Legacy Self-Built Kafka
- Suggestions for CKafka Version Selection
- CKafka Data Reliability Description
- Connector
- FAQs
- Service Level Agreement
- Contact Us
- Glossary
Conducting Production and Consumption Pressure Testing on CKafka
Last updated: 2024-01-09 15:02:47
Testing Tool
The open-source script of the Kafka client can be used for Kafka producer and consumer performance testing. Test results are displayed mainly based on the size of messages sent per second (MB/second) and the number of messages sent per second (records/second).
Kafka producer test script:
$KAFKA_HOME/bin/kafka-producer-perf-test.shKafka consumer test script:
$KAFKA_HOME/bin/kafka-consumer-perf-test.shTesting Command
Note:
The
ckafka vip:vport in the following sample commands should be replaced by the actual IP and port assigned for your instance.Sample command for production testing:
bin/kafka-producer-perf-test.sh--topic test--num-records 123--record-size 1000--producer-props bootstrap.servers= ckafka vip : port--throughput 20000
Sample command for consumption testing:
bin/kafka-consumer-perf-test.sh--topic test--new-consumer--fetch-size 10000--messages 1000--broker-list bootstrap.servers=ckafka vip : port
Suggestions
We recommend you create three or more partitions to increase throughput. This is because there must be at least three CKafka cluster nodes at the backend. If only one partition is created, it will be distributed in a single broker, which will affect CKafka performance.
As messages in each CKafka partition are ordered, the production performance will be affected if there are too many partitions. We recommend you create up to six partitions.
It is necessary to simulate concurrency with multiple clients to ensure the testing effect. We recommend you use multiple test servers as the pressure test clients (producers) and start multiple pressure test programs on each test server to increase concurrency. To avoid the high load of test servers, you are also recommended to start one producer every second rather than all producers simultaneously.
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