\n| Total Available Messages<\/td>\n | 0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/h1>\nPublishing Text Messages to the above topic<\/h3>\nTo demonstrate how Kafka partitions messages based on their keys, I published a few sample messages to the getting-started<\/span> <\/strong><\/em>topic using different message keys.<\/p>\nThe following messages were produced:<\/p>\n Key: a\u00a0 Value: first message<\/em>
\nKey: a\u00a0 Value: second message<\/em>
\nKey: b\u00a0 Value: first message<\/em><\/p><\/blockquote>\nNotice that the first two messages use the same key (a<\/strong><\/span><\/em>), while the third message uses a different key (b<\/strong><\/span><\/em>). This is intentional because Kafka’s default partitioner routes messages with the same key to the same partition. As a result, messages with key (a<\/strong><\/span><\/em>)\u00a0should be stored in the same partition and maintain their order, whereas the message with key (b<\/strong><\/span><\/em>) may be assigned to a different partition.<\/p>\nAfter publishing these messages, Kafdrop immediately reflects the updated state of the topic. The dashboard shows that the topic still contains 3 partitions<\/strong><\/em><\/span>, all preferred replicas remain in a healthy state (100%<\/strong><\/span><\/em>), there are 0 under-replicated partitions<\/strong><\/span><\/em>, and the Total Available Messages<\/strong><\/span><\/em> count has increased to 3<\/strong><\/span><\/em>.<\/p>\nAt a glance, we can confirm that the Kafka cluster is healthy, replication is functioning correctly and the messages have been successfully written to the topic.<\/p>\n ![\"Topic](\"https:\/\/www.tothenew.com\/blog\/wp-ttn-blog\/uploads\/2026\/06\/Screenshot-2026-06-29-at-12.04.14\u202fAM-1024x520.png\") Published Messages Overview | Kafdrop<\/p><\/div>\n <\/p>\n
\n <\/h1>\nUnderstanding Partition Details<\/h1>\n <\/p>\n ![\"Partition](\"https:\/\/www.tothenew.com\/blog\/wp-ttn-blog\/uploads\/2026\/06\/Screenshot-2026-06-20-at-7.58.14\u202fPM-1-1024x698.png\") Partition Details View | Kafdrop<\/p><\/div>\n The Partition Details<\/span><\/strong><\/em> section is one of the most valuable views in Kafdrop because it provides insight into how Kafka has distributed messages across the partitions of a topic. Rather than simply showing that messages exist, it allows you to understand where those messages have been stored and how the topic is being utilised.<\/p>\nFor the getting-started<\/span><\/strong><\/em> topic, the partition information is shown below:<\/p>\n\n\n\nPartition<\/strong><\/td>\n Last Offset<\/strong><\/td>\n<\/tr>\n\n| <\/td>\n | <\/td>\n<\/tr>\n | \n| 0<\/td>\n | 0<\/td>\n<\/tr>\n | \n| 1<\/td>\n | 2<\/td>\n<\/tr>\n | \n| 2<\/td>\n | 1<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n <\/p>\n From the values shown above, we can immediately see that Kafka has not distributed the messages evenly across all three partitions. Instead, messages have been assigned according to Kafka’s partitioning strategy.<\/p>\n By inspecting the partition details in Kafdrop, you can quickly verify whether messages are being distributed as expected, identify potential partition skew and confirm that key-based partitioning is working correctly.<\/p>\n
\n<\/h1>\nUnderstanding Kafka Partition Assignment<\/h1>\nOne of Kafka’s most important features is its ability to consistently route messages with the same key to the same partition. This ensures that messages belonging to the same logical entity are processed in the order they were produced.<\/p>\n This behaviour is critical for:<\/p>\n \n- Order Processing<\/li>\n
- Payment Events<\/li>\n
- Inventory Updates<\/li>\n
- User Activity Streams<\/li>\n<\/ul>\n
<\/p>\n In our example, the getting-started<\/span><\/strong><\/em> topic contains three partitions. When the producer publishes messages with the key a<\/strong><\/span><\/em>, Kafka computes the same hash value each time, resulting in both messages being assigned to Partition 1<\/span><\/strong><\/em>. Similarly, the message with key b is hashed to a different value and is therefore routed to Partition 2.<\/span><\/strong><\/em><\/p>\nAs a result, the messages are distributed as follows:<\/p>\n Partition 1<\/span><\/em><\/strong><\/p>\nKey: a Value: first message<\/span><\/em><\/strong>
\nKey: a Value: second message<\/span><\/em><\/strong><\/p>\nPartition 2<\/span><\/em><\/strong><\/p>\nKey: b Value: first message<\/span><\/em><\/strong><\/p><\/blockquote>\n
\n<\/h1>\nViewing Messages in Kafdrop<\/h1>\nOne of Kafdrop’s most powerful features is direct message inspection.<\/p>\n Click: View Messages<\/span><\/p>\nto browse messages stored in Kafka.<\/p>\n ![\"View](\"https:\/\/www.tothenew.com\/blog\/wp-ttn-blog\/uploads\/2026\/06\/Screenshot-2026-06-20-at-8.02.00\u202fPM-1024x500.png\") View Messages | Kafdrop<\/p><\/div>\n <\/p>\n Kafdrop displays:<\/p>\n \n
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