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Month: September 2025

debezium

Implementing the Outbox Pattern with Debezium

Posted on September 27, 2025September 27, 2025 by admin

Introduction Modern applications often need to store data and at the same time publish events.Example: If the app writes to the database and Kafka separately, things can go wrong: This problem is called the dual-write problem.The Outbox Pattern solves it.

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debezium

Production-Grade Debezium Connector with Kafka (Postgres Outbox Example – E-Commerce Orders)

Posted on September 27, 2025September 27, 2025 by admin

Introduction Running Debezium in production is very different from running it locally. In production, the pipeline must be: This article shows how to build a production-grade Debezium + Kafka connector using the Outbox Pattern with PostgreSQL in an e-commerce order system.

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debezium

Connecting Debezium with Kafka for Real-Time Streaming

Posted on September 27, 2025September 27, 2025 by admin

Introduction Modern systems need real-time data. For example: Batch jobs are too slow for these cases. The solution is to build a real-time streaming pipeline. Together, they form a strong foundation for event-driven systems.

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debezium

Debezium Architecture – How It Works and Core Components

Posted on September 27, 2025September 27, 2025 by admin

Introduction Modern systems need to move data fast and in real time. A small change in a database, like a new order or an update to a customer’s profile, must reach many systems instantly: analytics dashboards, search engines, caches, or other microservices. Debezium helps solve this challenge. It is an open-source platform for Change Data…

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debezium

What is Debezium? – An Introduction to Change Data Capture

Posted on September 22, 2025October 8, 2025 by admin

Introduction Today, many companies need to move data quickly from one system to another. For example, when a new order is made in an online shop, that order data must be sent to many other systems: payment, inventory, shipping, and reports. Doing this manually is slow and complex. This is where Debezium comes in.

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kafka

Offset Management and Consumer Groups in Kafka

Posted on September 22, 2025September 22, 2025 by admin

When talking about Apache Kafka, two very important concepts are offsets and consumer groups. These two work together to make sure messages are read correctly, even when there are many consumers.

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kafka

Partitions, Replication, and Fault Tolerance in Kafka

Posted on September 22, 2025September 22, 2025 by admin

Apache Kafka is built to handle big data and stay reliable even when some servers fail. The secret lies in three concepts: partitions, replication, and fault tolerance.

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kafka

Delivery Semantics in Kafka: At Most Once, At Least Once, Exactly Once

Posted on September 22, 2025September 22, 2025 by admin

When working with Apache Kafka, one of the most important questions is:How many times can a message be delivered to a consumer? This is called delivery semantics. Kafka supports three modes: at most once, at least once, and exactly once.

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kafka

Producers and Consumers: How Data Flows in Kafka

Posted on September 14, 2025September 14, 2025 by admin

One of the most important things to understand in Apache Kafka is how data flows. This happens through two main actors: producers and consumers.

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kafka

Kafka Architecture Explained: Brokers, Topics, Partitions, and Offsets

Posted on September 14, 2025September 14, 2025 by admin

Apache Kafka may look complex at first, but its main building blocks are simple. If you understand brokers, topics, partitions, and offsets, you can understand how Kafka works.

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Widhian Bramantya

Recent Posts

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  • Elasticsearch Best Practices for Beginners
  • Implementing the Outbox Pattern with Debezium
  • Production-Grade Debezium Connector with Kafka (Postgres Outbox Example – E-Commerce Orders)
  • Connecting Debezium with Kafka for Real-Time Streaming
  • Debezium Architecture – How It Works and Core Components
  • What is Debezium? – An Introduction to Change Data Capture
  • Offset Management and Consumer Groups in Kafka
  • Partitions, Replication, and Fault Tolerance in Kafka
  • Delivery Semantics in Kafka: At Most Once, At Least Once, Exactly Once

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