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Orchestration Made Easy with Zeebe and Kafka

Orchestration with Zeebe and Kafka as a workflow engine was approached to encounter the challenges faced by microservices. In other words, shifting from monolith to microservices was a bold move. But it also brought issues of complexity and lack of visibility. Therefore, these orchestration tools formed a layer to monitor and manage long-running business processes that span multiple microservices.

While businesses were already using Microservice Choreography to handle the interaction between microservices, complexity and visibility issues persisted.

This diagram shows  how Choreography had been the exact opposite of what you expect:

Choreography Expectations vs Reality.png

As a result, microservice orchestration with Zeebe and Kafka evolved that is loosely coupled, autonomous, ensure visibility (unlike choreography), and supports continuous progress. At present, the approach is being widely used to handle the interaction between microservices.

let us discuss in detail about these orchestration tools:

Orchestration with Zeebe and Kafka

What is Apache Kafka?

Apache Kafka is an open-source stream-processing software platform created by LinkedIn in 2011 to handle throughput, low latency transmission, and processing of the stream of records in real-time.

It has the following three significant capabilities, which makes it ideal for users:

1. Publishing and subscribing to the stream of records.

2. Storing streams of record in a fault-tolerant way.

3. Processing stream of records as they occur.

Why is it critical for your company?

1. Acts as the backbone of your business

Apache Kafka works in multi-step intermediator. It receives data from the source system and makes it available to target systems in real-time. Your systems won’t crash as Kafka has its set of servers (Apache Kafka cluster).

2. Enables easy integrations

As all your data streams through Apache Kafka, there is no need to add multiple integrations. Instead, you only have to create one integration for each producing system and each consuming system.

3. Low latency and high throughput

By decoupling your data-streams, Apache Kafka lets you consume data when you want it. It can scale to hundreds of servers within a cluster to manage big data.

Big companies like Uber, Airbnb, and Twitter are using Kafka for integrating their diverse kinds of data, for example, page searches, shopping cart, likes, all go into the predictive analytics engine to analyze customer behavior.

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