Distributed Messaging Platform in AWS

With the advent of cloud, Mobile and IoT networks, huge volumes of data from disparate sources is being generated in data centers of every enterprise. When it comes to processing this streaming data in real-time, traditional data processing infrastructures have already reached a threshold point. At CloudTern, we understand how important it is for organizations to process streams of data in real-time. To address this challenge, we have designed a world-class distributed streaming solution.

CloudTern Distributed Streaming solution is a distributed messaging system powered by Apache Kafka for the AWS infrastructure. Apache Kafka is an open-source distributed streaming platform that perfectly suits the AWS environment. With AWS and Apache Kafka, CloudTern brings the best of both worlds.


Built-in Fault Tolerance

Partitioned logs are distributed across multiple servers in the Kafka cluster. As each partition is replicated across an assigned number of servers, fault tolerance comes out of the box.

Better Throughput

With an average message overhead of 9 bytes, Kafka offers higher throughput for publishing as well as subscribing to topics.

Built-in Partitioning

Kafka topics are stored in partitioned logs that are arranged in an ordered and immutable sequence. This built-in partitioning allows for insane scaling while balancing ordering guarantees and load balancing.


Kafka uses a Leader-Follower method wherein followers passively replicate the leader. In case a leader fails, one of the followers automatically takes over as the leader.

Data Integration

Data Integration is easy with Kafka as it efficiently captures streams of data or events and feeds them to assigned relational databases.

Stream Processing

By accepting and storing streams of events in append-only logs, Kafka facilitates stream processing in a continuous and real-time manner while making the results available system-wide.

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