Apache Kafka is the New Black at the Edge in Industrial IoT, Logistics and Retailing

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Headings…
Apache Kafka is the New Black at the Edge in Industrial IoT, Logistics and
Multiple Kafka Clusters Became the Norm, not an Exception!
What is “The Edge” or “Edge Computing”?
Apache Kafka at the Edge
Use Cases for Kafka at the Edge
Kafka at the Edge – High Level Architecture
Why and How does Kafka help at the Edge?
Challenges at the Edge
The Same Infrastructure and Technology at the Edge and in the Data Center 

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The last section discusses how Kafka as event streaming platform complements other IoT frameworks and products at the edge for data integration and edge processing in real time at scale.
A Kafka deployment at the edge can be an independent project.
This blog post focuses on the deployment of kafka/”>Apache Kafka at the edge.
Apache Kafka at the Edge
Edge and Beyond: Kafka Cluster deployed at the edge.
In most scenarios, “Kafka at the edge” means the deployment of a Kafka cluster on site at the edge.
Now let’s think about use cases for running Kafka at the edge.
Use Cases for Kafka at the Edge
Use cases for Kafka deployments at the edge exist in various industries.
No matter which use case you want to implement: The architecture for Apache Kafka at the edge typically looks more or less like the following (on a very high level):
Let’s take a loot at different options for deploying Kafka at the edge.
Resilient Deployment at the Edge with 3+ Kafka Brokers
Non-Resilient Deployment at the Edge with One Single Kafka Broker
The demand to deploy a “lightweight Kafka cluster” at the edge and synchronize / replicate data with a bigger central Kafka cluster comes up more and more.
Due to hardware limitations or lower SLAs regarding high availability, the deployment of just one single Kafka broker (plus one Zookeeper) at the edge is totally fine.
Communication, connectivity, integration and data processing are important components in a Kafka infrastructure, no matter if in the cloud, on premise or at the edge:
Edge-Only: Device -> Kafka at the edge -> Device Edge-to-Remote: Device -> Kafka at the edge -> Replication -> Kafka (Data Center / Cloud) -> Analytics / Real Time Processing Bidirectional: A combination of 1) and 2) for bidirectional communication between the edge and remote Kafka cluster
24/7 deployments, zero data loss, and real time processing without latency spikes are requirements Kafka works best for

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