What describes the relationship between edge computing and cloud computing?

In the context of AWS, if you are developing a distributed system architecture, then you would need to learn the relationship of edge computing and cloud computing. Here is the relationship between both given in the form of their differences:-

Role of edge computing

In edge computing, we can implement various computing resources closer to the data source. It helps the developers to process data locally which leads you to reduce latency. Therefore, it is beneficial for application which has low latency rates such as IoT devices.

Integration of cloud computing

cloud computing is used to complement edge computing. It helps edge computing by providing it with centralized resources. It also helps in storing, analyzing, and even managing large volumes of data compared to edge computing. The complex computational works, analytics, and tasks which is based on intensive data can be done easily by using cloud computing.

Data flow and consistency

In the context of data flow, you would be happy to know that the data flows smoothly between edge and cloud computing. They both have a synchronization mechanism that helps in the maintenance of data fluency across the distributed architecture.

Scalability dynamics

cloud computing is known for the dynamic allocation of resources. It allocates resources based on demand. On the other hand edge computing offers flexibility by providing or distributing the processing power when needed.

Here is the relationship between edge and cloud computing given in the form of a coding analogy. The following coding demonstrates the integration of edge and cloud computing by a simple Python example:-

# Cloud-based processing

Def process_data_in_cloud(data):

    # Cloud-specific processing logic

    Return processed_data

# Edge device processing

Def process_data_at_edge(data):

    # Edge-specific processing logic

    Return processed_data

# Data synchronization between edge and cloud

Def synchronize_data_to_cloud(processed_data):

    # Code for synchronizing data to the cloud

    Pass

# Example usage

Edge_data = fetch_data_from_edge()

Processed_edge_data = process_data_at_edge(edge_data)

Cloud_data = process_data_in_cloud(processed_edge_data)

Synchronize_data_to_cloud(cloud_data)