TrendForce analyst Jimmy Liu points out that the digital transformation has become a must for many enterprises, who have realized the challenges brought by massive data to their current information system architectures. Cloud services like storage, data transmission and computing are on the rise, changing the mindsets of enterprises. Major cloud service providers have made eye-catching achievements in recent years, such as Amazon, Microsoft, Google, IBM, and Alibaba Cloud.

However, with increasing growth momentum, the competition among cloud service providers has also become fierce. Before incorporating cloud systems into daily business operations, enterprises are bound to consider the stability, cost-effectiveness, scalability, and sustainability of cloud services, urging service providers to make the functions more integrated and prices more competitive.

In addition, the rise of the Internet of Things has brought dynamic development needs. Users not only upload their systems to the cloud, but also use the cloud platforms for development and testing of IoT applications, further optimizing development costs and shortening the time for product development.

Faced with existing price competition and the emerging diverse needs, cloud service providers started to extend their existing businesses and expand towards IoT platforms and edge computing. Liu notes that, most cloud service providers have established their own IoT platforms and edge computing software, such as AWS IoT Core and AWS Greengrass of Amazon, Azure IoT Solutions and Azure IoT Edge of Microsoft, etc. Based on cloud ecosystems, complete architecture and functions, as well as corresponding development tools for users, the cloud service providers have been shifting to the edge, trying to deliver more comprehensive cloud-to-end solutions on the advantages of the cloud.

Cloud-to-end solutions also assist in data analysis by service providers, who used to collect existing data from applications passively. Together with a large amount of messy data, the analysis was time- and effort-consuming. However, as the cloud-to-edge development tools and ecosystems are built, they can cooperate with edge device makers more actively and have better control of these devices closer to the sources of data such as sensors, end devices, and gateways.

In addition, the enhancement of edge devices will also enable cloud service providers to deploy artificial intelligence, machine learning and other technologies to the edge, and to upgrade vertical fields through various algorithms. The integration of cloud computing, edge computing and professional domain knowledge will also drive the loop of automation, autonomous training, and self-optimization. In this way, cloud service providers and edge device makers will jointly develop new forms of operation in the future to realize the digital transformation.