International Business Machines Corporation

Kyndryl, Inc.

Xu Hui Bai

Yue Wang

Li Long Chen

Wen Rui Zhao

Min Xiang

Ann Corrao

Lan Luo

Jian Dong Yin

Li Xia

Li Na Yuan

In an approach to improve workload orchestration in a multi-cloud environment, embodiments orchestrate and manage a workload in a decentralized multi-cloud environment using one or more smart contracts. Additionally, embodiments measure, by a competency measurement component, competency of cloud services based on one or more predefined cloud benchmarks, a consensus network, and the one or more smart contracts, and generate an orchestration plan that is a best fit for the workload. Furthermore, embodiments validate and update, by the consensus network and the one or more smart contracts, the generated orchestration plan, and executing the generated orchestration plan.

Workload orchestration in a multi-cloud environment

Executing serverless application functions is provided. A response to a user request for a service is received with an include callback parameter and a transaction identifier of the user request included in a header of the response from an external service via a network. A checkpoint of a container corresponding to the service is retrieved from a data store using the transaction identifier of the user request. The container corresponding to the service is restored using the checkpoint to process the response received from the external service.

Serverless application function execution

In an approach to intelligent scaling in a cloud platform, an attribute template is stored for one or more target services based on one or more system data. One or more request metrics for each target service is stored, wherein the request metrics are based on an analysis of one or more incoming requests of one or more service call chains. Responsive to receiving a request for a target service in a service call chain, the target service is scaled based on the attribute template of the target service and the request metrics of the target service.

Intelligent scaling in microservice-based distributed systems

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Beijing, China

Xu Hui Bai