Amazon Technologies, Inc.

Manoj Bhagwan Jadhav

Harsha Ramalingam

Zachary Ganwise Fewtrell

Srinivasa Susheel Kumar Mannepalli

Gaurav Dubey

Bhavnish H Lathia

Kurt Kufeld

Anthony G Anton, Iii

Scott Cameron Webster

Computing platforms may enable clients to use services to perform data processing jobs. A given job may utilize several services in a service call pattern. Each of these services consumes resources during execution. Described herein are systems, devices, and methods for determining costs associated with performance of a service call pattern. Weight data may be generated for each service using various metrics. As service calls are made in the service call pattern, an accumulated weight value is generated which is indicative of the weight data of the services in the service call pattern. The accumulated weight data may represent metrics such as amounts of resources consumed, latency, and transactions per second.

Cost determination of a service call

Computing platforms may enable clients to use services to perform data processing jobs. A given job may utilize several services in a service call pattern. Each of these services consumes resources during execution. Described herein are systems, devices and methods for determining costs associated with performance of a service call pattern. Weight data may be generated for each service using various metrics. As service calls are made in the service call pattern, an accumulated weight value is generated which is indicative of the weight data of the services in the service call pattern. The accumulated weight data may represent metrics such as amounts of resources consumed, latency, and transactions per second.

Determining cost of service call

Service fleets made up of many pieces of computer hardware may perform computational tasks. Described herein are systems and methods for optimizing costs associated with the computer hardware. In one example, an optimization system indicates an amount of hardware needed such that the service fleet operates at an optimal cost. The amount of hardware may be determined based on hardware cost metric data generated for a service fleet.

Systems and methods providing optimization data

This disclosure is directed, at least partly, to automating infrastructure operations performed for a computing service. The infrastructure operations may include many tasks that are infrequently preformed by a service owner. In some embodiments, the infrastructure operations may include procuring hardware, configuring network settings, configuring security, determining and implementing monitors/alarms, deploying the computing service, and/or scaling or otherwise maintaining the computing service. Since the service owners infrequently perform these tasks, deployment of each computing service may require the service owner to reinvent or relearn each of the infrastructure operations, which may result in large inefficiencies, errors, delays, unnecessary costs, and other undesirable outcomes. By automating at least a portion of the infrastructure operations, or otherwise creating a simplified portal with a common user interface, the service owners may more easily deploy their computing service, thereby reducing errors, delays, and unnecessary costs.

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Hyderabad Telangana, India

Manoj Bhagwan Jadhav