Amazon Technologies, Inc.

Prashant Prahlad

Rajesh Viswanathan

Tanya Bansal

William Trotter Shelton

Veeraraghavan Vijayaraj

Adam Daniel Everett Wright

Benjamin John Ullom

Amit Kumar Gupta

Onur Filiz

Archana Srikanta

Song Hu

Anil M Kumar

Matthew John Hinkle

The present application relates to performing a scale-down of the computing resources allocated to executing a software application. For example, the software application for implementing a web server may be packaged as a container image, and one or more instances of the container images may be executed as one or more tasks. The individual tasks may be allocated a set of computing resources such as CPU and memory, and the incoming requests sent to the web server may be distributed across the tasks. If the volume of incoming requests drops below a threshold level, one or more of the tasks may be placed in standby mode, and the amount of computing resources allocated to such tasks may be reduced. When the volume of incoming requests returns above the threshold level, the amount of computing resources allocated to such tasks can be scaled back up to the full amount.

Scaling down computing resource allocations for execution of containerized applications

The present application relates to performing a scale-up of the computing resources allocated to executing a software application. For example, the software application for implementing a web server may be packaged as a container image, and one or more instances of the container images may be executed as one or more tasks. The individual tasks may be allocated a set of computing resources such as CPU and memory, and the incoming requests sent to the web server may be distributed across the tasks. If the volume of incoming requests drops below a threshold level, one or more of the tasks may be placed in standby mode, and the amount of computing resources allocated to such tasks may be reduced. When the volume of incoming requests returns above the threshold level, the amount of computing resources allocated to such tasks can be scaled back up to the full amount.

Scaling up computing resource allocations for execution of containerized applications

Techniques are described for identifying 'out-of-band' modifications to an interrelated set of computing resources, also referred to herein as a computing resource stack, that was provisioned at a service provider network using an infrastructure modeling service. An infrastructure modeling service generally allows users to describe a computing resource stack in a text file or other type of descriptive representation, referred to herein as an infrastructure template, and to automatically provision computing resource stacks defined in templates at a service provider network. Users may at times make so-called out-of-band modifications to one or more computing resources of a provisioned computing resource stack, either inadvertently or in response to time-sensitive demands, where an out-of-band modification is made outside of the infrastructure modeling service.

Detecting configuration drift for computing resource stacks

Configurations of computing resources established in a network-based computing service can be tested to assess impacts of proposed changes to the configuration states of the computing resources or to policies governing the configurations of such computing resources. Test environments can be established to simulate an operational computing environment under study. Changes to the configuration of one or more computing resources can be introduced to the test environment, and impacts to the test environment can be assessed. Changes to configuration policy can also be introduced and subsequent impacts can be observed.

Resource configuration testing service

A configuration history service for web-based computing resources is implemented by capturing and storing a historical record of each configuration state for each computing resource in a subscriber's account. Files of the configuration history store information about a computing resource type offered by the web service. The file comprises records for each particular resource of that type that is or was actively configured in the subscriber's account during the period that the configuration history service is active in the account. Each record lists a particular configuration state, at a particular point in time, for a particular computing resource. The configuration history of a computing resource can be displayed as a timeline by which a subscriber can access information describing the configuration state of the particular computing resource at any point in time.

Resource configuration history service

Configurations of computing resources established on a web-based computing service can be monitored, managed and controlled. According to one embodiment, a method may include discovering a set of computing resources being used by an enterprise. The disclosed resource configuration service can deliver a set of resource-specific data that uniquely identifies each computing resource and describes each resource's configuration state. The resource configuration service monitors the computing environment and detects changes to the configurations of computing resources. The resource configuration service can deliver a stream of notifications when computing resources are created, updated, deleted or otherwise reconfigured. The notifications can be used by, for example, software tools or system administrators.

Resource configuration service

Configurations of computing resources established on a web-based computing service can be monitored, managed and controlled. According to an embodiment, a configuration compliance service is implemented. Policy rules governing attributes of configuration states for computing resources in a subscriber's account are defined. The computing resources in the account are monitored for changes to configuration states. In response to detection of a change to a configuration state that violates a rule, a predefined action is taken. The predefined action can include sending a notification to the subscriber's account, reconfiguring the configuration state of the computing resource, and deactivating the computing resource.

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Seattle, WA, United States of America

Prashant Prahlad