Analyzing deployment pipelines used to update production computing services using a live pipeline template process

• US 10,255,058 B2
• Filed: 04/25/2017
• Issued: 04/09/2019
• Est. Priority Date: 12/21/2015
• Status: Expired due to Fees

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Frank, Martin Robert, Mosher, Ian Aird, Jodoin, Felix Walter Blue, Mansour, Mark Sidney James, Gu, Sixiang
• Primary Examiner(s): Brophy, Matthew J
• Application Number:
  US15/496,488
• Publication Number:
  US 20170255460A1
• Time in Patent Office: 714 Days
• Field of Search: None
• CPC Class Codes: G06F 11/302 where the computing system component is a software system
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3476 Data logging G06F11/14, G06F11/2205 take precedence
• CPC Class Codes: G06F 11/3688 for test execution, e.g. scheduling of test suites
• CPC Class Codes: G06F 11/3696 Methods or tools to render software testable
• CPC Class Codes: G06F 2009/4557 Distribution of virtual machine instances; Migration and load balancing
• CPC Class Codes: G06F 2201/81 Threshold
• CPC Class Codes: G06F 2201/865 Monitoring of software
• CPC Class Codes: G06F 8/65 Updates security arrangements therefor G06F21/57
• CPC Class Codes: G06F 9/45558 Hypervisor-specific management and integration aspects
• CPC Class Codes: G06Q 10/103 Workflow collaboration or project management
• CPC Class Codes: H04L 41/0813 characterised by the conditions triggering a change of settings
• CPC Class Codes: H04L 67/34 involving the movement of software or configuration parameters network booting or remote initial program loading [RIPL] G06F9/4416
• CPC Class Codes: H04L 67/51 Discovery or management thereof, e.g. service location protocol [SLP] or web services

Abstract

Techniques are presented for managing a deployment pipeline using an inheritable and extensible source code template—generally referred to as a live pipeline template (LPT). As described, live pipeline templates may be used to manage deployment pipelines which, in turn, are used to launch, maintain, and update the services and systems used to host and provide computing services.

Claims

1. A computer-readable storage medium storing instructions, which, when executed on a processor, perform an operation for evaluating a deployment pipeline for at least one of testing and updating a production computing service, the operation comprising:

generating an application definition to reflect a current operational state of the deployment pipeline, wherein the application definition is generated by invoking a plurality of analysis drivers and wherein each analysis driver inspects a configuration of a respective computing service of a plurality of computing services included in the deployment pipeline, as deployed to at least a first cloud computing region, wherein the plurality of computing services is used for at least one of testing and updating the production computing service;

evaluating the application definition using a set of one or more rules, wherein each rule specifies one or more conditions for configuration of the plurality of computing services included in the deployment pipeline; and

generating a report indicating which of the one or more rules are satisfied by the current operational state of the deployment pipeline and which of the one or more rules are not satisfied by the current operational state of the deployment pipeline.

2. The computer-readable storage medium of claim 1, wherein the operation further comprises:

determining a live pipeline template to associate with the deployment pipeline, wherein the live pipeline template comprises source code for one or more base pipeline templates.

3. The computer-readable storage medium of claim 1, wherein the operation further comprises:

for at least a first one of the rules which is not satisfied by the current operational state of the deployment pipeline, generating a suggested modification to the plurality of computing services included in the deployment pipeline needed to satisfy the first rule.

4. The computer-readable storage medium of claim 3, wherein the operation further comprises:

propagating the suggested modification to the plurality of computing services.

5. The computer-readable storage medium of claim 1, wherein each of the plurality of analysis drivers includes at least one of a pipeline driver, a deployment driver, a host driver, a network driver, a security driver, an identity and access management (IAM) driver, a performance monitor driver, and an alarm driver.

6. The computer-readable storage medium of claim 1, wherein the application definition is formatted according to a structured interchange format.

7. The computer-readable storage medium of claim 1, wherein the deployment pipeline is a continuous deployment pipeline used to deploy changes to one or more applications corresponding to a user service in the production computing service hosted in the first cloud computing region.

20. The computer-readable storage medium of claim 1, wherein the set of one or more rules comprises at least one enterprise-wide rule applicable to multiple deployment pipelines in a global computing cloud and at least one service-type rule based on a particular service type of the deployment pipeline.

8. A system, comprising:

a processor; and

a memory storing one or more applications, which when executed on the processor, perform an operation for evaluating a deployment pipeline for at least one of testing and updating a production computing service, the operation comprising;

generating an application definition to reflect a current operational state of the deployment pipeline, wherein the application definition is generated by invoking a plurality of analysis drivers and wherein each analysis driver inspects a configuration of a respective computing service of a plurality of computing services included in the deployment pipeline, as deployed to at least a first cloud computing region, wherein the plurality of computing services is used for at least one of testing and updating the production computing service;

evaluating the application definition using a set of one or more rules, wherein each rule specifies one or more conditions for the configuration of the plurality of computing services included in the deployment pipeline; and

generating a report indicating which of the one or more rules are satisfied by the current operational state of the deployment pipeline and which of the one or more rules are not satisfied by the current operational state of the deployment pipeline.

9. The system of claim 8, wherein the operation further comprises:

determining a live pipeline template to associate with the deployment pipeline, wherein the live pipeline template comprises source code for one or more base pipeline templates.

10. The system of claim 8, wherein the operation further comprises:

for at least a first one of the rules which is not satisfied by the current operational state of the deployment pipeline, generating a suggested modification to the plurality of computing services included in the deployment pipeline needed to satisfy the first rule.

11. The system of claim 10, wherein the operation further comprises:

propagating the suggested modification to the plurality of computing services.

12. The system of claim 8, wherein each of the plurality of analysis drivers include at least one of a pipeline driver, a deployment driver, a host driver, a network driver, a security driver, an identity and access management (IAM) driver, a performance monitor driver, and an alarm driver.

13. The system of claim 8, wherein the application definition is formatted according to a structured interchange format.

14. The system of claim 8, wherein the deployment pipeline is a continuous deployment pipeline used to deploy changes to one or more applications corresponding to a user service in the production computing service hosted in the first cloud computing region.

15. A computer-implemented method for evaluating a deployment pipeline for at least one of testing and updating a production computing service, the method comprising:

generating an application definition to reflect a current operational state of the deployment pipeline, wherein the application definition is generated by invoking a plurality of analysis drivers and wherein each analysis driver inspects a configuration of a respective computing service of a plurality of computing services included in the deployment pipeline, as deployed to at least a first cloud computing region, wherein the plurality of computing services is used for at least one of testing and updating the production computing service;

evaluating the application definition using a set of one or more rules, wherein each rule specifies one or more conditions for the configuration of the plurality of computing services included in the deployment pipeline; and

generating a report indicating which of the one or more rules are satisfied by the current operational state of the deployment pipeline and which of the one or more rules are not satisfied by the current operational state of the deployment pipeline.

16. The method of claim 15, further comprising:

determining a live pipeline template to associate with the deployment pipeline, wherein the live pipeline template comprises source code for one or more base pipeline templates.

17. The method of claim 15, further comprising:

for at least a first one of the rules which is not satisfied by the current operational state of the deployment pipeline, generating a suggested modification to the plurality of computing services included in the deployment pipeline needed to satisfy the first rule.

18. The method of claim 15, wherein the application definition is formatted according to a structured interchange format.

19. The method of claim 15, wherein the deployment pipeline is a continuous deployment pipeline used to deploy changes to one or more applications corresponding to a user service in the production computing service hosted in the first cloud computing region.