Progressive deployment and termination of canary instances for software analysis

Patent metadata

Field	Value
Publication number	US-2016119207-A1
Application number	US-201514981629-A
Country	US
Kind code	A1
Filing date	Dec 28, 2015
Priority date	Jun 25, 2013
Publication date	Apr 28, 2016
Grant date	—

Abstract

A data processing method, comprising: using computing apparatus, causing instantiating a plurality of baseline application instances that are running a first version of software, and one or more canary application instances that are running a second version of the software; using computing apparatus including a load balancer, causing selectively routing a first proportion of incoming requests to the baseline instances, and routing a second proportion of the incoming requests to the canary instances; monitoring the plurality of canary instances to collect performance data for performance metrics; determining that the performance data indicates a negative performance issue, and in response thereto: using computing apparatus, automatically updating the first proportion to be larger and updating the second proportion to be smaller, and then reconfiguring the load balancer based upon the first proportion and the second proportion; terminating one or more of the canary application instances.

First claim

We claim:

1 . A computer-implemented method, comprising:
deploying a plurality of baseline application instances that run a first version of software application code and one or more canary application instances that run a second version of the software application code; routing a first proportion of incoming requests to the plurality of baseline instances and a second proportion of the incoming requests to the one or more canary instances; monitoring the one or more canary application instances relative to a plurality of performance metrics; determining whether the plurality of performance metrics indicates a negative performance issue; and modifying the first portion of incoming requests and the second portion of incoming requests according to whether the plurality of performance metrics indicates a negative performance issue.

2 . The computer-implemented method of claim 1 , wherein the plurality of performance metrics does not indicate a negative performance issue, modifying the first portion of incoming requests comprises decreasing the size of the first portion, and modifying the second portion of incoming requests comprises increasing the size of the second portion.

3 . The computer-implemented method of claim 2 , further comprising deploying one or more additional canary application instances.

4 . The computer-implemented method of claim 3 , further comprising terminating one or more baseline application instances included in the plurality of baseline application instance.

5 . The computer-implemented method of claim 1 , wherein the plurality of performance metrics indicates a negative performance issue, and modifying the first portion of incoming requests comprises increasing the size of the first portion, and modifying the second portion of incoming requests comprises decreasing the size of the second portion.

6 . The computer-implemented method of claim 5 , further comprising terminating at least one of the one or more canary application instances.

7 . The computer-implemented method of claim 1 , wherein determining whether the plurality of performance metrics indicates a negative performance issue comprises evaluating at least one of (i) a threshold amount of variance, (ii) one or more error messages associated with the plurality of performance metrics, and (iii) how much data has been collected for the plurality of performance metrics.

8 . The computer-implemented method of claim 1 , wherein the plurality of baseline application instances are instantiated in a first cluster, and the one or more canary application instances are instantiated in a second cluster.

9 . The computer-implemented method of claim 8 , wherein a first cloud service provider instantiates the plurality of baseline application instance, and a second cloud service provider different than the first cloud service provider instantiates the one or more canary application instances.

10 . A non-transitory computer-readable medium including instructions that, when executed by a processor, cause the processor to perform the steps of:
deploying a plurality of baseline application instances that run a first version of software application code and one or more canary application instances that run a second version of the software application code; routing a first proportion of incoming requests to the plurality of baseline instances and a second proportion of the incoming requests to the one or more canary instances; monitoring the one or more canary application instances relative to a plurality of performance metrics; and modifying the first portion of incoming requests and the second portion of incoming requests according to whether the plurality of performance metrics indicates a negative performance issue.

11 . The non-transitory computer-readable medium of claim 10 , wherein the plurality of performance metrics does not indicate a negative performance issue, and modifying comprises decreasing the size of the first portion and increasing the size of the second portion.

12 . The non-transitory computer-readable medium of claim 11 , further comprising deploying one or more additional canary application instances.

13 . The non-transitory computer-readable medium of claim 12 , further comprising terminating one or more baseline application instances included in the plurality of baseline application instance.

14 . The non-transitory computer-readable medium of claim 10 , wherein the plurality of performance metrics indicates a negative performance issue, and modifying comprises increasing the size of the first portion and decreasing the size of the second portion.

15 . The non-transitory computer-readable medium of claim 14 , further comprising terminating at least one of the one or more canary application instances.

16 . The non-transitory computer-readable medium of claim 10 , further comprising determining whether the plurality of performance metrics indicates a negative performance issue by evaluating a threshold amount of variance, one or more error messages associated with the plurality of performance metrics, or how much data has been collected for the plurality of performance metrics.

17 . The non-transitory computer-readable medium of claim 10 , wherein the plurality of baseline application instances are instantiated in a first cluster, and the one or more canary application instances are instantiated in a second cluster.

18 . A computer system, comprising:
a memory that stores a canary analysis engine; and a processor that is coupled to the memory and, when executing the canary analysis engine, is configured to:
monitor one or more canary application instances relative to a plurality of performance metrics, and
cause a first portion of incoming requests routed to a plurality of baseline application instances to be modified and a second portion of incoming requests routed to the one or more canary application instances to be modified according to whether the plurality of performance metrics indicates a negative performance issue.

19 . The computer system of claim 18 , wherein the plurality of performance metrics does not indicate a negative performance issue, and causing comprises causing the size of the first portion to be decreased and causing the size of the second portion to be increased.

20 . The computer system of claim 18 , wherein the plurality of performance metrics indicates a negative performance issue, and causing comprises causing the size of the first portion to be increased and causing the size of the second portion to be decreased.

Assignees

• Netflix Inc

Inventors

• Tseitlin Ariel
• Sondow Joe

Classifications

• H04L43/08 Primary

  Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters · CPC title

• H04L41/5025 Primary

  by proactively reacting to service quality change, e.g. by reconfiguration after service quality degradation or upgrade · CPC title

• H04L41/5096

  wherein the managed service relates to distributed or central networked applications · CPC title

• H04L67/10

  in which an application is distributed across nodes in the network (software deployment G06F8/60; multiprogramming arrangements G06F9/46) · CPC title

• H04L67/1004

  Server selection for load balancing · CPC title