# US 2019/0317869 A1 · Intelligent failover migration across multiple high availability stacks based on quality of prior failover migrations > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0317869 A1 - Document ID: US20190317869A1 - Status: Published application - Kind: A1 - Application number: 15/952,765 - Filed: 2018-04-13 - Published: 2019-10-17 - Earliest claimed: 2018-04-13 - Assignees: International Business Machines Corporation - Applicants: International Business Machines Corporation - Inventors: Jagadesh Selvaraj; Pramod Vadayadiyil Raveendran; Narasimhan B. Rajagopal; Sajith Kizhakke Veedu; Kuntal Dey - Web page: https://patentgrep.com/patent/US20190317869A1 ## CPC - G06F 11/203: {using migration} - G06F 11/2041: {with more than one idle spare processing component} - G06F 11/3409: {for performance assessment} - G06F 2201/82: Solving problems relating to consistency - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract A computer-implemented method includes: monitoring, by a computing device, failover data from one or more high availability stacks, wherein the failover data includes data associated with prior failovers associated with the one or more high availability stacks; scoring, by the computing device, a plurality of prior failovers identified in the failover data; generating, by the computing device, a failover instruction for implementing a failover based on the scoring; and causing, by the computing device, and based on the failover instruction, an application to migrate from a target cluster to a destination cluster. ## Claims ### Claim 1 A computer-implemented method comprising: monitoring, by a computing device, failover data from one or more high availability stacks, wherein the failover data includes data associated with prior failovers associated with the one or more high availability stacks; scoring, by the computing device, a plurality of prior failovers identified in the failover data; generating, by the computing device, a failover instruction for implementing a failover based on the scoring; and causing, by the computing device, and based on the failover instruction, an application to migrate from a target cluster to a destination cluster. ### Claim 2 (depends on 1) The method of claim 1, further comprising detecting a failover trigger, wherein the generating the failover instruction is based on the detecting the failover trigger. ### Claim 3 (depends on 1) The method of claim 1, wherein the scoring of each of the plurality of prior failovers includes generating a record identifying a corresponding score of the prior failover. ### Claim 4 (depends on 3) The method of claim 3, wherein the record identifies attributes of the prior failover. ### Claim 5 (depends on 4) The method of claim 4, wherein the attributes include at least one selected from the group consisting of: downtime; migration time; reliability; resource cost; performance; hardware and software configuration; network location; and physical location. ### Claim 6 (depends on 1) The method of claim 1, wherein the scoring each of the plurality of failovers includes scoring a set of attributes associated with each of the plurality of failovers. ### Claim 7 (depends on 6) The method of claim 6, wherein the generating the failover instruction includes selecting a destination application server cluster having attributes with the highest score. ### Claim 8 (depends on 1) The method of claim 1, wherein the failover data includes data relating to the implemented failover after outputting the failover instruction, wherein the failover instruction is a first failover instruction, the method further comprising: scoring the implemented failover; and generating a second failover instruction for implementing another failover based on the scoring the implemented failover. ### Claim 9 (depends on 1) The method of claim 1, further comprising generating a report indicating the failover instruction; wherein the report provides a recommendation to migrate a failed application server cluster to a destination application server cluster having an optimal set of attributes. ### Claim 10 (depends on 1) The method of claim 1, wherein a service provider at least one of creates, maintains, deploys and supports the computing device. ### Claim 11 (depends on 1) The method of claim 1, wherein the monitoring, the scoring, the generating, and the outputting are provided by a service provider on a subscription, advertising, and/or fee basis. ### Claim 12 (depends on 1) The method of claim 1, wherein the computing device includes software provided as a service in a cloud environment. ### Claim 13 (depends on 1) The method of claim 1, further comprising deploying a system for optimizing failovers, comprising providing a computer infrastructure operable to perform the monitoring, the scoring, the generating, and the outputting. ### Claim 14 A computer program product for optimizing failovers, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computing device to cause the computing device to: generate a respective plurality of scores for a plurality of prior failovers within one or more high availability stacks; detect a failover trigger for failing over an application from a target application server cluster to one of a plurality of destination application server clusters; select a particular destination application server cluster of the plurality of destination application server clusters based on the respective plurality of scores and the detecting the failover trigger; generate a failover instruction that causes the application to migrate from the target application server to the selected particular destination application server cluster. ### Claim 15 (depends on 14) The computer program product of claim 14, wherein the selected particular destination application server cluster includes attributes associated with a highest score of the respective plurality of scores. ### Claim 16 (depends on 15) The computer program product of claim 15, wherein the attributes include at least one selected from the group consisting of: hardware and software configuration; network location; and physical location. ### Claim 17 (depends on 14) The computer program product of claim 14, wherein the selected destination application server cluster is a virtual or physical cluster. ### Claim 18 (depends on 14) The computer program product of claim 14, wherein the failover trigger comprises at least one selected from the group consisting of: a manual instruction, a time-based trigger; a performance-based trigger; and an event-based trigger. ### Claim 19 A system comprising: a CPU, a computer readable memory and a computer readable storage medium associated with a computing device; program instructions to identify attributes of a failover; program instructions to track migration time of the failover; program instructions to track performance of applications and services after migration of the failover; program instructions to track uptime of migrated applications and services; program instructions to score the failover based on the migration time, the performance, and the uptime, wherein the score indicates a quality of the failover; program instructions to generate a record that associates the attributes of the failover with the score; program instructions to generate a failover instruction for a future failover based on the score and one or more other scores associated with other failovers; and program instructions to output the failover instruction to implement the future failover by causing an application to migrate from a target application server to a destination application server cluster, wherein the program instructions are stored on the computer readable storage medium for execution by the CPU via the computer readable memory. ### Claim 20 (depends on 19) The system of claim 19, wherein the score is further generated based on external data and weightings.