Best outcome AIOps modeling with data confidence fabrics

US12045739B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-12045739-B2
Application numberUS-202017134898-A
CountryUS
Kind codeB2
Filing dateDec 28, 2020
Priority dateDec 28, 2020
Publication dateJul 23, 2024
Grant dateJul 23, 2024

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  1. Title

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  2. Abstract

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  3. Assignees and inventors

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

One example method includes receiving a transaction at a digital twin that incorporates all transactions that have occurred at a site from which the transaction was received, and wherein the digital twin was created based in part on a data confidence fabric ledger, entering the transaction in the data confidence fabric ledger at the digital twin, receiving another transaction at the digital twin, wherein the another transaction has caused a problem to occur, entering the another transaction in the data confidence fabric ledger, replaying any transactions that have occurred in a defined time window that includes the another transaction, based on the replaying, identifying a state of a system where the problem occurred, and a time when the problem occurred, and determining a resolution to the problem.

First claim

Opening claim text (preview).

What is claimed is: 1. A method, comprising: receiving a transaction at a digital twin that incorporates all transactions that have occurred at a site from which the transaction was received, and wherein the digital twin was created based in part on a data confidence fabric ledger; entering the transaction in the data confidence fabric ledger at the digital twin; receiving another transaction at the digital twin, wherein the another transaction has caused a problem to occur; entering the another transaction in the data confidence fabric ledger; replaying any transactions that have occurred in a defined time window that includes the another transaction; based on the replaying, identifying a state of a system where the problem occurred, and a time when the problem occurred; and determining a resolution to the problem, wherein the resolution relates to a problem that has not actually occurred at the site by the time the another transaction has been entered into the data confidence fabric ledger, and the resolution to the problem is made available to the site. 2. The method as recited in claim 1 , wherein the transaction and the another transaction are received from a vendor site, and the problem concerns hardware and/or software sourced by a vendor associated with the vendor site, and at least part of the data conference fabric ledger is made accessible to the vendor. 3. The method as recited in claim 1 , wherein the transaction and the another transaction are received from a data management site, and the problem concerns a data management operation implemented at the data management site. 4. The method as recited in claim 1 , wherein the digital twin assigns a confidence level to the resolution, and the confidence level indicates a confidence as to how the site is expected to respond when the resolution is implemented at the site, and the resolution was selected for implementation based on a comparison of the confidence level of the resolution with a respective confidence level of one or more other possible solutions. 5. The method as recited in claim 1 , wherein the another transaction relates to a problem that has actually occurred at the site by the time the another transaction has been entered into the data confidence fabric ledger. 6. The method as recited in claim 1 , wherein the another transaction is received from an AIOps platform hosted at the site. 7. The method as recited in claim 1 , wherein the resolution to the problem is made available to an AIOPs platform hosted at the site. 8. The method as recited in claim 1 , wherein the site comprises a vendor site. 9. The method as recited in claim 1 , wherein at least part of the method is instantiated in response to a request by an AIOps platform. 10. A non-transitory storage medium having stored therein instructions that are executable by one or more hardware processors to perform operations comprising: receiving a transaction at a digital twin that incorporates all transactions that have occurred at a site from which the transaction was received, and wherein the digital twin was created based in part on a data confidence fabric ledger; entering the transaction in the data confidence fabric ledger at the digital twin; receiving another transaction at the digital twin, wherein the another transaction has caused a problem to occur; entering the another transaction in the data confidence fabric ledger; replaying any transactions that have occurred in a defined time window that includes the another transaction; based on the replaying, identifying a state of a system where the problem occurred, and a time when the problem occurred; and determining a resolution to the problem, wherein the resolution relates to a problem that has not actually occurred at the site by the time the another transaction has been entered into the data confidence fabric ledger, and the resolution to the problem is made available to the site. 11. The non-transitory storage medium as recited in claim 10 , wherein the transaction and the another transaction are received from a vendor site, and the problem concerns hardware and/or software sourced by a vendor associated with the vendor site, and at least part of the data conference fabric ledger is made accessible to the vendor. 12. The non-transitory storage medium as recited in claim 10 , wherein the transaction and the another transaction are received from a data management site, and the problem concerns a data management operation implemented at the data management site. 13. The non-transitory storage medium as recited in claim 10 , wherein the digital twin assigns a confidence level to the resolution, and the confidence level indicates a confidence as to how the site is expected to respond when the resolution is implemented at the site, and the resolution was selected for implementation based on a comparison of the confidence level of the resolution with a respective confidence level of one or more other possible solutions. 14. The non-transitory storage medium as recited in claim 10 , wherein the another transaction relates to a problem that has actually occurred at the site by the time the another transaction has been entered into the data confidence fabric ledger. 15. The non-transitory storage medium as recited in claim 10 , wherein the another transaction is received from an AIOps platform hosted at the site. 16. The non-transitory storage medium as recited in claim 10 , wherein the resolution to the problem is made available to an AIOPs platform hosted at the site. 17. The non-transitory storage medium as recited in claim 10 , wherein the site comprises a vendor site. 18. The non-transitory storage medium as recited in claim 10 , wherein at least part of the non-transitory storage medium is instantiated in response to a request by an AIOps platform.

Assignees

Inventors

Classifications

  • Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor · CPC title

  • using machine learning or artificial intelligence · CPC title

  • Point-in-time backing up or restoration of persistent data · CPC title

  • Using snapshots, i.e. a logical point-in-time copy of the data · CPC title

  • Debugging of software · CPC title

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What does patent US12045739B2 cover?
One example method includes receiving a transaction at a digital twin that incorporates all transactions that have occurred at a site from which the transaction was received, and wherein the digital twin was created based in part on a data confidence fabric ledger, entering the transaction in the data confidence fabric ledger at the digital twin, receiving another transaction at the digital twi…
Who is the assignee on this patent?
Emc Ip Holding Co Llc
What technology area does this patent fall under?
Primary CPC classification G06N5/04. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Jul 23 2024 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 12 related publications on this page (citations in our corpus or others sharing the same primary CPC).