Dynamic three-dimensional map generation for computing environment
In a computing environment comprising a plurality of equipment racks wherein each equipment rack comprises one or more of compute, storage and network assets, the method captures an image of at least one equipment rack in the computing environment. The method identifies a known object in the image to determine physical characteristics of the equipment rack. The method receives, from a peer-to-peer network, positioning beacon signals respectively associated with at least a portion of the compute, storage and network assets in and around the equipment rack. The method determines a closest asset among the portion of the compute, storage and network assets for which positioning beacon signals are received. The method obtains data indicative of physical characteristics associated with the closest asset, obtains a model of the computing environment based on the obtained data, and then obtains a three-dimensional map of the computing environment based on the model.
1. A method, comprising:
in a computing environment comprising a plurality of equipment racks wherein each equipment rack comprises one or more of compute, storage and network assets, capturing an image of at least one equipment rack in the computing environment;
identifying a known object in the image to determine physical characteristics of the equipment rack;
receiving, from a peer-to-peer network, positioning beacon signals broadcasted by one or more signal emitters respectively associated with at least a portion of the compute, storage and network assets in and around the equipment rack;
determining a closest asset among the portion of the compute, storage and network assets for which positioning beacon signals are received;
obtaining data indicative of physical characteristics associated with the closest asset;
obtaining a model of the computing environment based on the obtained data; and
obtaining a three-dimensional map of the computing environment based on the model;
wherein the steps are performed via at least one processing device comprising a processor and a memory.
2. The method of claim 1 , further comprising determining, from the peer-to-peer network, one or more compute, storage and network assets in a proximity of the closest asset.
3. The method of claim 2 , further comprising determining relative coordinates for the one or more compute, storage and network assets in the proximity of the closest asset.
4. The method of claim 3 , further comprising obtaining data indicative of physical characteristics associated with the one or more compute, storage and network assets in the proximity of the closest asset.
5. The method of claim 4 , further comprising updating the model of the computing environment using the obtained data indicative of physical characteristics associated with the one or more compute, storage and network assets in the proximity of the closest asset.
6. The method of claim 5 , further comprising obtaining an updated three-dimensional map of the computing environment based on the updated model.
7. The method of claim 6 , further comprising repeating the model and three-dimensional map updating steps until each of the plurality of equipment racks and their corresponding compute, storage and network assets are rendered in the three-dimensional map of the computing environment.
8. The method of claim 1 , wherein the step of determining the closest asset among the portion of the compute, storage and network assets for which positioning beacon signals are received further comprises comparing received signal strength values for the received positioning beacon signals to determine the closest asset.
9. The method of claim 1 , wherein the peer-to-peer network is a gossip-based mesh network.
10. The method of claim 1 , wherein one or more of updating the model and the three-dimensional map are performed on a device that performs the capturing, identifying, receiving and determining steps.
11. The method of claim 1 , wherein one or more of updating the model and the three-dimensional map are performed remote from a device that performs the capturing, identifying, receiving and determining steps.
12. A system, comprising:
at least one processor, coupled to a memory, and configured to:
in a computing environment comprising a plurality of equipment racks wherein each equipment rack comprises one or more of compute, storage and network assets, capture an image of at least one equipment rack in the computing environment;
identify a known object in the image to determine physical characteristics of the equipment rack;
receive, from a peer-to-peer network, positioning beacon signals broadcasted by one or more signal emitters respectively associated with at least a portion of the compute, storage and network assets in and around the equipment rack;
determine a closest asset among the portion of the compute, storage and network assets for which positioning beacon signals are received;
obtain data indicative of physical characteristics associated with the closest asset;
obtain a model of the computing environment based on the obtained data; and
obtain a three-dimensional map of the computing environment based on the model.
13. The system of claim 12 , wherein the at least one processor and memory are further configured to determine, from the peer-to-peer network, one or more compute, storage and network assets in a proximity of the closest asset.
14. The system of claim 13 , wherein the at least one processor and memory are further configured to determine relative coordinates for the one or more compute, storage and network assets in the proximity of the closest asset.
15. The system of claim 14 , wherein the at least one processor and memory are further configured to obtain data indicative of physical characteristics associated with the one or more compute, storage and network assets in the proximity of the closest asset.
16. The system of claim 15 , wherein the at least one processor and memory are further configured to update the model of the computing environment using the obtained data indicative of physical characteristics associated with the one or more compute, storage and network assets in the proximity of the closest asset.
17. The system of claim 16 , wherein the at least one processor and memory are further configured to obtain an updated three-dimensional map of the computing environment based on the updated model.
18. The system of claim 17 , wherein the at least one processor and memory are further configured to repeat the model and three-dimensional map updating steps until each of the plurality of equipment racks and their corresponding compute, storage and network assets are rendered in the three-dimensional map of the computing environment.
19. An article of manufacture comprising a processor-readable storage medium having encoded therein executable code of one or more software programs, wherein the one or more software programs when executed by at least one processing device implement steps of:
in a computing environment comprising a plurality of equipment racks wherein each equipment rack comprises one or more of compute, storage and network assets, capturing an image of at least one equipment rack in the computing environment;
identifying a known object in the image to determine physical characteristics of the equipment rack;
receiving, from a peer-to-peer network, positioning beacon signals broadcasted by one or more signal emitters respectively associated with at least a portion of the compute, storage and network assets in and around the equipment rack;
determining a closest asset among the portion of the compute, storage and network assets for which positioning beacon signals are received;
obtaining data indicative of physical characteristics associated with the closest asset;
obtaining a model of the computing environment based on the obtained data; and
obtaining a three-dimensional map of the computing environment based on the model.
20. The article of claim 19 , wherein the peer-to-peer network is a gossip-based mesh network.