OPTIMIZING NETWORK TRANSACTIONS FOR DATABASES HOSTED ON A PUBLIC CLOUD
Configuration management e.g., configuration validation and remediation (when necessary) of entities in a collective of databases and/or other machines or devices can be burdensome when vendor/cloud provider tools are used to manage the entities due to lack of control over the management. Rather than rely on vendor/cloud provider tools, instead configuration management is offloaded to, e.g., a local API and/or local machine, where configuration deviation detection from an expected configuration is locally determined and remediation needs may be prioritized so higher-priority collective entities are remediated first and other entities deferred. Local processing reduces burdens associated with entity remediation, such as in a cloud-hosted environment having many burdens associated with accessing cloud data and/or databases.
1 . A computing system for localizing transactions between a private network and a public cloud hosting a collection of databases, the computing system comprising at least one processor and a memory coupled to the at least one processor and storing instructions that, when executed by the at least one processor, cause the computing system to:
access a data store on the private network storing database configurations;
determine a first configuration in the data store associated with a first database in the collection;
locally check for a first deviation of the first configuration from a first expected configuration;
remotely log with the public cloud a first result of the check for the first deviation;
locally request a first configuration correction from the public cloud for the first deviation;
determine a first corrective action corresponding to the first configuration correction;
determine an operation to apply to a second database in the collection;
prioritize the first corrective action and the operation to determine a priority action; and
locally perform the priority action.
2 . The computing system of claim 1 , the instructions further including instructions to:
determine a second configuration in the data store associated with the second database in the collection;
locally check for a second deviation of the second configuration from a second expected configuration;
remotely log with the public cloud a second result of the check for the second deviation;
locally request a second configuration correction from the public cloud for the second deviation; and
determine the operation as a second corrective action corresponding to the second configuration correction.
3 . The computing system of claim 1 , wherein the first corrective action is the first configuration correction.
4 . The computing system of claim 1 , wherein instructions for localizing transactions includes instructions to cause the computing system to:
perform a heartbeat transaction associated with the first database on the private network.
5 . The computing system of claim 1 , wherein instructions for localizing transactions includes instructions to cause the computing system to:
perform in a collection of cloud-based databases
6 . The computer program of claim 1 , wherein the instructions for the locally check for the first deviation further comprising instructions to apply artificial-intelligence based analytics to at least the first configuration to at least identify the first deviation.
7 . The computing system of claim 1 , wherein instructions for localizing transactions includes instructions to cause the computing system to:
determine the first corrective action is the priority action; and
defer the operation.
8 . A database implemented method for localizing transactions between a private network and a public cloud hosting a collection of databases, comprising:
access a data store on the private network storing database configurations;
determine a first configuration in the data store associated with a first database in the collection;
locally check for a first deviation of the first configuration from a first expected configuration;
remotely log with the public cloud a first result of the check for the first deviation;
locally request a first configuration correction from the public cloud for the first deviation;
determine a first corrective action corresponding to the first configuration correction;
determine an operation to apply to a second database in the collection;
prioritize the first corrective action and the operation to determine a priority action; and
locally perform the priority action.
9 . The method of claim 8 , further comprising:
determine a second configuration in the data store associated with the second database in the collection;
locally check for a second deviation of the second configuration from a second expected configuration;
remotely log with the public cloud a second result of the check for the second deviation;
locally request a second configuration correction from the public cloud for the second deviation; and
determine the operation as a second corrective action corresponding to the second configuration correction.
10 . The method of claim 8 , wherein the first corrective action is the first configuration correction.
11 . The method of claim 8 , further comprising:
perform a heartbeat transaction associated with the first database on the private network.
12 . The method of claim 8 , further comprising:
perform in a collection of cloud-based databases
13 . The method of claim 8 , further comprising:
apply artificial-intelligence based analytics to at least the first configuration to at least identify the first deviation.
14 . The method of claim 8 , further comprising:
determine the first corrective action is the priority action; and
defer the operation.
15 . A computer program for localizing transactions between a private network and a public cloud hosting a collection of databases, the computing program including instructions to:
access a data store on the private network storing database configurations;
determine a first configuration in the data store associated with a first database in the collection;
locally check for a first deviation of the first configuration from a first expected configuration;
remotely log with the public cloud a first result of the check for the first deviation;
locally request a first configuration correction from the public cloud for the first deviation;
determine a first corrective action corresponding to the first configuration correction;
determine an operation to apply to a second database in the collection;
prioritize the first corrective action and the operation to determine a priority action; and
locally perform the priority action.
16 . The computing program of claim 15 , the instructions further including instructions to:
determine a second configuration in the data store associated with the second database in the collection;
locally check for a second deviation of the second configuration from a second expected configuration;
remotely log with the public cloud a second result of the check for the second deviation;
locally request a second configuration correction from the public cloud for the second deviation; and
determine the operation as a second corrective action corresponding to the second configuration correction.
17 . The computing program of claim 15 , the instructions further including instructions to:
perform a heartbeat transaction associated with the first database on the private network.
18 . The computing program of claim 15 , the instructions further including instructions to:
perform in a collection of cloud-based databases
19 . The computing program of claim 15 , the instructions further including instructions to:
apply artificial-intelligence based analytics to at least the first configuration to at least identify the first deviation.
20 . The computing program of claim 15 , the instructions further including instructions to:
determine the first corrective action is the priority action; and
defer the operation.