Methods and systems for enhanced fault detection of a component of a computing node through peer-based assessments

1 . A method for enhanced fault detection of a component of a computing node, the method comprising:

executing a component health assessment of a plurality of components of a target computing node based on identifying the target computing node as having an unhealthy state of health, wherein executing the component health assessment of the plurality of components includes:

identifying a healthy computing node having a healthy state of health;

establishing a plurality of distinct pairs of components, each distinct pair of components of the plurality of distinct pairs of components includes one component of the target computing node and one component of the healthy computing node; and

executing bi-directional testing by each of the plurality of distinct pairs of components;

evaluating health assessment data generated based on the execution of the bi-directional testing, wherein evaluating the health assessment data includes:

identifying a subset of pairs of components of the plurality of distinct pairs of components that fail to satisfy one or more performance benchmarks; and

identifying within the subset of pairs of components, the one or more components of the target computing node appearing in more than one pair of components of the subset of pairs of components; and

classifying as faulty one or more components of the plurality of components of the target computing node based on the evaluation of the health assessment data, wherein the classification of faulty is based at least on the one or more components of the target computing node appearing in the more than one pair of components of the subset of pairs of components.

2 . The method according to claim 1 , wherein evaluating the health assessment data includes:

comparing a performance metric of each pair of components of the plurality of distinct pairs of components to a performance benchmark; and

identifying any component of the target computing node that fails to satisfy the performance benchmark across multiple pairs of components of the plurality of distinct pairs of components.

3 . The method according to claim 2 , wherein the classification of faulty is based at least on identifying the one or more components of the target computing node in the multiple pairs of components of the plurality of distinct pairs of components.

4 . The method according to claim 1 , wherein establishing the plurality of distinct pairs of components includes computing a Cartesian product between a set of components of the target computing node and a set of components of the healthy computing node.

5 . The method according to claim 1 , wherein the plurality of components of the target computing node includes a plurality of distinct component types including a plurality of processing components and a plurality of networking components.

6 . The method according to claim 1 , further comprising:

configuring the component health assessment based on identifying a suspected faulty component type of the plurality of distinct component types of the target computing node, wherein configuring the health assessment includes selecting one or more node component health tests according to a component type of the suspected faulty component type.

7 . The method according to claim 1 , wherein executing the bi-directional testing includes:

concurrently executing the bi-directional testing by at least a subset of pairs of components of the plurality of distinct pairs of components, each pair of the subset of pairs including a unique combination of components that does share a component that is common with any other pair of the subset of pairs.

8 . The method according to claim 1 , further comprising:

identifying from a repair matrix one or more remedial actions for repairing the target computing node based on the classification of faulty of the one or more components, wherein:

the repair matrix comprises a data structure that maps each of a plurality of distinct faults to one or more remedial actions, and

identifying the one or more remedial actions includes performing a search of the repair matrix using data associated with the classification of faulty.

9 . The method according to claim 1 , further comprising:

generating an assessment composition based on the health assessment data, wherein the assessment composition comprises a graphical illustration listing the plurality of distinct pairs of components with an identification within the listing of the one or more components of the plurality of components that fail to satisfy one or more tests of the node component health assessment.

10 . The method according to claim 1 , wherein:

the healthy computing node is selected from a peer group of computing nodes associated with the target computing node; and

the peer group of computing nodes includes a plurality of computing nodes having common hardware attributes as the target computing node.

11 . A system for enhanced fault detection of a component of a computing node, the system comprising: a computing node configured to execute a component health assessment of a plurality of components of a target computing node based on identifying the target computing node as having an unhealthy state of health, wherein executing the component health assessment of the plurality of components includes:

identifying a healthy computing node having a healthy state of health;

establishing a plurality of distinct pairs of components, each distinct pair of components of the plurality of distinct pairs of components includes one component of the target computing node and one component of the healthy computing node; and

executing bi-directional testing by each of the plurality of distinct pairs of components;

wherein the health assessment executed by the computing node further comprises: evaluating health assessment data generated based on the execution of the bi-directional testing, wherein evaluating the health assessment data includes:

identifying a subset of pairs of components of the plurality of distinct pairs of components that fail to satisfy one or more performance benchmarks; and identifying within the subset of pairs of components, the one or more components of the target computing node appearing in more than one pair of components of the subset of pairs of components; and

and fault characterization, which classifies one or more components of the plurality of components of the target computing node based on the evaluation of the health assessment data, wherein the classification of faulty is based at least on the one or more components of the target computing node appearing in the more than one pair of components of the subset of pairs of components.

12 . The system according to claim 11 , wherein evaluating the health assessment data includes:

comparing a performance metric of each pair of components of the plurality of distinct pairs of components to a performance benchmark; and

identifying any component of the target computing node that fails to satisfy the performance benchmark across multiple pairs of components of the plurality of distinct pairs of components.

13 . The system according to claim 11 , wherein executing the bi-directional testing includes:

concurrently executing the bi-directional testing by at least a subset of pairs of components of the plurality of distinct pairs of components, each pair of the subset of pairs including a unique combination of components that does share a component that is common with any other pair of the subset of pairs.

14 . A computer-program product comprising a non-transitory machine-readable storage medium storing computer instructions that, when executed by one or more processors, perform operations comprising:

executing a component health assessment of a plurality of components of a target computing node based on identifying the target computing node as having an unhealthy state of health, wherein executing the component health assessment of the plurality of components includes:

identifying a healthy computing node having a healthy state of health;

establishing a plurality of distinct pairs of components, each distinct pair of components of the plurality of distinct pairs of components includes one component of the target computing node and one component of the healthy computing node; and

executing bi-directional testing by each of the plurality of distinct pairs of components;

evaluating health assessment data generated based on the execution of the bi-directional testing, wherein evaluating the health assessment data includes:

identifying a subset of pairs of components of the plurality of distinct pairs of components that fail to satisfy one or more performance benchmarks; and

identifying within the subset of pairs of components, the one or more components of the target computing node appearing in more than one pair of components of the subset of pairs of components; and

classifying as faulty one or more components of the plurality of components of the target computing node based on the evaluation of the health assessment data, wherein the classification of faulty is based at least on the one or more components of the target computing node appearing in the more than one pair of components of the subset of pairs of components.

15 . The computer-program product according to claim 14 , wherein evaluating the health assessment data includes:

comparing a performance metric of each pair of components of the plurality of distinct pairs of components to a performance benchmark; and

identifying any component of the target computing node that fails to satisfy the performance benchmark across multiple pairs of components of the plurality of distinct pairs of components.

16 . The computer-program product according to claim 14 , wherein executing the bi-directional testing includes:

concurrently executing the bi-directional testing by at least a subset of pairs of components of the plurality of distinct pairs of components, each pair of the subset of pairs including a unique combination of components that does share a component that is common with any other pair of the subset of pairs.

17 . A method for enhanced fault detection of a component of a computing node, the method comprising:

executing a component health assessment of a plurality of components of a target computing node based on identifying the target computing node as having an unhealthy state of health, wherein executing the component health assessment of the plurality of components includes:

identifying a healthy computing node having a healthy state of health;

establishing a plurality of distinct pairs of components, each distinct pair of components of the plurality of distinct pairs of components includes one component of the target computing node and one component of the healthy computing node, wherein establishing the plurality of distinct pairs of components includes computing a Cartesian product between a set of components of the target computing node and a set of components of the healthy computing node; and

executing bi-directional testing by each of the plurality of distinct pairs of components;

evaluating health assessment data generated based on the execution of the bi-directional testing; and

classifying as faulty one or more components of the plurality of components of the target computing node based on the evaluation of the health assessment data.

18 . The method according to claim 17 , wherein evaluating the health assessment data includes:

identifying a subset of pairs of components of the plurality of distinct pairs of components that fail to satisfy one or more performance benchmarks; and

identifying within the subset of pairs of components, the one or more components of the target computing node appearing in more than one pair of components of the subset of pairs of components.

19 . The method according to claim 18 , wherein the classification of faulty is based at least on the one or more components of the target computing node appearing in the more than one pair of components of the subset of pairs of components.