Stochastic risk scoring with counterfactual analysis for storage capacity
One example method includes accessing a dataset, selecting a list of parameters of the dataset, each of the parameters being selected based on a determination that the parameter is affecting a size of the dataset and/or affecting an amount of data storage space consumed by the dataset, performing a counterfactual analysis using the parameters, and using results of the counterfactual analysis to generate a recommendation that identifies one or more data protection actions which influence utilization of the data storage space, and modifying utilization of the data storage space by implementing one of the data protection actions.
1 . A method for managing utilization of a data storage space so as to reduce a risk of capacity exhaustion for the data storage space, the method comprising:
accessing a dataset;
selecting a list of parameters of the dataset, each parameter in the list of parameters related to a growth of the dataset, wherein one of the parameters of the list of parameters is related to data deduplication operations;
generating a directed acyclic graph that identifies a causal relationship among the parameters in the list of parameters of the dataset based on a storage utilization and a deduplication ratio of the dataset;
performing a counterfactual analysis based on the directed acyclic graph identifying the causal relationship among the parameters, which include a total_post_compression_used amount, a daily precompression, a workload pattern, a snapshot deletion, a data movement, a post_compression_used after space reclamation, and a space reclamation after garbage collection;
using results of the counterfactual analysis to generate a recommendation that identifies one or more data protection actions which influence utilization of a data storage space;
displaying the recommendation that identifies the one or more data protection actions as one or more user interface elements on a graphical user interface; and
modifying utilization of the data storage space by implementing one of the data protection actions, wherein implementing the one data protection action includes performing at least one of:
reconfiguring an existing backup policy,
changing an existing backup schedule,
load balancing current workloads,
deleting existing dataset snapshots that are determined to be unneeded,
performing a garbage collection process to delete expired data, or
expanding existing storage capacity.
2 . The method as recited in claim 1 , wherein the dataset is a backup dataset.
3 . The method as recited in claim 1 , further comprising identifying, for one of the list of parameters, a causal relationship between the one parameter and the others in the list of parameters.
4 . The method as recited in claim 1 , further comprising identifying, for one of the parameters, a causal relationship between the one parameter and an amount of storage capacity consumed by the dataset.
5 . The method as recited in claim 1 , further comprising identifying, for one of the parameters, a causal relationship between the one parameter and the size of the dataset.
6 . The method as recited in claim 1 , wherein the data protection action is implemented before any additional data is added to the dataset.
7 . The method as recited in claim 1 , wherein the data protection action is implemented on a temporary basis as part of performance of a what-if analysis.
8 . The method as recited in claim 1 , wherein the recommendation is additionally based on a risk score that indicates an extent to which there is a risk that the data storage space will be exhausted by a particular point in time.
9 . The method as recited in claim 1 , wherein the implemented data protection action affects either a size of the dataset, or an amount of available storage space.
10 . A non-transitory computer readable storage medium having stored therein instructions that are executable by one or more hardware processors to perform operations for managing utilization of a data storage space, the operations comprising:
accessing a dataset;
selecting a list of parameters of the dataset, each parameter in the list of parameters related to a growth of the dataset, wherein one of the parameters of the list of parameters is related to data deduplication operations;
generating a directed acyclic graph that identifies a causal relationship among the parameters in the list of parameters of the dataset based on a storage utilization and a deduplication ratio of the dataset;
performing a counterfactual analysis based on the directed acyclic graph identifying the causal relationship among the parameters, which include a total_post_compression_used amount, a daily precompression, a workload pattern, a snapshot deletion, a data movement, a post_compression_used after space reclamation, and a space reclamation after garbage collection;
using results of the counterfactual analysis to generate a recommendation that identifies one or more data protection actions which influence utilization of a data storage space;
displaying the recommendation that identifies the one or more data protection actions as one or more user interface elements on a graphical user interface; and
modifying utilization of the data storage space by implementing one of the data protection actions, wherein implementing the one data protection action includes performing at least one of:
reconfiguring an existing backup policy,
changing an existing backup schedule,
load balancing current workloads,
deleting existing dataset snapshots that are determined to be unneeded,
performing a garbage collection process to delete expired data, or
expanding existing storage capacity.
11 . The non-transitory computer readable storage medium as recited in claim 10 , wherein the dataset is a backup dataset.
12 . The non-transitory computer readable storage medium as recited in claim 10 , wherein the operations further comprise identifying, for one of the list of parameters, a causal relationship between the one parameter and the others in the list of parameters.
13 . The non-transitory computer readable storage medium as recited in claim 10 , wherein the operations further comprise identifying, for one of the parameters, a causal relationship between the one parameter and an amount of storage capacity consumed by the dataset.
14 . The non-transitory computer readable storage medium as recited in claim 10 , wherein the operations further comprise identifying, for one of the parameters, a causal relationship between the one parameter and the size of the dataset.
15 . The non-transitory computer readable storage medium as recited in claim 10 , wherein the data protection action is implemented before any additional data is added to the dataset.
16 . The non-transitory computer readable storage medium as recited in claim 10 , wherein the data protection action is implemented on a temporary basis as part of performance of a what-if analysis.
17 . The non-transitory computer readable storage medium as recited in claim 10 , wherein the recommendation is additionally based on a risk score that indicates an extent to which there is a risk that the data storage space will be exhausted by a particular point in time.
18 . The non-transitory computer readable storage medium as recited in claim 10 , wherein the implemented data protection action affects either a size of the dataset, or an amount of available storage space.