Autonomous data protection
Embodiments of the present disclosure relate to autonomous data protection. An input/output (I/O) stream can be received for a storage device. One or more anomalies corresponding to the I/O stream can be identified. At least one of the one or more anomalies can be offloaded anomalies to a remote storage based on a capacity of memory allocated to store at least one snapshot of the storage device that include at least one of the one or more anomalies.
1. An apparatus comprising a memory and at least one processor configured to:
receive an input/output (IO) stream for a storage device;
identify one or more events having a change rate greater than a threshold and corresponding to the IO stream; and
offload at least one of the one or more events to a remote storage based on a capacity of memory allocated to store at least one snapshot of the storage device that include at least one of the one or more events.
2. The apparatus of claim 1 further configured to:
obtain the one or more snapshots of the storage device or at least one component of the storage device based on one or more of a predetermined snapshot rate and a dynamically determined snapshot rate; and
identify the one or more events based on a change rate corresponding to the memory allocated to store data contained in one or more IO operations of the IO stream, wherein the change rate corresponds to changed tracks of each logical unit number (LUN) of the memory.
3. The apparatus of claim 1 further configured to offload the one or more events based on at least one or more of a bandwidth to the remote storage, storage device performance state, service level priorities, and predictions of one or more events being identified during a future time period.
4. The apparatus of claim 1 further configured to measure a bandwidth to the remote storage and/or a storage device performance state.
5. The apparatus of claim 1 further configured to identify a service level (SL) tier of a service level agreement (SLA) corresponding to data contained in one or more IO operations of the IO stream, wherein each SL tier of the SLA defines one or more performance requirements for storing the data.
6. The apparatus of claim 4 further configured to monitor throughput to the remote storage to measure a bandwidth capacity for sending data to the remote storage.
7. The apparatus of claim 6 further configured to allocate a portion of the bandwidth capacity for offloading the one or more events.
8. The apparatus of claim 7 further configured to dynamically assign at least one of a bandwidth consumption ceiling and/or bandwidth consumption floor to each SL tier based on the allocated bandwidth portion.
9. The apparatus of claim 8 further configured to:
generate an anomaly detection model based on confirmed anomaly data, using an anomaly detection learning engine; and
generate a bandwidth capacity model for offloading the one or more events based on measured bandwidth capacities over time.
10. The apparatus of claim 9 further configured to offload the one or more events based on one or more of the anomaly detection model and the bandwidth capacity model.
11. A method comprising:
receiving an input/output (IO) stream for a storage device;
identifying one or more events having a change rate greater than a threshold and corresponding to the IO stream; and
offloading at least one of the one or more events to a remote storage based on a capacity of memory allocated to store at least one snapshot of the storage device that include at least one of the one or more events.
12. The method of claim 11 further comprising:
obtaining the one or more snapshots of the storage device or at least one component of the storage device based on one or more of a predetermined snapshot rate and a dynamically determined snapshot rate; and
identifying the one or more events based on a change rate corresponding to the memory allocated to store data contained in one or more IO operations of the IO stream, wherein the change rate corresponds to changed tracks of each logical unit number (LUN) of the memory.
13. The method of claim 11 further comprising offloading the one or more events based on at least one or more of a bandwidth to the remote storage, storage device performance state, service level priorities, and predictions of one or more events being identified during a future time period.
14. The method of claim 11 further comprising measuring a bandwidth to the remote storage and/or a storage device performance state.
15. The method of claim 11 further comprising identifying a service level (SL) tier of a service level agreement (SLA) corresponding to data contained in one or more IO operations of the IO stream, wherein each SL tier of the SLA defines one or more performance requirements for storing the data.
16. The method of claim 14 further comprising monitoring throughput to the remote storage to measure a bandwidth capacity for sending data to the remote storage.
17. The method of claim 16 further comprising allocating a portion of the bandwidth capacity for offloading the one or more events.
18. The method of claim 17 further comprising dynamically assigning at least one of a bandwidth consumption ceiling and/or bandwidth consumption floor to each SL tier based on the allocated bandwidth portion.
19. The method of claim 18 further comprising:
generating an anomaly detection model based on confirmed anomaly data using an anomaly detection learning engine; and
generating a bandwidth capacity model for offloading the one or more events based on the measured bandwidth capacities over time.
20. The method of claim 19 further comprising offloading the one or more events based on one or more of the anomaly detection model and the bandwidth capacity model.