A method for synchronous replication of stream data includes receiving a stream of data blocks for storage at a first storage location associated with a first geographical region and at a second storage location associated with a second geographical region. The method also includes synchronously writing the stream of data blocks to the first storage location and to the second storage location. While synchronously writing the stream of data blocks, the method includes determining an unrecoverable failure at the second storage location. The method also includes determining a failure point in the writing of the stream of data blocks that demarcates data blocks that were successfully written and not successfully written to the second storage location. The method also includes synchronously writing, starting at the failure point, the stream of data blocks to the first storage location and to a third storage location associated with a third geographical region.

Systems and methods for performing data protection operations including garbage collection operations and copy forward operations. For deduplicated data stored in a cloud-based storage or in a cloud tier that stores containers containing dead and live segments or dead and live regions such as compression regions, the dead compression regions are deleted by copying the live compression regions into new containers and then deleting the old containers. The copy forward is based on a recipe from a data protection system and is performed using a serverless approach.

Method and apparatus for stress management in a searchable data service. The searchable data service may provide a searchable index to a backend data store, and an interface to build and query the searchable index, that enables client applications to search for and retrieve locators for stored entities in the backend data store. Embodiments of the searchable data service may implement a distributed stress management mechanism that may provide functionality including, but not limited to, the automated monitoring of critical resources, analysis of resource usage, and decisions on and performance of actions to keep resource usage within comfort zones. In one embodiment, in response to usage of a particular resource being detected as out of the comfort zone on a node, an action may be performed to transfer at least part of the resource usage for the local resource to another node that provides a similar resource.

A storage controller has an operating system (OS) and power control firmware configured to manage use of battery power during a power outage event. The OS specifies to the power control firmware first and second sets of physical components that should be shed by power control firmware during a two-phase vault process. Upon a power failure, the power control firmware turns off power to the first set of physical components and notifies the OS of the power failure. The OS determines whether to abort or continue the vault process. If the OS aborts the vault process, the power control firmware restores power to the first set of physical components. If the OS continues the vault process, the power control firmware turns off power to the second set of physical components, the OS saves application state, and moves all data from volatile memory to persistent memory.

A monitoring and alerting system backed by a machine learning engine for anomaly detection and prediction of time series data indicative of health of an application, a system, an environment, or a person. Using any data of interest that is modeled into a time series known as times and values; comparing input data against learned previous patterns; predicting data; identifying anomalies; generating notifications or an alert identifying the deviation, and communicating the alert to users, applications, or devices, applying the action or health functions logic using the significance of the issue to modify/start/stop components of the system or application. The data is received via a metrics server and is cleaned into a unified format and passed through via streaming or push/pull mechanisms. Planned deviations are configured to prevent false positives. A variety of machine learning methods is used and the system has dual function components and disaster recovery.

A system includes a multi-process application that runs. A multi-process application runs on primary hosts and is checkpointed by a checkpointer comprised of at least one of a kernel-mode checkpointer module and one or more user-space interceptors providing at least one of barrier synchronization, checkpointing thread, resource flushing, and an application virtualization space. Checkpoints may be written to storage and the application restored from said stored checkpoint at a later time. Checkpointing may be incremental using Page Table Entry (PTE) pages and Virtual Memory Areas (VMA) information. Checkpointing is transparent to the application and requires no modification to the application, operating system, networking stack or libraries. In an alternate embodiment the kernel-mode checkpointer is built into the kernel.

A distributed database encrypts a table using a table encryption key protected by a client master encryption key. The encrypted table is replicated among a plurality of nodes of the distributed database. The table encryption key is replicated among the plurality of nodes, and is stored on each node in a respective secure memory. In the event of node failure, a copy of the stored key held by another member of the replication group is used to restore a node to operation. The replication group may continue operation in the event of a revocation of authorization to access the client master encryption key.

The present invention provides systems and methods for data storage. A hierarchical storage management architecture is presented to facilitate data management. The disclosed system provides methods for evaluating the state of stored data relative to enterprise needs by using weighted parameters that may be user defined. Also disclosed are systems and methods evaluating costing and risk management associated with stored data.

A method includes saving a control state for a processor in response to commencing a transactional processing sequence, wherein saving the control state produces a saved control state. The method also includes permitting updates to the control state for the processor while executing the transactional processing sequence. Examples of updates to the control state include key mask changes, primary region table origin changes, primary segment table origin changes, CPU tracing mode changes, and interrupt mode changes. The method also includes restoring the control state for the processor to the saved control state in response to encountering a transactional error during the transactional processing sequence. In some embodiments, saving the control state comprises saving the current control state to memory corresponding to internal registers for an unused thread or another level of virtualization. A corresponding computer system and computer program product are also disclosed herein.

Certain embodiments described herein relate to an improved disk usage growth prediction system. In some embodiments, one or more components in an information management system can determine usage status data of a given storage device, perform a validation check on the usage status data using multiple prediction models, compare validation results of the multiple prediction models to identify the best performing prediction model, generate a disk usage growth prediction using the identified prediction model, and adjust the available space of the storage device according to the disk usage growth prediction.