Abstract: A distributed data security event detection and response (DDSEDR) system includes a data security management (DSM) system and a client-side data security event confirmation and response (CDSECR) system that manage data security events, such as ransomware attacks. In at least one embodiment, the DDSEDR system provides data security event detection, confirmation, mitigation, alerting, and recovery from malicious processes and other data security events. In at least one embodiment, the DSM system monitors one or more client file event records for information that indicates a potential data security event. If the DSM system detects a potential data security threat, the DSM, sends information to the CDSECR system that causes CDSECR system to inspect one or more files associated with the potential data security event to determine whether an actual data security event occurred and initiate a responsive action when the CDSECR system detects an actual data security event.

Abstract: The disclosed embodiments disclose techniques for accessing a scale-out block interface in a cloud-based distributed computing environment (CBDCE). During operation, an instance of a block device service (BDS) receives a data request from a client. The BDS instance translates the data request into a set of data block accesses, and then sends the translated data request to a data processing layer service (DPL). The DPL instance services the data request using a set of data operations that leverage one or more of a distributed cache, a distributed database, and a cloud storage system. The BDS service leverages the DPL instance to provide to the client an abstraction of a highly-available block storage device with unlimited storage space via the scale-out block interface.

Abstract: The disclosed embodiments disclose techniques for journaling data received in a cloud-based distributed computing environment (CBDCE). Multiple services simultaneously execute on the CBDCE compute nodes, with each service comprising multiple service instances that simultaneously execute on multiple, distinct compute nodes of the CBDCE. The CBDCE includes a distributed database that enables coordination between the service instances of services that execute in the CBDCE; this distributed database also includes multiple distributed database instances that simultaneously executing on multiple different CBDCE compute nodes. During operation, a service instance executing on one of these compute nodes receives a client request. The service instance submits this client request to a distributed database instance and, in parallel, also submits the client request and its associated user data to a distributed journaling service.

Abstract: The disclosed embodiments disclose techniques for managing a cloud-based distributed computing environment (CBDCE) that comprises multiple geographically-distributed compute nodes. Multiple services simultaneously execute on the CBDCE compute nodes, with each service comprising multiple service instances that simultaneously execute on multiple distinct compute nodes of the CBDCE. During operation, the system uses a distributed database to track the status of the CBDCE to ensure the ongoing stability and scalability of the CBDCE. Upon receiving a request that is associated with the configuration of the CBDCE, a service accesses CBDCE status information from the distributed database to respond to the request.

Abstract: The disclosed embodiments disclose techniques for managing a distributed cache in a cloud-based distributed computing environment (CBDCE). During operation, an instance of a data processing layer service (DPL) receives a data request from a client that specifies an address and an operation for a target data block. The DPL instance uses these to determine a first cache instance of the distributed cache that is assigned to cache a metadata entry that links the address with a data block fingerprint for the target data block. The DPL instance then uses the data block fingerprint and the cache mapping to determine a second cache instance that is assigned to store the target data block, and then accesses the second cache instance to complete the operation for the target data block.

Abstract: The disclosed embodiments disclose techniques for managing cloud-based storage using a time-series database. A distributed cloud data management system (DCDMS) manages objects stored in a cloud storage system. The DCDMS leverages a distributed time-series database to track objects accessed via the DCDMS. During operation, the DCDMS receives a request to access an object using a path identifier and an object identifier. The DCDMS determines from the path identifier that the request is associated with one of its supported extended capabilities, and uses the previously tracked object operations that are stored in the time-series database to determine the actual target bucket in the cloud storage system that contains the requested object; the target bucket that contains the object may be different from the bucket identified in the path identifier that is received. The object identifier is then used to access the requested object from the target bucket to service the request.