元の名称記録: Beijing Volcano Engine Technology Co., Ltd.

Embodiments of the present disclosure provide a traffic scheduling control method and device based on a zoned storage device, and a storage medium. The method includes: determining, based on a garbage data ratio and a valid data ratio of a current zone to be collected of the zoned storage device, a target ratio of a throughput for writing data in a garbage collection process of the current zone to be collected to a throughput for writing data to the zoned storage device by a user; and controlling, based on the target ratio, the zoned storage device to process a first class request for writing data in the garbage collection process and a second class request for writing data to the zoned storage device by the user.

The present disclosure discloses a data migration method and a system based on a storage cluster, and a storage medium. The method includes: triggering a dual write mode of a block storage access client in response to a data migration instruction, and implementing incremental data synchronization to a source storage cluster and a target storage cluster by executing the dual write mode, where the data migration instruction is used to instruct to migrate data in the source storage cluster to the target storage cluster; and triggering a storage node in the source storage cluster to generate corresponding snapshot data for existing data in response to the data migration instruction, and migrate the snapshot data to the target storage cluster.

A method and device for loading virtual machine snapshot data, the method comprising: in response to receiving startup instructions of multiple virtual machines, selecting target image files corresponding to multiple virtual machines from multiple image files stored in an image center, and caching multiple snapshot data in the target image files in the form of stripe data to multiple snapshot cache nodes in an elastic block storage EBS cluster according to a preset first stripe size; wherein the EBS cluster is configured with a snapshot distributed cache formed by multiple snapshot cache nodes to be responsible for caching and distributing snapshot data; creating a data loading cloud disk corresponding to each virtual machine, and for each virtual machine, loading the snapshot data required to start the virtual machine from the snapshot storage space of multiple snapshot cache nodes through the data loading cloud disk corresponding to the virtual machine.

Embodiments of the present application provide a remote direct memory access method and apparatus, and relate to the field of computer technologies. The method includes: receiving a first virtual extensible local area network (VXLAN) message sent by a first virtual machine to a second virtual machine through a VXLAN tunnel, where the first VXLAN message is generated by performing VXLAN encapsulation on a remote direct memory access (RDMA) over Converged Ethernet (RoCE) message; and performing VXLAN decapsulation on the first VXLAN message through a hardware programmable network interface card based on a virtual switch, to obtain a first RoCE message, and performing access control on the first RoCE message through the hardware programmable network interface card, where the hardware programmable network interface card based on the virtual switch is preconfigured based on software of the virtual switch.

A resource scheduling method based on a storage system, a medium, and an electronic device are provided. The method includes: acquiring a manifest file respectively corresponding to each object bucket in a storage system; performing loop traversal allocation for each object bucket based on a preset object allocation rule to obtain a target object allocation quota for each object bucket; generating a data processing task corresponding to each object bucket based on the target object allocation quota for each object bucket and the manifest file corresponding to each object bucket, where a number of expired objects in a manifest file executed by a total data processing task of an object bucket is not greater than a target object allocation quota for the object bucket; and controlling the data processing task of each object bucket to be executed in parallel.

The disclosed embodiments provide a method, an apparatus, a system, a device and a storage medium for scheduling a resource for Just a Bunch of Disks (JBOD). The method comprises: acquiring, by a control and scheduling service node, attribution data of the JBOD, wherein the attribution data of the JBOD represents a mapping relationship between at least one JBOD and a storage service node to which the at least one JBOD belongs; and detecting, by the control and scheduling service node, an abnormal storage service node in the dual-head storage service node group, and scheduling, by the control and scheduling service node, a JBOD mounted on the abnormal storage service node to a normal storage service node in the dual-head storage service node group based on the attribution data of the JBOD.

Embodiments of the present disclosure provide a cloud storage resource scheduling method and apparatus, an electronic device, and a storage medium. The method includes: obtaining time-series statistical data of a storage system, which is used for representing a change over time of a plurality of resource states of a storage cluster in the storage system; determining, based on the time-series statistical data, whether resource scheduling needs to be triggered; in response to determining resource scheduling needs to be triggered, generating a resource scheduling topological graph for the storage system, and selecting, from the storage cluster in the storage system, candidate storage volume sets, based on the resource scheduling topological graph and the time-series statistical data; generating a resource scheduling plan based on a resource situation of each candidate storage volume, and controlling a performing of a scheduling task for a related storage volume based on the resource scheduling plan.

Provided in examples of the disclosure are a method and device for garbage collection of a zoned storage device, and a storage medium. Valid data segments in a source zone to be collected in the zoned storage device are determined, the read valid data segments are written into cache pools, and the valid data segments in the same cache pool are aggregated into a valid aggregated data segment; and a target cache pool to be written into the zoned storage device is determined, the valid aggregated data segment in the target cache pool is written into a target zone, and storage space of the source zone is collected.

The disclosed embodiment provides a method, device and storage medium for deduplication of an object storage system, which determines the target granularity for deduplication of the object storage system, which is the object granularity or the slice granularity; obtains the first check value of each data of the target granularity in the object storage system, and screens out the data with the same first check value from the object storage system to determine as duplicate data; adds, by taking one data in any group of duplicate data as the reference data, a soft link to the metadata of other data except the reference data in any group of duplicate data to point to the reference data, and recycles the storage space of other data.

A method, a device and a storage medium for detecting intrusion of a container environment. The method includes: performing event recognition on a real-time system event by calling an event recognition model corresponding to the target container, where the event recognition model is constructed based on a historical normal system event of the target container; in response to determining that the real-time system event is an abnormal system event, calling a predetermined intrusion detection rule to perform intrusion detection on the real-time system event, to determine whether the real-time system event is an intrusion event. Thus, a real-time system event that belongs to a normal system event may be filtered out, and a complete intrusion detection may be performed on the abnormal system event, thereby reducing the amount of data for intrusion detection, reducing resource occupation, and improving the performance and efficiency of the intrusion detection.

The present disclosure provides a risk detection method and apparatus for a language model, a device, a medium and a product, and the method includes: acquiring model input data of a target language model; determining at least one of intent description content and technique description content from the model input data; performing intent risk detection processing on the intent description content determined to obtain an intent risk detection result, and/or performing technique risk detection processing on the technique description content determined to obtain a technique risk detection result; and determining a risk detection result of the target language model applied to the model input data based on at least one of the intent risk detection result obtained and the technique risk detection result obtained.

Embodiments of the present disclosure provide a packet forwarding method and device based on a cloud network, the method including: receiving a first packet sent by a source virtual machine to a destination virtual machine, parsing the first packet, replacing an Ethernet protocol header of the first packet with a preset private extension protocol header, setting each field in the private extension protocol header according to a business requirement, and performing encapsulation through a VXLAN protocol to generate a second packet; and forwarding the target traffic based on the second packet.

The present disclosure relates to a traffic transmission control method, an electronic device, and a storage medium. The method includes: obtaining a central processing unit CPU consumption value consumed by each tenant traffic of a cloud network service transmitted via a virtual switch in a current statistical period, to obtain a CPU consumption value corresponding to each tenant; calculating a CPU consumption proportion among tenants based on the CPU consumption value and a CPU consumption value corresponding to each tenant accumulated in a historical statistical period; receiving outbound traffic of each tenant in a next statistical period of the current statistical period; and controlling the virtual switch to perform forwarding processing on the outbound traffic of each tenant in the next statistical period of the current statistical period based on the CPU consumption proportion among the tenants and a virtual switch forwarding performance proportion preconfigured for each tenant.