Managing storage systems that are synchronously replicating a dataset, including: detecting a change in membership to the set of storage systems synchronously replicating the dataset; and applying one or more membership protocols to determine a new set of storage systems to synchronously replicate the dataset, wherein the one or more membership protocols include a quorum protocol, an external management protocol, or a racing protocol, and wherein one or more I/O operations directed to the dataset are applied to a new set of storage systems.

Various implementations described herein relate to systems and methods for predicting and managing drive hazards for Solid State Drive (SSD) devices in a data center, including receiving telemetry data corresponding to SSDs, determining future hazard of one of those SSDs based on an a-priori model or machine learning, and causing migration of data from that SSD to another SSD.

An error information processing method includes, in response to a memory error triggering an interrupt, collecting error information of the memory error that includes a first memory area where the memory error occurs, obtaining a second memory area for writing log information, determining whether the second memory area contains the first memory area, and, in response to determining that the second memory area contains the first memory area, skipping a process of writing the log information into the second memory area.

Devices and techniques for fatal error logging in a memory device are described herein. For example, a read request can be received for a component of the memory device. A fatal error indication of an error that prevents correct execution of read request can be detected. Diagnostic information for the failure indication can be collected. A response to the read request can then be made with a portion of the diagnostic information as payload instead of the user data that would have occupied the payload had the read succeeded. Metadata in the response can be used to communicate an error code.

A system includes a cluster of nodes, memory, and a processor, where the cluster includes an application programming interface (API) server and one or more components. The processor is configured to initialize an interface to the API server, where the interface is operable to send status information from the one or more components within the cluster via a single output stream. The API server is configured to modify the single output stream of the API server to output status information associated with a first component of the one or more components within the cluster. The status information is aggregated and it is determined whether the cluster is at a failure point. In response to determining that the cluster is at a failure point, an execution signal is set to false, where the execution signal is accessible to an automation tool in communication the cluster.

Methods and systems are presented for providing a framework to integrate independent fragment modules into an integrated user interface. The fragment modules can be simultaneously rendered on a user interface page or sequentially rendered across multiple user interface pages. The fragment modules are configured to interact with a user via the user interface. The interactions with the user may trigger an event. When an event associated with a fragment module occurs, the fragment module is configured to broadcast the event. An orchestrator is configured to monitor events associated with different fragment modules. The orchestrator may include an event handler for performing one or more action in response to an event. The action may include configuring another fragment module to modify a presentation and/or perform a transaction based on the event.

Systems and methods are provided for analyzing one or more root causes of service degradation events in a network or other environment. A method, according to one implementation, includes a step of monitoring a plurality of overlying services offered in an underlying infrastructure having a plurality of resources arranged with a specific topology. In response to detecting a negative impact on the overlying services during a predetermined time window and based on an understanding of the specific topology, the method further includes the step of identifying suspect components from the plurality of resources in the underlying infrastructure. The method also includes the step of obtaining status information with respect to the suspect components to determine a root cause of the negative impact on the overlying services.

The present disclosure provides a method and a system of verifying access by a multi-core interconnect to an L2 cache in order to solve problems of delays and difficulties in locating errors and generating check expectation results. A consistency transmission monitoring circuitry detects, in real time, interactions among a multi-core interconnects system, all single-core processors, an L2 cache and a primary memory, and sends collected transmission information to an L2 cache expectation generator and a check circuitry. The L2 cache expectation generator obtains information from a global memory precise control circuitry according to a multi-core consistency protocol and generates an expected result. The check circuitry is responsible for comparing the expected result with an actual result, thus implementing determination of multi-core interconnect's access accuracy to the L2 cache without delay.

Embodiments may generally be directed to systems and techniques to detect failure events in data pipelines, determine one or more remedial actions to perform, and perform the one or more remedial actions.

A cloud scraping system using pre-scraped big data includes an information providing server which, when receiving a scraping request from a user terminal, provides the user terminal with response information to the received scraping request, and a big data storage which stores pre-scraped information, wherein when the scraping request is about static information, the information providing server acquires the response information using the pre-scraped information. According to the above cloud scraping system using pre-scraped big data, there is an advantage that it is possible to quickly respond to a scraping request from the user terminal afterwards by pre-scraping and storing static information in the big data storage. Additionally, it is possible to improve the scraping server operation efficiency by making a proper use of a single or multi-processing scraping server based on policy information of a scraping target external institution.