Operational Intelligence Platform

Abstract

An approach is provided for monitoring and managing one or more operational components of a data center. Data of one or more applications related to the operational functions may be received. The one or more applications may be associated with one or more associated applications. A failure of one or more components monitored by the one or more applications or the one or more associated applications may be detected. A cause of the failure may be determined based at least in part on the sensed changes and context information associated with the failure. At least one change may be implemented to the component based on the determined cause.

Description

[Background technology]

[0001] This PCT application claims priority to and the benefit of pending U.S. Provisional Application No. 63 / 289,593, filed December 14, 2021, entitled "OPERATIONAL MANAGEMENT PLATFORM," the entire disclosure of which is incorporated herein by reference in its entirety for all purposes.

[0002] Users and service providers are increasingly dependent on electronic computing resources available in one or more data centers for various computing needs. Some operational requirements of a data center include, among others, a building management system (BMS), a power management system (PMS), heating, ventilation, and air conditioning system (HVAC), fire alarm system, network management system, battery management system, open weather APIs, and integration with third-party systems. However, a data center's operational systems often run independently of each other, with separate systems monitored by separate entities. When a failure occurs, it can be difficult to pinpoint the cause of the failure with a high degree of accuracy, partly due to the number of entities involved. For example, if a temperature sensor reads a high temperature, it can be difficult and time-consuming for a data center provider to determine the cause of the high temperature, especially if one or more operational systems are not communicating with each other.

[0003] Additionally, various components may indirectly cause operational issues over time. Technicians may not be able to directly observe the components and determine how they affect downstream operations. Additionally, technicians may work different shifts and may overlook potential sources of operational failure. [Brief description of the drawings]

[0004] Various embodiments according to the present disclosure are described with reference to the drawings.

[0005] [Figure 1] FIG. 1 illustrates an example interface that can be utilized to implement one or more embodiments. [Diagram 2] FIG. 2 illustrates another example interface that may be utilized in accordance with one or more embodiments. [Diagram 3] FIG. 3 illustrates an example control system for controlling one or more components of a data center cooling system according to various embodiments. [Figure 4] FIG. 4 illustrates an example method that may be utilized in accordance with one or more embodiments. [Diagram 5] FIG. 5 illustrates an environment in which various embodiments may be implemented according to various embodiments. [Figure 6] FIG. 6 illustrates an exemplary environment that can be utilized in accordance with various embodiments. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0006] In the following description, various embodiments are described. For purposes of explanation, specific configurations and details are set forth in order to provide a thorough understanding of the embodiments. However, it will be apparent to one skilled in the art that the embodiments may be practiced without the specific details. Furthermore, well-known features may be omitted or simplified so as not to obscure the described embodiments.

[0007] Data center operations may require significant human involvement, and technicians working in one operational area may not even have contact with other technicians working in other areas. Thus, when a component in a data center fails, it may be cumbersome to determine the cause of the failure, given the number of agencies that independently operate and manage the individual components in the data center. Data in the integrated platform may be provided in a data structure that includes multiple parent nodes associated with multiple child nodes, and data may be presented in relation to a single asset with all related data associated with the asset in a single view. In this manner, fewer technicians may be required to monitor and control data center operations. One or more neural networks may be utilized to observe environmental changes in the data center and generate associations between data points, according to various embodiments. Based on the changes, one or more neural networks may be utilized to generate recommendations or automatically implement environmental changes.

[0008] An integrated, centralized platform may enable faster detection and diagnosis of one or more operational faults because such a platform allows a technician to quickly analyze and determine the cause or root cause of the fault. For example, a fault is displayed on the platform with a corresponding timestamp. The technician can then backtrack from that timestamp and analyze various operations on a single screen to determine what actually caused the fault. The root cause of the fault may be distinguishable from the perceived fault because the perceived fault may be a result of the root cause of the fault. As a result, operational uptime may be increased due to resilient load balancing and reduced monitoring of redundant architectures. In at least some exemplary embodiments, artificial intelligence may be utilized to generate suggestions and recommendations to conserve energy. For example, at least one neural network may be trained to recognize changes or behaviors in the environment, infer the causes of the changes, and recommend corrective actions to be taken. As used herein, "artificial intelligence" includes, but is not limited to, machine learning, natural language processing, neural networks, random forest models, and other such algorithms or models.

[0009] Such a platform may be hosted on a cloud-based service and managed remotely. Additionally, the platform may be offered in an on-premise option depending on the client's needs and available building systems and data network connections. A scalable architecture within the system allows the system to expand for new sites while minimising the risk of system downtime associated with relocations or expansions. The platform may also be integrated with data centres hosted by different providers. In at least some embodiments, the system may be controlled automatically without human intervention. For example, the system may use artificial intelligence or threshold management techniques to determine when to automatically cut power to one or more components of the system or to change the operating conditions of one or more components to optimise energy savings while maintaining proper operation.

[0010] According to an exemplary embodiment, one or more components within a data center may be remotely controlled via the platform to allow a technician working remotely to adjust conditions such as the temperature and humidity of the data center, or the fan speeds of fan wall units operating within the data center. Such data may be provided to the platform in real time to allow the technician to adjust one or more system metrics to improve the efficiency of the data center. Additionally, control logic may be implemented to make proactive decisions to optimize efficiency, such as lowering power loads or increasing fan speeds.

[0011] FIG. 1 illustrates an exemplary interface 100 that can be utilized to implement one or more embodiments. In accordance with an exemplary embodiment, a user can access functionality related to the operation of a data center via the interface 100. A platform for monitoring and operating a data center according to an exemplary embodiment can be integrated with multiple systems and data sources. For example, a computer-aided facility management (CAFM) ticket management system can be integrated with relevant system data to allow an operations team to track down operational faults in the data center system. Additionally, the platform can be integrated with any internal or external system with fine-grained controls that implement role-based access control (RBAC) on data such as API data. Developers, engineers, and customers can be provided with programmatic access to the platform. Third-party vendors can also be provided with access to the platform and access can be restricted to information determined to be relevant to the vendor. According to an example, active directory can be integrated to provide role-based access control to the platform. For example, engineers can have different privileges than customers of the data center. Access to the platform and permissions to various functions of the platform can be modified according to one or more needs of the user. Changes may be pushed out in real time so that customers who require access to modules they would not otherwise have permission to access can be granted access without delay.

[0012] Additionally, multi-factor authentication may be utilized when providing access to the platform. For example, when requesting access to the platform, a user may be required to provide login credentials along with another token to log into the platform. For added security, a complete audit trail of the user may be recorded along with every system activity. According to another example, visitor and contractor management for Data Center Requests (DCR) may be provided within the platform. For example, a visitor or contractor may request access to a physical site or submit a work request for a specific asset if the visitor or contractor is not within the network of the host location.

[0013] Using the dashboard 102 or other type of navigation tool, a user may manage or view data associated with one or more environments. For example, a user may view and manage data associated with one or more data centers in various regions. In accordance with an exemplary embodiment, the data may be uniquely integrated using a data structure that includes multi-parent and multi-child data formats with a common naming scheme. In this manner, operational data associated with various aspects of a data center may be easily integrated into the platform, and data may be easily associated across multiple operations. Independently monitored operations may be associated with other independent operations to provide meaningful insights to the user.

[0014] According to an exemplary embodiment, one or more widgets may be provided for display. The one or more widgets may be dynamically provided depending on one or more permissions granted to the user. The widgets may include usage data, statistical data, performance data, status information, service ticket information, and environmental data, among others. Usage data may include plant availability usage, power usage effectiveness (PUE) provided as a PUE index, PUE vs. site supply vs. IT load history, and PUE average for a given period of time. Usage data may also include data indicating the total amount of energy consumed at a particular site, or the total amount of water consumed at a particular site. Other usage data includes fuel usage and real-time carbon usage. In this example, the user may view one or more data points including humidity 104, power 106, temperature 108, and PUE 110. These data points may be provided in real time as well as in daily / weekly / monthly reports. For example, a PUE report may provide insight into the energy efficiency of a data center. PUE may be a measure of how much energy is used by computing equipment in a data center. According to one example, PUE may be expressed as a ratio of the total amount of energy used by a computer data center facility to the energy supplied to the computing equipment in the data center.

[0015] A user may want to see related and unrelated data in a single report. An exemplary centralized platform may provide one or more features to allow a user to select the data series they want to see, regardless of whether that data is related to other data series in the platform, and generate a report for the user. Reports may be scheduled to be delivered directly to the user on a daily, weekly, or monthly schedule, depending on the user's needs. Reports may also be provided with a single click, and reports may reflect real-time data. In traditional systems, creating a report covering such a large number of components would take weeks. The integrated solution provides reports much more quickly and accurately than traditional systems. Reports may be exported to the user in a variety of formats, including spreadsheets, document files, and portable document formats.

[0016] One or more insights, such as a PUE vs. load graph 112, may be generated and provided for presentation on the interface 100. The insights may also include an equipment uptime monitor 114, among other similar insights. According to an exemplary embodiment, the interface may enable clients, suppliers, or other such users to access one or more configurable widgets that include user-defined dashboards and other interactive and live information. Such a platform may be used on desktops, tablets, mobile devices, and the like, among other similar devices.

[0017] One or more benefits of a centralized platform may include cost optimization through continuous improvement of operational efficiency. For example, such a system may enable energy savings and expenditures on physical labor performing operations at a given location. Additionally, predictive maintenance may beneficially detect changes in the behavior of the system and indicate early maintenance issues prior to failure. For example, one or more maintenance recommendations may be provided to a user prior to failure using data such as age of one or more components or learned behavior of one or more components. In at least some exemplary embodiments, cost savings may be calculated and provided to a user to enable the user to use the cost information and maintenance recommendations to determine whether it would be more costly to wait to replace a component.

[0018] While this example is of displaying data points, graphs, and monitors, other information may also be provided to display. For example, the interface may be used to provide a user with health and safety compliance information in addition to a graphical view of people on-site, health and safety near misses, and events by location. The converged platform may provide operational visibility into one or more operational aspects of the data center. For example, a single platform may provide, among other configurations, a building management system (BMS), a power management system (PMS), HVAC, fire alarm systems, network management, battery management, open weather APIs, cloud-based storage and sync service integration, and visibility into third-party systems. Third-party systems may include asset management systems, maintenance services, document management services, record management services, email and messenger systems, human resources services, and the like. According to an exemplary embodiment, a user may be provided with workflows that support on-site compliance requirements, such as new inspection workflows and workaround processes.

[0019] One or more widgets of the interface may also provide statistical information including, but not limited to, the total amount of assets added to a third-party system, such as asset management software. Other statistics may include one or more metrics providing insight into data center infrastructure efficiency (DCIE), statistics showing deltas over time between environmental or ambient values. According to another example, one or more widgets may provide an incident count, or an executive view of incident counts by category, which may also be mapped as an indication of current values ​​against past values. Other statistics according to one example may include one or more numerical values ​​representing IT load and total IT load.

[0020] According to one example, one or more charts may be provided, such as a chart showing PPM requests statistics, a chart showing problem requests statistics, a chart showing completed requests statistics, etc. According to another example, the total site load distribution may be provided as a pie chart and one or more site load metrics and historical site metrics may be provided in one or more widgets.

[0021] According to another example, the statistics may also include percentages of uptime for a time period for one or more metrics such as humidity, power, and temperature. Historical performance of temperature, humidity, and power uptime may also be provided. Additionally, in another example, total equipment uptime may be provided and shown as a comparison to a total target amount.

[0022] Health status information may also be provided in one or more widgets. For example, the status of building management system (BMS) sensors may be provided for one or more components of a data center. Other status information may include information regarding generator availability for one or more generators associated with the data center. In another example, status regarding one or more running services may be provided. Site electrical health status and / or site mechanical health status may also be provided, as well as electrical capacity. One or more health statuses may be provided for all systems in real time.

[0023] According to another example, one or more widgets for a platform may show a graphical relationship view of one or more systems and their endpoints related to one or more data center assets (e.g., generators). One or more widgets may also be provided to show changes in the development of an application, such as a change log showing changes made at a particular point in time. According to another example, one or more widgets may provide a list of critical work areas, a list of recent incident records, and / or a total number of incident reports.

[0024] Because weather conditions can affect the overall efficiency of a data center, weather and historical weather data can be provided in the form of charts or tables on the exemplary platform. Such information can be beneficial when current or future projects involve operational system changes, building system reconfigurations, plant replacements, or system redesigns.

[0025] According to one example, a platform for monitoring and operating a data center may include a document management system that may be fully integrated with the platform, allowing a user to access one or more files from a centralized platform associated with a particular asset without having to switch among other file management systems.

[0026] An exemplary platform may also be fully integrated with work management software or project management tools for tracking issues and bugs while allowing for the submission of bugs and feature requests. In this manner, users of the platform may not need to log into separate services to manage one or more operational aspects of the datacenter.

[0027] Within the exemplary platform, one or more training videos may be provided on how to use the platform and how to perform specific tasks. Additionally, one or more tooltips may be provided within the platform to inform the user of various features of the platform and / or suggest recommended actions the user may take with respect to a given widget. Explanations of terms may also be provided so that the user can fully understand and appreciate what they are seeing.

[0028] In one example data center environment, water management may be a significant part of the operation since water may be used in cooling units to cool the data center. Thus, in one example, a platform for monitoring a data center may include a module for water management, where the site's water consumption and emissions may be calculated and analyzed to provide insights for water efficiency within the system.

[0029] Service level agreement (SLA) reports may also be provided to users, providing a calculation of the percentage of time that acceptable service levels were maintained for the resources included in the report. For example, a user may be provided with a runtime report that describes how many times various components of a data center were operating at full capacity over a specified period of time. In accordance with an exemplary embodiment, a user may be notified of tickets that have violated an SLA or are at risk of violating an SLA. Notifications may be generated automatically based on the analyzed data. For example, a data point that falls below an agreed upon value for a determined period of time may indicate a possible SLA violation. Users that are subject to SLAs may be provided with notifications of the event. In at least some exemplary embodiments, a user may also be provided with recommended corrective actions to prevent future failures.

[0030] The status and availability status of an entire data center may be provided on the platform, as well as the availability of individual components within the data center. For example, a user may view the status of one or more components of a cooling system, and one or more components of an electrical system that powers the cooling system and the computer components within the data center. According to another exemplary embodiment, a live or rolling view of a network operations center (NOC) or network management center (NMC) may be provided.

[0031] A platform according to one example can include a module for risk assessment, which can include estimated production availability of the system by evaluating failure modes, frequencies, and consequences. In one example, an asset impact assessment may be provided within or separate from the module to predict or model operational issues that may occur downstream when a circuit breaker is turned off. The asset impact assessment is integrated with or otherwise associated with one or more other monitoring components to maintain real-time updates of the system.

[0032] According to an exemplary embodiment, a Planned Preventive Maintenance (PPM) tool and calendar view may be provided. For example, a calendar extract of PPM tasks visualized in Data Center Operations (DCOps) may be displayed along with current SLA status, allowing a user to easily analyze tasks and determine which operations need to be addressed at any given time.

[0033] FIG. 2 illustrates another example interface 200 available in accordance with one or more embodiments. In this example, a user can view information associated with one or more work orders 202. A work order may be utilized to alert a user to one or more issues that may need to be addressed, and the work order may be specific to a facility or a component within a facility. Operational maintenance may also be optimized using work orders or other types of service tickets that may be raised in response to incidents, ticket performance monitoring, operational blueprint process libraries, time and resource monitoring, and collaborative safety tools, among other similar options. Using processing logic associated with the platform, a service ticket may be automatically raised in response to a detected rate of change of one or more metrics within the data center. A technician may then be notified of the issue quickly, rather than waiting for a user to raise a ticket. Additionally, because data regarding nearly all assets within the data center may be provided in a centralized manner, a technician may easily determine why a service ticket was raised, as well as how to address the issue raised in the ticket. In some example embodiments, maintenance tasks may be automatically scheduled.

[0034] The total number of tickets may also be provided in the widget, along with the total number of users of the system or part of the system and the associated permissions assigned to particular users. In at least one exemplary embodiment, tickets may be automatically assigned to technicians based on the technician's skill set. For example, if a technician has a particular skill for addressing an issue, the technician may be automatically assigned to handle the task.

[0035] In the example of the ticket service widget, or separately from the ticket service widget, a summary of the work order may be provided. The summary may be ranked based on a risk classification. According to one example, the risk level may be automatically determined and classified. For example, if the power supplied to a critical area falls outside one or more determined thresholds, a risk ticket with an increased risk category may be raised without technician intervention. Depending on the determined thresholds, the risk may be classified as low, medium, or high. In other embodiments, the risk level may be manually determined by a technician.

[0036] As shown, the work orders may have corresponding information including, but not limited to, a start date, an end date, a summary, and a status. Work order number 6 indicates that the system automatically adjusted the flow rate of one of the components in the environment. According to an exemplary embodiment, the flow rate may be adjusted in response to the system determining that corrective action is required for the component. The system may make such a determination, at least in part, using a neural network or other form of artificial intelligence.

[0037] Also shown in the example of Figure 2 is a line graph 204 of various data points from various sensors over time. For example, outside air temperature, outside air humidity, fresh air temperature, return air temperature, flow rate values, and other types of values ​​may be recorded and provided for display. In this manner, different types of data for a particular environment may be easily visualized.

[0038] In accordance with an exemplary embodiment, a workflow engine may be used to assign workload items to users, such as via work orders or other manners of task assignment. One or more aspects of an exemplary workflow engine may include a universal workflow and automation designer engine. Such an engine may include computer aided facility management (CAFM) functionality, including management tools and the ability to track, manage, report, and plan one or more operations of a data center.

[0039] The workflow engine may be compatible with Business Process Model and Notation (BPMN) such that the end-to-end orchestration of the workflow is provided graphically in a business process model. According to one example, one or more visualizations of the workflow and the current state of the workflow are provided on the platform. The visualizations make bottlenecks in the operational workflow easily recognizable or determinable, allowing the user to optimize processes that may be causing the bottlenecks.

[0040] Reports related to estimated production availability may be generated in addition to any other reports related to any of the components associated with the system. Additionally, a live view of active incident management may be provided along with a root cause analysis of every incident. Root cause analysis by way of an example includes observations, near misses, and accidents. If a critical component in the data center fails, the component may be identified as high priority and provided with high urgency to a ticket management system integrated with the platform. A technician may be provided with a notification or message in the ticket management system or another module of the system regarding the failure of the critical component along with the location of the component to facilitate identification.

[0041] According to another embodiment, one or more reports can provide one or more site metrics to a user. For example, the reports can include metrics related to the operation of cooling units in a data center, such as temperature, pressure, energy efficiency, emissions, carbon reporting, among other similar metrics. Reports may also be provided that focus on availability of critical systems. Incident reports from multiple systems may also be provided that indicate incidents related to one or more components in the data center. Notes related to the incidents can also be entered automatically or manually to indicate causes and provide troubleshooting advice for the incidents.

[0042] FIG. 3 illustrates an exemplary control system 300 for controlling one or more components of a data center cooling system. According to one embodiment, the control system may include a calculator 306 that may receive at least temperature data 302 and pressure data 304 from one or more temperature and pressure sensors. In this example, the use of temperature and pressure sensors is described, but other data may be collected from other sensors that may be indicative of operating conditions associated with the environment. A calculator, such as calculator 306, may process the temperature data 302 and pressure data 304 to determine a temperature differential and a pressure differential for the cooling system. The calculations may be received by one or more controllers, such as controller 308, to determine one or more control functions for one or more components of the data center cooling system. For example, if the pressure differential is equal to or greater than a determined threshold, a controller, such as controller 308, may control a fluid flow rate 310. The controller may include a memory and at least one processor configured to execute one or more instructions for controlling one or more components of the system. The controller may also control other functions, such as one or more operation of a cooling unit 312 or one or more fan speeds 314, among other similar components. A technician may utilize a centralized platform according to one or more embodiments described herein to locally or remotely monitor and control one or more of these components shown in Figure 3. According to an exemplary embodiment, one or more components of system 300 may be automatically controlled, such as through the use of artificial intelligence techniques. For example, one or more neural networks may be utilized to analyze the operating conditions of the various components over time and implement or otherwise recommend corrective actions to maintain target operating conditions.

[0043] FIG. 4 illustrates an example method 400 that may be utilized in accordance with one or more embodiments. For any process herein, it should be understood that there may be additional, fewer, or alternative steps performed in a similar or alternative order, or in parallel, within the scope of various embodiments, unless otherwise noted. In accordance with an example embodiment, data of one or more applications associated with one or more operational functions of a data center may be received (402). The one or more applications may be associated with one or more associated applications and provided for display in at least one display interface 404. A failure of one or more components monitored by the one or more applications or the one or more associated applications may be detected (406). A cause of the failure is determined (408) based at least in part on the detected changes and context information associated with the failure. At least one change may be made to the one or more components based at least in part on the determined cause 410.

[0044] FIG. 5 illustrates an environment 500 in which various embodiments may be implemented according to various embodiments. According to an exemplary embodiment, the environment 500 may include at least one server 506 and one or more data stores 508. It should be understood that there may be multiple servers, layers, or other elements, processes, or components that may be chained or otherwise configured that may interact to perform tasks such as retrieving data from or providing data to an appropriate data store. Data is backed up daily in all systems and data stores. Depending on the client's request, backups may also be performed more frequently, such as hourly. Data in the platform is refreshed in real time, and one or more widgets in the platform may provide live data displays. With data refreshed in real time, service providers can quickly and efficiently pinpoint the cause of failures in their data centers.

[0045] The server 506 may include any suitable hardware and software for executing aspects of one or more applications for the client devices and integrating with the data store 508 as necessary to handle most of the data access and business logic for the applications. A web server may be utilized to provide application data to users in the form of HTML, XML, or other suitable structured language. In accordance with an exemplary embodiment, the server 506 may include an application side server and a web server. All request and response processing, as well as the delivery of content between the client device 502 and the application side server, may be handled by the web server. Requests may be received over a network 504. The network 504 may include any suitable network, including an intranet, the Internet, a cellular network, a local area network (LAN), or any other such network or combination, and communication over the network may be enabled via wired and / or wireless connections. It should be understood that the structured code described herein may be executed on any suitable device or host machine, and thus the web server and application side server are merely exemplary components rather than required.

[0046] Each server typically includes an operating system that provides executable program instructions for the general management and operation of the server, and typically includes a computer-readable medium that stores instructions that, when executed by the server's processor, enable the server to perform its intended functions. Suitable implementations of operating systems and the general functions of servers are known or commercially available, and will be readily implemented by those of skill in the art, especially in light of the disclosure herein.

[0047] The environment in one embodiment is a distributed computing environment utilizing multiple computer systems and components interconnected through computing links using one or more computer networks or direct connections. However, those skilled in the art will appreciate that such a system may operate similarly in systems having fewer or more components than are illustrated in Figure 5. Thus, the illustration of environment 500 in Figure 5 should be considered exemplary in nature and not limiting of the scope of the present disclosure.

[0048] FIG. 6 illustrates an exemplary environment 600 in which aspects of various embodiments may be implemented. In this example, a user may utilize at least one client device 602 to send requests to a resource provider environment 606 over at least one network 604. A client device may include any suitable electronic device operable to send and receive requests, messages, or other such information over an appropriate network and return information to a user of the device. Examples of such client devices include personal computers, tablet computers, smartphones, notebook computers, and the like. The at least one network 604 may include any suitable network, including an intranet, the Internet, a cellular network, a local area network (LAN), or any other such network or combination, and communication over the network may be enabled via wired and / or wireless connections. The resource provider environment 606 may include any suitable components for receiving requests and returning information or performing actions in response to those requests. As an example, the provider environment may include a web server and / or application server for receiving and processing requests and returning data, web pages, video, audio, or other such content or information in response to the requests.

[0049] In various embodiments, the provider environment may include various types of resources that may be utilized by multiple users for various different purposes. As used herein, computing and other electronic resources utilized in a network environment may be referred to as "network resources." These may include, for example, servers, databases, load balancers, routers, and the like, which may perform tasks such as receiving, transmitting, and / or processing data and / or executable instructions. In at least some embodiments, all or a portion of a given resource or set of resources may be assigned to a particular user or for a particular task, at least for a determined period of time. The sharing of these multi-tenant resources from the provider environment is often referred to as resource sharing, web services, or "cloud computing," among other similar terms, depending on the particular environment and / or implementation. In this example, the provider environment includes multiple resources 614 of one or more types. These types may include, for example, application servers operable to process instructions provided by users, or database servers operable to process data stored in one or more data stores 616 in response to user requests. As is known for such purposes, users may also reserve at least a portion of the data storage in a given data store. Methods for allowing users to reserve various resources and resource instances are well known in the art, so a detailed description of the entire process and an explanation of all possible components will not be described in detail herein.

[0050] In at least some embodiments, a user desiring to utilize a portion of the resource 614 can submit a received request to an interface layer 608 of the provider environment 606. The interface layer can include an application programming interface (API) or other public interface that allows a user to submit a request to the provider environment. The interface layer 608 in this example can also include other components, such as at least one web server, routing component, load balancer, etc. When a request to provision a resource is received at the interface layer 608, the information in the request can be directed to a resource manager 610 or other such systems, services, or components configured to manage user accounts and information, resource provisioning and usage, and other such configurations. The resource manager 610 receiving the request can perform tasks such as authenticating the identity of the user submitting the request and determining whether the user has an existing account with the resource provider, where the account data may be stored in at least one data store 612 of the provider environment. The user can provide any of a variety of types of credentials to authenticate the user's identity to the provider. These credentials may include, for example, a username and password pair, biometric data, a digital signature, or other such information. The provider may verify this information against information stored for the user. If the user has an account with appropriate privileges, state, etc., the resource manager may determine whether there are suitable resources available that match the user's request, and if so, may provision the resources or otherwise allow access to the corresponding portions of the resources for use by the user for an amount specified by the request. This amount may include, for example, capacity to process a single request, capacity to perform a single task, a specified period of time, or a repeatable / renewable period of time, among other similar values.If the user does not have a valid account with the provider, if the user account does not allow access to resources of the type specified in the request, or if other such reasons prevent the user from gaining access to such resources, a communication may be sent to the user to enable the user to create or modify an account or change the resources specified in the request, among other similar options.

[0051] Once a user is authenticated, an account is verified, and resources are allocated, the user may utilize the allocated resources for a specified capacity, data transfer amount, duration, or other such value. In at least some embodiments, the user may provide a session token or other such credential information in subsequent requests to enable requests to be processed in that user session. The user may receive a resource identifier, specific address, or other such information, which may enable the client device 602 to communicate with the allocated resources without communicating with the resource manager 610, at least until an associated configuration of the user account is changed, the user is no longer granted access to the resource, or other such configuration is changed.

[0052] The resource manager 610 (or another such system or service) in this example may also function as a virtual layer of hardware and software components that handles control functions in addition to management actions, such as may include provisioning, scaling, replication, etc. The resource manager may utilize dedicated APIs in the interface layer 608, each of which may be provided to receive a request for at least one specific action to be performed with respect to a data environment, such as provisioning, scaling, cloning, or hibernation of an instance. Upon receiving a request to one of the APIs, the web services portion of the interface layer may parse or otherwise analyze the request and determine the steps or actions required to address or process the call. For example, a web services call may be received that includes a request to create a data repository.

[0053] The interface layer 608 in at least one embodiment includes a scalable set of user-facing servers that can provide various APIs and return appropriate responses based on the API specifications. The interface layer can also include at least one API services layer, which in one embodiment is comprised of stateless, replicated servers that handle the external-facing user APIs. The interface layer can be responsible for web service front-end functions such as authenticating users based on credentials, authorizing users, throttling user requests to the API servers, validating user input, and marshaling or unmarshaling requests and responses. The API layer can also be responsible for reading and writing database configuration data to / from a managed data store in response to API calls. In many embodiments, the web services layer and / or API services layer are the only components visible to the outside world or visible and accessible to users of the control services. The servers in the web services layer can be stateless and horizontally scalable as known in the art. The API servers and persistent data stores can be distributed across multiple data centers in a region, for example, to allow the servers to survive a failure of a single data center.

[0054] As used herein, the term "data store" refers to any location consisting of one or more devices where data can be stored, accessed, and retrieved, among other elements, which may include any combination and number of data servers, databases, data storage devices, and data storage media in any standard, distributed, or cluster environment. The environment in one embodiment is a distributed computing environment utilizing multiple computer systems and components interconnected via communication links using one or more computer networks or direct connections. However, those skilled in the art will appreciate that such a system may operate similarly in systems having fewer or more components than those shown. Thus, the depictions of the systems herein should be considered exemplary in nature and not limiting of the scope of the present disclosure.

[0055] In embodiments utilizing a web server, the web server may run any of a variety of server or mid-tier applications, including an HTTP server, an FTP server, a CGI server, a data server, a Java server, and a business application server. The server may also execute programs or scripts in response to requests from user equipment, such as executing one or more web applications implemented as one or more scripts or programs written in programming languages ​​such as Java, C, C#, C++, scripting languages ​​such as Perl, Python, TCL, and combinations thereof. Servers may also include database servers, including but not limited to those commercially available from Oracle, Microsoft, Sybase, IBM, open source servers such as MySQL, Postgres, SQLite, MongoDB, and other servers capable of storing, searching, and accessing structured or unstructured data. Database servers may include table-based servers, document-based servers, unstructured servers, relational servers, non-relational servers, or combinations of these and / or other database servers.

[0056] The environment may include various data stores and other memory and storage media, as described above. In one particular set of embodiments, the information may reside in a storage area network (SAN) known to those skilled in the art. Where the system includes computerized devices, such as the control system or controller of the present disclosure, each such device may include hardware elements that may be electrically coupled via a bus, including, for example, at least one central processing unit (CPU), at least one input device (e.g., a mouse, keyboard, controller, touch-sensitive display element or keypad), and at least one output device (e.g., a display device, printer or speaker). Such a system may also include one or more storage devices, such as disk drives, magnetic tape drives, optical storage devices, and solid-state storage devices, such as random access memory (RAM) or read-only memory (ROM), as well as removable media devices, memory cards, flash cards, and the like.

[0057] Such computerized devices may also include computer-readable storage medium reading devices, communication devices (e.g., modems, network cards (wireless or wired), infrared communication devices), and working memories. The computer-readable storage medium reading devices may be connected to or configured to receive computer-readable storage media representing remote, local, fixed and / or removable storage devices as well as storage media for temporarily and / or more permanently storing, storing, transmitting and retrieving computer-readable information. The systems and various computerized devices also typically include a number of software applications, modules, services or other elements located within at least one working memory device, including an operating system and application programs such as client applications or web browsers. It should be understood that alternative embodiments may have numerous variations from those described above. For example, customized hardware may be used and / or specific elements may be implemented in hardware, software (including portable software such as applets) or both. Additionally, connections to other computing devices such as network input / output devices may be employed.

[0058] Storage media and other non-transitory computer readable media for storing the code, or portions of the code, may include any suitable media known or used in the art, such as, but not limited to, volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information such as computer readable instructions, data structures, program modules, or other data, including RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVDs) or other optical storage devices, magnetic cassettes, magnetic tapes, magnetic disk storage devices or other magnetic storage devices, or any other media that can be used to store the desired information and that can be accessed by a system device. Based on the disclosure and teachings provided herein, a person skilled in the art will recognize other ways and / or techniques for implementing the various embodiments.

[0059] Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense, however it will be apparent that various modifications and changes may be made thereto without departing from the broader spirit and scope of the invention as set forth in the appended claims.

Claims

1. Receiving data for one or more applications related to one or more operational functions of the data center; associating the one or more applications with one or more associated applications; detecting a failure of one or more components monitored by said one or more applications or said one or more associated applications; determining a cause of the fault based at least in part on the detected changes and contextual information related to the fault; applying at least one change to the one or more components based on the determined cause of the failure; and A computer-implemented method comprising:

2. The cause of the disorder is Observing and extracting said contextual information from a surrounding environment; generating one or more recommendations related to the disorder; 2. The computer-implemented method of claim 1 , wherein the at least one neural network is trained to determine the at least one feature of the network.

3. generating a service ticket identifying a root cause of the failure; presenting the service ticket and one or more corrective actions to be taken on the display interface; The computer-implemented method of claim 1 , further comprising:

4. 10. The computer-implemented method of claim 1, further comprising dynamically allocating one or more maintenance tasks associated with the fault based at least in part on trends in historical data.

5. 5. The computer-implemented method of claim 4, wherein the one or more maintenance tasks are dynamically assigned based further in part on one or more policies that define a skill set required to process the one or more maintenance tasks.

6. Associating the one or more applications with the one or more associated applications includes: associating one or more parent nodes of the one or more applications with one or more child nodes of the one or more related applications in a data structure; The computer-implemented method of claim 1 , further comprising:

7. Making at least one change to the one or more components based on the determined cause includes: making an adjustment to at least one operating condition for at least one of the one or more components; The computer-implemented method of claim 1 , further comprising:

8. At least one processor; When executed by the at least one processor, the at least one processor Receiving data for one or more applications related to one or more operational functions of the data center; associating the one or more applications with one or more associated applications; detecting a failure of one or more components monitored by said one or more applications or said one or more associated applications; determining a cause of the fault based at least in part on the detected changes and contextual information related to the fault; applying at least one change to the one or more components based on the determined cause of the failure; and A memory storing instructions for executing the A system comprising:

9. The cause of the disorder is Observing and extracting said contextual information from a surrounding environment; generating one or more recommendations related to the disorder; and determining the number of occurrences of the sigma-based feature using at least one neural network trained to determine the number of occurrences of the sigma-based feature. The system of claim 8.

10. The instructions, when executed by the at least one processor, cause the at least one processor to: generating a service ticket identifying a root cause of the failure; presenting the service ticket and one or more corrective actions to be taken on the display interface; The system of claim 8 , further comprising:

11. The instructions, when executed by the at least one processor, cause the at least one processor to: Dynamically allocating one or more maintenance tasks associated with the fault based at least in part on trends in historical data; The system of claim 8 , further comprising:

12. The system of claim 11 , wherein the one or more maintenance tasks are dynamically assigned based further in part on one or more policies that define a skill set required to handle the one or more maintenance tasks.

13. Associating the one or more applications with the one or more associated applications includes: associating one or more parent nodes of the one or more applications with one or more child nodes of the one or more related applications in a data structure; The system of claim 8 further comprising:

14. Making at least one change to the one or more components based on the determined cause includes: making an adjustment to at least one operating condition of at least one of the one or more components; The system of claim 8 further comprising:

15. 1. A non-transitory computer-readable medium that, when executed by at least one processor, causes the at least one processor to: Receiving data for one or more applications associated with one or more operational functions of the data center; associating the one or more applications with one or more associated applications; detecting a failure of one or more components monitored by said one or more applications or said one or more associated applications; determining a cause of the fault based at least in part on the detected changes and contextual information associated with the fault; applying at least one change to the one or more components based on the determined cause of the failure; and A non-transitory computer readable medium storing instructions for causing a

16. The cause of the disorder is Observing and extracting said contextual information from a surrounding environment; generating one or more recommendations related to the disorder; and determining the number of occurrences of the sigma-based feature using at least one neural network trained to determine the number of occurrences of the sigma-based feature.

16. The non-transitory computer readable medium of claim 15.

17. The instructions, when executed by the at least one processor, cause the at least one processor to: generating a service ticket identifying a root cause of the failure; presenting the service ticket and one or more corrective actions to be taken on the display interface; 20. The non-transitory computer readable medium of claim 15, further comprising:

18. The instructions, when executed by the at least one processor, cause the at least one processor to: dynamically allocating one or more maintenance tasks associated with the fault based at least in part on trends in historical data; 20. The non-transitory computer readable medium of claim 15, further comprising:

19. Associating the one or more applications with the one or more associated applications includes: associating one or more parent nodes of the one or more applications with one or more child nodes of the one or more related applications in a data structure; 20. The non-transitory computer readable medium of claim 15, further comprising:

20. Making at least one change to the one or more components based on the determined cause includes: making an adjustment to at least one operating condition of at least one of the one or more components; 20. The non-transitory computer readable medium of claim 15, further comprising:

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