One or more implementations relate to monitoring customer relationship management (CRM) systems.
Customer Relationship Management (CRM) systems are implemented to manage a company's relationships and interactions with customers and potential customers by compiling data from a range of different communication channels, including a company's website, telephone, email, live chat, marketing materials and social media. Due to the high volume of requests, it is often necessary to monitor CRM systems for adjustments that may be required to modify and balance database connections to ensure optimum CRM system operations.
In the following drawings like reference numbers are used to refer to like elements. Although the following figures depict various examples, one or more implementations are not limited to the examples depicted in the figures.
In the following description, numerous specific details are set forth. However, embodiments of the invention may be practiced without these specific details. In other instances, well-known structures and techniques have not been shown in detail in order not to obscure the understanding of this description.
Methods and systems are provided to facilitate prevent exhaustion of a database connection pool. In embodiments access to the connection pool to various clients is throttled upon a determination that the connection pool is at risk of exhaustion. It is contemplated that embodiments and their implementations are not merely limited to multi-tenant database system (“MTDBS”) and can be used in other environments, such as a client-server system, a mobile device, a personal computer (“PC”), a web services environment, etc. However, for the sake of brevity and clarity, throughout this document, embodiments are described with respect to a multi-tenant database system, such as Salesforce.com®, which is to be regarded as an example of an on-demand services environment. Other on-demand services environments include Salesforce® Exact Target Marketing Cloud™.
As used herein, a term multi-tenant database system refers to those systems in which various elements of hardware and software of the database system may be shared by one or more customers. For example, a given application server may simultaneously process requests for a great number of customers, and a given database table may store rows for a potentially much greater number of customers. As used herein, the term query plan refers to a set of steps used to access information in a database system.
Embodiments are described with reference to an embodiment in which techniques for facilitating management of data in an on-demand services environment are implemented in a system having an application server providing a front end for an on-demand database service capable of supporting multiple tenants, embodiments are not limited to multi-tenant databases nor deployment on application servers. Embodiments may be practiced using other database architectures, i.e., ORACLE®, DB2® by IBM and the like without departing from the scope of the embodiments claimed.
In one embodiment, computing device 120 may serve as a service provider core (e.g., Salesforce.com® core) in communication with one or more database(s) 140, one or more client computers 130A-N, over one or more network(s) 135, and any number and type of dedicated nodes. Computing device 120 may include (without limitation) server computers (e.g., cloud server computers, etc.), desktop computers, cluster-based computers, set-top boxes (e.g., Internet-based cable television set-top boxes, etc.), etc. Computing device 120 includes an operating system (“OS”) 106 serving as an interface between one or more hardware/physical resources of computing device 120 and one or more client devices 130A-130N, etc. Computing device 120 further includes processor(s) 102, memory 104, input/output (“I/O”) sources 108, such as touchscreens, touch panels, touch pads, virtual or regular keyboards, virtual or regular mice, etc.
In one embodiment, host organization 101 may further employ a production environment that is communicably interfaced with client devices 130A-N through host organization 101. Client devices 130A-N may include (without limitation) customer organization-based server computers, desktop computers, laptop computers, mobile computing devices, such as smartphones, tablet computers, personal digital assistants, e-readers, media Internet devices, smart televisions, television platforms, wearable devices (e.g., glasses, watches, bracelets, smartcards, jewelry, clothing items, etc.), media players, global positioning system-based navigation systems, cable setup boxes, etc.
In one embodiment, the illustrated multi-tenant database system 150 includes database(s) 140 to store (without limitation) information, relational tables, datasets, and underlying database records having tenant and user data therein on behalf of customer organizations 121A-N (e.g., tenants of multi-tenant database system 150 or their affiliated users). In alternative embodiments, a client-server computing architecture may be utilized in place of multi-tenant database system 150, or alternatively, a computing grid, or a pool of work servers, or some combination of hosted computing architectures may be utilized to carry out the computational workload and processing that is expected of host organization 101.
The illustrated multi-tenant database system 150 is shown to include one or more of underlying hardware, software, and logic elements 145 that implement, for example, database functionality and a code execution environment within host organization 101. In accordance with one embodiment, multi-tenant database system 150 further implements databases 140 to service database queries and other data interactions with the databases 140. In one embodiment, hardware, software, and logic elements 145 of multi-tenant database system 150 and its other elements, such as a distributed file store, a query interface, etc., may be separate and distinct from customer organizations (121A-121N) which utilize the services provided by host organization 101 by communicably interfacing with host organization 101 via network(s) 135 (e.g., cloud network, the Internet, etc.). In such a way, host organization 101 may implement on-demand services, on-demand database services, cloud computing services, etc., to subscribing customer organizations 121A-121N.
In some embodiments, host organization 101 receives input and other requests from a plurality of customer organizations 121A-N over one or more networks 135; for example, incoming search queries, database queries, application programming interface (“API”) requests, interactions with displayed graphical user interfaces and displays at client devices 130A-N, or other inputs may be received from customer organizations 121A-N to be processed against multi-tenant database system 150 as queries via a query interface and stored at a distributed file store, pursuant to which results are then returned to an originator or requestor, such as a user of client devices 130A-N at any of customer organizations 121A-N.
As aforementioned, in one embodiment, each customer organization 121A-N is an entity selected from a group consisting of a separate and distinct remote organization, an organizational group within host organization 101, a business partner of host organization 101, a customer organization 121A-N that subscribes to cloud computing services provided by host organization 101, etc.
In one embodiment, requests are received at, or submitted to, a web server within host organization 101. Host organization 101 may receive a variety of requests for processing by host organization 101 and its multi-tenant database system 150. For example, incoming requests received at the web server may specify which services from host organization 101 are to be provided, such as query requests, search request, status requests, database transactions, graphical user interface requests and interactions, processing requests to retrieve, update, or store data on behalf of one of customer organizations 121A-N, code execution requests, and so forth. Further, the web-server at host organization 101 may be responsible for receiving requests from various customer organizations 121A-N via network(s) 135 on behalf of the query interface and for providing a web-based interface or other graphical displays to one or more end-user client devices 130A-N or machines originating such data requests.
Further, host organization 101 may implement a request interface via the web server or as a stand-alone interface to receive requests packets or other requests from the client devices 130A-N. The request interface may further support the return of response packets or other replies and responses in an outgoing direction from host organization 101 to one or more client devices 130A-N.
It is to be noted that any references to software codes, data and/or metadata (e.g., Customer Relationship Model (“CRM”) data and/or metadata, etc.), tables (e.g., custom object table, unified index tables, description tables, etc.), computing devices (e.g., server computers, desktop computers, mobile computers, such as tablet computers, smartphones, etc.), software development languages, applications, and/or development tools or kits (e.g., Force.com®, Force.com Apex™ code, JavaScript™, jQuery™, Developerforce™, Visualforce™, Service Cloud Console Integration Toolkit™ (“Integration Toolkit” or “Toolkit”), Platform on a Service™ (“PaaS”), Chatter® Groups, Sprint Planner®, MS Project®, etc.), domains (e.g., Google®, Facebook®, LinkedIn®, Skype®, etc.), etc., discussed in this document are merely used as examples for brevity, clarity, and ease of understanding and that embodiments are not limited to any particular number or type of data, metadata, tables, computing devices, techniques, programming languages, software applications, software development tools/kits, etc.
It is to be noted that terms like “node”, “computing node”, “server”, “server device”, “cloud computer”, “cloud server”, “cloud server computer”, “machine”, “host machine”, “device”, “computing device”, “computer”, “computing system”, “multi-tenant on-demand data system”, “multi-tenant database system” and the like, may be used interchangeably throughout this document. It is to be further noted that terms like “code”, “software code”, “application”, “software application”, “program”, “software program”, “package”, “software code”, “code”, and “software package” may be used interchangeably throughout this document. Moreover, terms like “job”, “input”, “request”, and “message” may be used interchangeably throughout this document.
According to one embodiment, connection pool 210 includes one or more application servers 212 (e.g., 212(A)-212(N)), each managing a plurality of connections 214. In such an embodiment, application servers 212 manage access by clients to database 205 resources via the connections 214. Thus, connections operate as traffic lanes to database 205. In a further embodiment, the database system 150 resources may be configured as one or more Point of Developments (PODs) (or instance machine). In this embodiment, an instance machine (or instance) comprises a cluster of infrastructure (e.g., servers, software, networking equipment, etc.) that operate collectively to serve client 220 traffic. Accordingly, two or more of servers 212 may be combined to operate as a cluster of servers, resulting in the pooling of connections 214 within the cluster.
However, while client 220 traffic, load and consumed resources may be dynamic (e.g., variable over time), the database system 150 resources are relatively static. Thus the maximum number of connections implemented in conventional systems are fixed, which may restrict the magnitude of traffic to the database. Connection pool manager 250 manages the configuration of connection pool 210. In one embodiment, connection pool manager 250 automatically adjusts the connections 214 in connection pool 210, or a cluster of application server 212 connections. Accordingly, connection pool manager 250 configures connection pool 210 for automatic adjustment to match traffic conditions.
However conventional connection pool management mechanisms have not been able to effectively manage all pool traffic conditions. For instance, a condition referred to as connection pool exhaustion may occur when there are no available connections in pool 210. Although connection pool exhaustion incidents may occur frequently, there are currently no mechanisms to prevent such incidents. Moreover, there is no automatic process to determine which clients are actually using the connection pool, or track how much each client is utilizing the connection pool, in order to detect overuse of the connection pool by clients that may causing the incidents.
According to one embodiment, connection pool manager 250 includes an anomaly detection mechanism 255 that monitors connection pool 210 to detect whether conditions exist that could lead to connection pool exhaustion. In such an embodiment, anomaly detection mechanism 255 determines whether a client request will cause connection pool exhaustion on a connection pool cluster. In a further embodiment, anomaly detection mechanism 255 may throttle client access requests by withholding a portion of available connections upon determining that the request swill cause connection pool exhaustion.
Monitor 320 monitors the current data to determine whether one or more connection pool clusters are at risk of connection pool exhaustion condition (e.g., connection pool is in trouble). According to one embodiment, monitor 320 may indicate that a connection pool 210 is in trouble upon a determination that pool utilization is greater than a configured threshold utilization value (e.g., pool utilization>X) and a number of clients waiting to obtain a connection is greater than a configured threshold of clients (e.g., clients waiting>Y).
In a further embodiment, connection pool exhaustion may be categorized as “sustained” or “intermittent”. A connection pool 210 is considered to be in sustained trouble upon a determination that the pool has been in trouble more than a first configured threshold percentage of intervals (e.g., pool in trouble>A times in past M intervals). Further, a connection pool 210 is considered to be in intermittent trouble upon a determination that the pool has been in trouble more than a second predetermined threshold percentage of intervals that is less than the first configured threshold percentage of intervals (e.g., pool in trouble>B times in past N intervals, where B<A and N>M). In a further embodiment, monitor 320 may trigger an alert to a GUI upon detecting that a connection pool 210 is in trouble, or in a state of exhaustion.
Analysis engine 330, upon a determination that the connection pool is in trouble, examines the historical data to determine usage by clients that has led to, or may lead to connection pool 210 becoming at risk of, connection pool exhaustion (e.g., candidate clients that may be causing a risk of connection exhaustion (or offenders)). According to one embodiment, analysis engine 330 evaluates all incoming client request source data to connection pool 210. In such an embodiment, analysis engine 330 evaluates the received access requests to determine whether a client is to be categorized as an offender. In a further embodiment, the access request includes data indicating a client organization (or org) from which the request has been received, a Uniform Resource Identifier (URI), timestamp and application servers to which the request was made. Based on these identifiers, analysis engine 330 may determine total utilization by each client to determine whether one or more clients are to be categorized as an offender.
In one embodiment, client's that are offenders may be categorized as “sustained” or “intermittent” offenders. In such an embodiment, a candidate client is designated as a sustained offender upon a determination that the client utilization is greater than a configured threshold percentage of intervals (e.g., client usage>P % in the last M intervals). A candidate client is designated as an intermittent offender upon a determination that a client weight is greater than a configured threshold (e.g., client weight>Q, where the weight is based on the timestamp, utilization, and properties from the candidate).
In one embodiment, the threshold parameters X, Y, A, B, M, N, P, Q are configured based on an examination of the historical data. In such an embodiment, analysis engine 330 learns from previous exhaustion incidents and dynamically configures anomaly detection mechanism 255 in response to environment changes. In a further embodiment, client offenders may be converted between “sustained” and “intermittent”.
Throttle engine 340 throttles access to clients identified as an offender. According to one embodiment, throttle engine 340 throttles access based on one or more throttle rules. In such an embodiment, the throttle rules provides a throttle access rate limit (e.g., requests per second) for an offending client, as well as an expiration date for throttling conditions.
In a further embodiment, the throttling rules may expire or be extended based on the connection pool conditions indicated by the continued update of the source data. Accordingly an offending client's throttling rate may be dynamically adjusted, or completely restored, based on the connection pool status and/or the offenders severity. In a further embodiment the throttling rules may be controlled at a server 212 cluster level. However in other embodiments, the throttling rules may be controlled at a server 212 level. In such embodiments, exceptions may be made for some offender clients to prevent the throttling of the access rate.
Method 400 begins at processing block 410, source data is retrieved for a connection pool (e.g., connection pool cluster) and stored. At processing block 420, the data is monitored to detect connection pool traffic conditions. At decision block 430, a determination is made as to whether the connection pool is in trouble. If not, control is returned to processing block 420, where the data continues to be monitored.
However upon a determination at decision block 430 that the connection pool is in trouble, client access requests included in the data are analyzed to determine whether there are one or more offenders causing the connection pool to be in trouble, processing block 440. At processing block 450, the access rate limit of the offending clients is throttled based on whether a client is a sustained or intermittent offender.
At decision block 460, a determination is made as to whether the connection pool is still in trouble. If so, control is returned to processing block 450, where the offenders' access rate limit remains throttled. As discussed above, the throttled rate may be continuously adjusted based on a real-time receipt of connection pool data. Upon a determination at decision block 460 the connection pool is no longer in trouble, the throttle of the offender's access rate is removed, processing block 470.
The above-described anomaly detection mechanism enables providing comprehensive connection pool details to track, investigate and perform diagnosis, balance resources across clients using connections and identify potential connection pool incidents, as well as those that are happening. Additionally, the anomaly detection mechanism identifies connection holders commonly from a uniform resource indicator (URI) associated with and endpoint (or tenant), resolves and prevents connection pool exhaustion by automatically throttling requests, and provides data for connection pool health visualization and comparison. Further, the anomaly detection mechanism reduces the number of the manual interventions from to resolve connection pool exhaustion.
The exemplary computer system 900 includes a processor 902, a main memory 504 (e.g., read-only memory (ROM), flash memory, dynamic random access memory (DRAM) such as synchronous DRAM (SDRAM) or Rambus DRAM (RDRAM), etc., static memory such as flash memory, static random access memory (SRAM), volatile but high-data rate RAM, etc.), and a secondary memory 918 (e.g., a persistent storage device including hard disk drives and persistent multi-tenant data base implementations), which communicate with each other via a bus 930. Main memory 904 includes emitted execution data 924 (e.g., data emitted by a logging framework) and one or more trace preferences 923 which operate in conjunction with processing logic 926 and processor 902 to perform the methodologies discussed herein.
Processor 902 represents one or more general-purpose processing devices such as a microprocessor, central processing unit, or the like. More particularly, the processor 902 may be a complex instruction set computing (CISC) microprocessor, reduced instruction set computing (RISC) microprocessor, very long instruction word (VLIW) microprocessor, processor implementing other instruction sets, or processors implementing a combination of instruction sets. Processor 902 may also be one or more special-purpose processing devices such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), network processor, or the like. Processor 902 is configured to execute the processing logic 926 for performing the operations as described with reference to
The computer system 900 may further include a network interface card 908. The computer system 900 also may include a user interface 910 (such as a video display unit, a liquid crystal display (LCD), or a cathode ray tube (CRT)), an alphanumeric input device 912 (e.g., a keyboard), a cursor control device 914 (e.g., a mouse), and a signal generation device 916 (e.g., an integrated speaker). The computer system 900 may further include peripheral device 936 (e.g., wireless or wired communication devices, memory devices, storage devices, audio processing devices, video processing devices, etc. The computer system 900 may further include a Hardware based API logging framework 934 capable of executing incoming requests for services and emitting execution data responsive to the fulfillment of such incoming requests.
The secondary memory 918 may include a machine-readable storage medium (or more specifically a machine-accessible storage medium) 931 on which is stored one or more sets of instructions (e.g., software 922) embodying any one or more of the methodologies as described with reference to
Portions of various embodiments may be provided as a computer program product, which may include a computer-readable medium having stored thereon computer program instructions, which may be used to program a computer (or other electronic devices) to perform a process according to the embodiments. The machine-readable medium may include, but is not limited to, floppy diskettes, optical disks, compact disk read-only memory (CD-ROM), and magneto-optical disks, ROM, RAM, erasable programmable read-only memory (EPROM), electrically EPROM (EEPROM), magnet or optical cards, flash memory, or other type of media/machine-readable medium suitable for storing electronic instructions.
The techniques shown in the figures can be implemented using code and data stored and executed on one or more electronic devices (e.g., an end station, a network element). Such electronic devices store and communicate (internally and/or with other electronic devices over a network) code and data using computer-readable media, such as non-transitory computer-readable storage media (e.g., magnetic disks; optical disks; random access memory; read only memory; flash memory devices; phase-change memory) and transitory computer-readable transmission media (e.g., electrical, optical, acoustical or other form of propagated signals—such as carrier waves, infrared signals, digital signals). In addition, such electronic devices typically include a set of one or more processors coupled to one or more other components, such as one or more storage devices (non-transitory machine-readable storage media), user input/output devices (e.g., a keyboard, a touchscreen, and/or a display), and network connections. The coupling of the set of processors and other components is typically through one or more busses and bridges (also termed as bus controllers). Thus, the storage device of a given electronic device typically stores code and/or data for execution on the set of one or more processors of that electronic device. Of course, one or more parts of an embodiment may be implemented using different combinations of software, firmware, and/or hardware.
Environment 1010 is an environment in which an on-demand database service exists. User system 1012 may be any machine or system that is used by a user to access a database user system. For example, any of user systems 1012 can be a handheld computing device, a mobile phone, a laptop computer, a workstation, and/or a network of computing devices. As illustrated in herein
An on-demand database service, such as system 1016, is a database system that is made available to outside users that do not need to necessarily be concerned with building and/or maintaining the database system, but instead may be available for their use when the users need the database system (e.g., on the demand of the users). Some on-demand database services may store information from one or more tenants stored into tables of a common database image to form a multi-tenant database system (MTS). Accordingly, “on-demand database service 1016” and “system 1016” will be used interchangeably herein. A database image may include one or more database objects. A relational database management system (RDMS) or the equivalent may execute storage and retrieval of information against the database object(s). Application platform 1018 may be a framework that allows the applications of system 1016 to run, such as the hardware and/or software, e.g., the operating system. In an embodiment, on-demand database service 1016 may include an application platform 1018 that enables creation, managing and executing one or more applications developed by the provider of the on-demand database service, users accessing the on-demand database service via user systems 1012, or third party application developers accessing the on-demand database service via user systems 1012.
The users of user systems 1012 may differ in their respective capacities, and the capacity of a particular user system 1012 might be entirely determined by permissions (permission levels) for the current user. For example, where a salesperson is using a particular user system 1012 to interact with system 1016, that user system has the capacities allotted to that salesperson. However, while an administrator is using that user system to interact with system 1016, that user system has the capacities allotted to that administrator. In systems with a hierarchical role model, users at one permission level may have access to applications, data, and database information accessible by a lower permission level user, but may not have access to certain applications, database information, and data accessible by a user at a higher permission level. Thus, different users will have different capabilities with regard to accessing and modifying application and database information, depending on a user's security or permission level.
Network 1014 is any network or combination of networks of devices that communicate with one another. For example, network 1014 can be any one or any combination of a LAN (local area network), WAN (wide area network), telephone network, wireless network, point-to-point network, star network, token ring network, hub network, or other appropriate configuration. As the most common type of computer network in current use is a TCP/IP (Transfer Control Protocol and Internet Protocol) network, such as the global internetwork of networks often referred to as the “Internet” with a capital “I,” that network will be used in many of the examples herein. However, it should be understood that the networks that one or more implementations might use are not so limited, although TCP/IP is a frequently implemented protocol.
User systems 1012 might communicate with system 1016 using TCP/IP and, at a higher network level, use other common Internet protocols to communicate, such as HTTP, FTP, AFS, WAP, etc. In an example where HTTP is used, user system 1012 might include an HTTP client commonly referred to as a “browser” for sending and receiving HTTP messages to and from an HTTP server at system 1016. Such an HTTP server might be implemented as the sole network interface between system 1016 and network 1014, but other techniques might be used as well or instead. In some implementations, the interface between system 1016 and network 1014 includes load-sharing functionality, such as round-robin HTTP request distributors to balance loads and distribute incoming HTTP requests evenly over a plurality of servers. At least as for the users that are accessing that server, each of the plurality of servers has access to the MTS' data; however, other alternative configurations may be used instead.
In one embodiment, system 1016, shown in
One arrangement for elements of system 1016 is shown in
Several elements in the system shown in
According to one embodiment, each user system 1012 and all of its components are operator configurable using applications, such as a browser, including computer code run using a central processing unit such as an Intel Core® processor or the like. Similarly, system 1016 (and additional instances of an MTS, where more than one is present) and all of their components might be operator configurable using application(s) including computer code to run using a central processing unit such as processor system 1017, which may include an Intel Pentium® processor or the like, and/or multiple processor units. A computer program product embodiment includes a machine-readable storage medium (media) having instructions stored thereon/in which can be used to program a computer to perform any of the processes of the embodiments described herein. Computer code for operating and configuring system 1016 to intercommunicate and to process webpages, applications and other data and media content as described herein are preferably downloaded and stored on a hard disk, but the entire program code, or portions thereof, may also be stored in any other volatile or non-volatile memory medium or device as is well known, such as a ROM or RAM, or provided on any media capable of storing program code, such as any type of rotating media including floppy disks, optical discs, digital versatile disk (DVD), compact disk (CD), microdrive, and magneto-optical disks, and magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data. Additionally, the entire program code, or portions thereof, may be transmitted and downloaded from a software source over a transmission medium, e.g., over the Internet, or from another server, as is well known, or transmitted over any other conventional network connection as is well known (e.g., extranet, VPN, LAN, etc.) using any communication medium and protocols (e.g., TCP/IP, HTTP, HTTPS, Ethernet, etc.) as are well known. It will also be appreciated that computer code for implementing embodiments can be implemented in any programming language that can be executed on a client system and/or server or server system such as, for example, C, C++, HTML, any other markup language, Java™, JavaScript, ActiveX, any other scripting language, such as VBScript, and many other programming languages as are well known may be used. (Java™ is a trademark of Sun Microsystems, Inc.).
According to one embodiment, each system 1016 is configured to provide webpages, forms, applications, data and media content to user (client) systems 1012 to support the access by user systems 1012 as tenants of system 1016. As such, system 1016 provides security mechanisms to keep each tenant's data separate unless the data is shared. If more than one MTS is used, they may be located in close proximity to one another (e.g., in a server farm located in a single building or campus), or they may be distributed at locations remote from one another (e.g., one or more servers located in city A and one or more servers located in city B). As used herein, each MTS could include one or more logically and/or physically connected servers distributed locally or across one or more geographic locations. Additionally, the term “server” is meant to include a computer system, including processing hardware and process space(s), and an associated storage system and database application (e.g., OODBMS or RDBMS) as is well known in the art. It should also be understood that “server system” and “server” are often used interchangeably herein. Similarly, the database object described herein can be implemented as single databases, a distributed database, a collection of distributed databases, a database with redundant online or offline backups or other redundancies, etc., and might include a distributed database or storage network and associated processing intelligence.
User system 1012, network 1014, system 1016, tenant data storage 1022, and system data storage 1024 were discussed above in
Application platform 1018 includes an application setup mechanism 1138 that supports application developers' creation and management of applications, which may be saved as metadata into tenant data storage 1022 by save routines 1136 for execution by subscribers as one or more tenant process spaces 1104 managed by tenant management process 1110 for example. Invocations to such applications may be coded using PL/SOQL 1134 that provides a programming language style interface extension to API 1132. A detailed description of some PL/SOQL language embodiments is discussed in commonly owned U.S. Pat. No. 7,730,478 entitled, “Method and System for Allowing Access to Developed Applicants via a Multi-Tenant Database On-Demand Database Service”, issued Jun. 1, 2010 to Craig Weissman, which is incorporated in its entirety herein for all purposes. Invocations to applications may be detected by one or more system processes, which manage retrieving application metadata 1116 for the subscriber making the invocation and executing the metadata as an application in a virtual machine.
Each application server 1100 may be communicably coupled to database systems, e.g., having access to system data 1025 and tenant data 1023, via a different network connection. For example, one application server 11001 might be coupled via the network 1014 (e.g., the Internet), another application server 1100N-1 might be coupled via a direct network link, and another application server 1100N might be coupled by yet a different network connection. Transfer Control Protocol and Internet Protocol (TCP/IP) are typical protocols for communicating between application servers 1100 and the database system. However, it will be apparent to one skilled in the art that other transport protocols may be used to optimize the system depending on the network interconnect used.
In certain embodiments, each application server 1100 is configured to handle requests for any user associated with any organization that is a tenant. Because it is desirable to be able to add and remove application servers from the server pool at any time for any reason, there is preferably no server affinity for a user and/or organization to a specific application server 1100. In one embodiment, therefore, an interface system implementing a load balancing function (e.g., an F5 Big-IP load balancer) is communicably coupled between the application servers 1100 and the user systems 1012 to distribute requests to the application servers 1100. In one embodiment, the load balancer uses a least connections algorithm to route user requests to the application servers 1100. Other examples of load balancing algorithms, such as round robin and observed response time, also can be used. For example, in certain embodiments, three consecutive requests from the same user could hit three different application servers 1100, and three requests from different users could hit the same application server 1100. In this manner, system 1016 is multi-tenant, wherein system 1016 handles storage of, and access to, different objects, data and applications across disparate users and organizations.
As an example of storage, one tenant might be a company that employs a sales force where each salesperson uses system 1016 to manage their sales process. Thus, a user might maintain contact data, leads data, customer follow-up data, performance data, goals and progress data, etc., all applicable to that user's personal sales process (e.g., in tenant data storage 1022). In an example of a MTS arrangement, since all of the data and the applications to access, view, modify, report, transmit, calculate, etc., can be maintained and accessed by a user system having nothing more than network access, the user can manage his or her sales efforts and cycles from any of many different user systems. For example, if a salesperson is visiting a customer and the customer has Internet access in their lobby, the salesperson can obtain critical updates as to that customer while waiting for the customer to arrive in the lobby.
While each user's data might be separate from other users' data regardless of the employers of each user, some data might be organization-wide data shared or accessible by a plurality of users or all of the users for a given organization that is a tenant. Thus, there might be some data structures managed by system 1016 that are allocated at the tenant level while other data structures might be managed at the user level. Because an MTS might support multiple tenants including possible competitors, the MTS should have security protocols that keep data, applications, and application use separate. Also, because many tenants may opt for access to an MTS rather than maintain their own system, redundancy, up-time, and backup are additional functions that may be implemented in the MTS. In addition to user-specific data and tenant specific data, system 1016 might also maintain system level data usable by multiple tenants or other data. Such system level data might include industry reports, news, postings, and the like that are sharable among tenants.
In certain embodiments, user systems 1012 (which may be client systems) communicate with application servers 1100 to request and update system-level and tenant-level data from system 1016 that may require sending one or more queries to tenant data storage 1022 and/or system data storage 1024. System 1016 (e.g., an application server 1100 in system 1016) automatically generates one or more SQL statements (e.g., one or more SQL queries) that are designed to access the desired information. System data storage 1024 may generate query plans to access the requested data from the database.
Each database can generally be viewed as a collection of objects, such as a set of logical tables, containing data fitted into predefined categories. A “table” is one representation of a data object, and may be used herein to simplify the conceptual description of objects and custom objects. It should be understood that “table” and “object” may be used interchangeably herein. Each table generally contains one or more data categories logically arranged as columns or fields in a viewable schema. Each row or record of a table contains an instance of data for each category defined by the fields. For example, a CRM database may include a table that describes a customer with fields for basic contact information such as name, address, phone number, fax number, etc. Another table might describe a purchase order, including fields for information such as customer, product, sale price, date, etc. In some multi-tenant database systems, standard entity tables might be provided for use by all tenants. For CRM database applications, such standard entities might include tables for Account, Contact, Lead, and Opportunity data, each containing pre-defined fields. It should be understood that the word “entity” may also be used interchangeably herein with “object” and “table”.
In some multi-tenant database systems, tenants may be allowed to create and store custom objects, or they may be allowed to customize standard entities or objects, for example by creating custom fields for standard objects, including custom index fields. U.S. patent application Ser. No. 10/817,161, filed Apr. 2, 2004, entitled “Custom Entities and Fields in a Multi-Tenant Database System”, and which is hereby incorporated herein by reference, teaches systems and methods for creating custom objects as well as customizing standard objects in a multi-tenant database system. In certain embodiments, for example, all custom entity data rows are stored in a single multi-tenant physical table, which may contain multiple logical tables per organization. It is transparent to customers that their multiple “tables” are in fact stored in one large table or that their data may be stored in the same table as the data of other customers.
Any of the above embodiments may be used alone or together with one another in any combination. Embodiments encompassed within this specification may also include embodiments that are only partially mentioned or alluded to or are not mentioned or alluded to at all in this brief summary or in the abstract. Although various embodiments may have been motivated by various deficiencies with the prior art, which may be discussed or alluded to in one or more places in the specification, the embodiments do not necessarily address any of these deficiencies. In other words, different embodiments may address different deficiencies that may be discussed in the specification. Some embodiments may only partially address some deficiencies or just one deficiency that may be discussed in the specification, and some embodiments may not address any of these deficiencies.
While one or more implementations have been described by way of example and in terms of the specific embodiments, it is to be understood that one or more implementations are not limited to the disclosed embodiments. To the contrary, it is intended to cover various modifications and similar arrangements as would be apparent to those skilled in the art. Therefore, the scope of the appended claims should be accorded the broadest interpretation so as to encompass all such modifications and similar arrangements. It is to be understood that the above description is intended to be illustrative, and not restrictive.
This application is a continuation of application Ser. No. 16/660,904, filed Oct. 23, 2019, the entire contents of which are hereby incorporated herein by reference.
Number | Name | Date | Kind |
---|---|---|---|
4239983 | Edwards | Dec 1980 | A |
4334320 | Liman | Jun 1982 | A |
5577188 | Zhu | Nov 1996 | A |
5608872 | Schwartz et al. | Mar 1997 | A |
5649104 | Carleton et al. | Jul 1997 | A |
5715450 | Ambrose et al. | Feb 1998 | A |
5761419 | Schwartz et al. | Jun 1998 | A |
5819038 | Carleton et al. | Oct 1998 | A |
5821937 | Tonelli et al. | Oct 1998 | A |
5831610 | Tonelli et al. | Nov 1998 | A |
5873096 | Lim et al. | Feb 1999 | A |
5918159 | Fomukong et al. | Jun 1999 | A |
5963953 | Cram et al. | Oct 1999 | A |
6092083 | Brodersen et al. | Jul 2000 | A |
6169534 | Raffel et al. | Jan 2001 | B1 |
6178425 | Brodersen et al. | Jan 2001 | B1 |
6189011 | Lim et al. | Feb 2001 | B1 |
6216135 | Brodersen et al. | Apr 2001 | B1 |
6233617 | Rothwein et al. | May 2001 | B1 |
6266669 | Brodersen et al. | Jul 2001 | B1 |
6295530 | Ritchie et al. | Sep 2001 | B1 |
6324568 | Diec | Nov 2001 | B1 |
6324693 | Brodersen et al. | Nov 2001 | B1 |
6336137 | Lee et al. | Jan 2002 | B1 |
D454139 | Feldcamp | Mar 2002 | S |
6367077 | Brodersen et al. | Apr 2002 | B1 |
6393605 | Loomans | May 2002 | B1 |
6405220 | Brodersen et al. | Jun 2002 | B1 |
6434550 | Warner et al. | Aug 2002 | B1 |
6446089 | Brodersen et al. | Sep 2002 | B1 |
6535909 | Rust | Mar 2003 | B1 |
6549908 | Loomans | Apr 2003 | B1 |
6553563 | Ambrose et al. | Apr 2003 | B2 |
6560461 | Fomukong et al. | May 2003 | B1 |
6574635 | Stauber et al. | Jun 2003 | B2 |
6577726 | Huang et al. | Jun 2003 | B1 |
6601087 | Zhu et al. | Jul 2003 | B1 |
6604117 | Lim et al. | Aug 2003 | B2 |
6604128 | Diec | Aug 2003 | B2 |
6609150 | Lee et al. | Aug 2003 | B2 |
6621834 | Scherpbier et al. | Sep 2003 | B1 |
6654032 | Zhu et al. | Nov 2003 | B1 |
6665648 | Brodersen et al. | Dec 2003 | B2 |
6665655 | Warner et al. | Dec 2003 | B1 |
6684438 | Brodersen et al. | Feb 2004 | B2 |
6697849 | Carlson | Feb 2004 | B1 |
6711565 | Subramaniam et al. | Mar 2004 | B1 |
6717912 | Lemyre | Apr 2004 | B1 |
6724399 | Katchour et al. | Apr 2004 | B1 |
6728702 | Subramaniam et al. | Apr 2004 | B1 |
6728960 | Loomans | Apr 2004 | B1 |
6732095 | Warshavsky et al. | May 2004 | B1 |
6732100 | Brodersen et al. | May 2004 | B1 |
6732111 | Brodersen et al. | May 2004 | B2 |
6754681 | Brodersen et al. | Jun 2004 | B2 |
6763351 | Subramaniam et al. | Jul 2004 | B1 |
6763501 | Zhu et al. | Jul 2004 | B1 |
6768904 | Kim | Jul 2004 | B2 |
6782383 | Subramaniam et al. | Aug 2004 | B2 |
6804330 | Jones et al. | Oct 2004 | B1 |
6826565 | Ritchie et al. | Nov 2004 | B2 |
6826582 | Chatterjee et al. | Nov 2004 | B1 |
6826745 | Coker et al. | Nov 2004 | B2 |
6829655 | Huang et al. | Dec 2004 | B1 |
6842748 | Warner et al. | Jan 2005 | B1 |
6850895 | Brodersen et al. | Feb 2005 | B2 |
6850949 | Warner et al. | Feb 2005 | B2 |
6862623 | Odhner | Mar 2005 | B1 |
7289976 | Kihneman et al. | Oct 2007 | B2 |
7299976 | Nakada | Nov 2007 | B2 |
7340411 | Cook | Mar 2008 | B2 |
7388839 | Chafle | Jun 2008 | B2 |
7620655 | Larsson et al. | Nov 2009 | B2 |
7925756 | Riddle | Apr 2011 | B1 |
8244865 | Burke | Aug 2012 | B2 |
8862837 | Marshak | Oct 2014 | B1 |
9785687 | Shivarudraiah | Oct 2017 | B2 |
9942312 | Langseth | Apr 2018 | B1 |
10051046 | Zacharski | Aug 2018 | B1 |
10191922 | Michael | Jan 2019 | B2 |
10505857 | Bandlamudi | Dec 2019 | B1 |
10657064 | Khan | May 2020 | B1 |
10659371 | Jain | May 2020 | B1 |
10931530 | Rzehak | Feb 2021 | B1 |
11151150 | Obembe | Oct 2021 | B2 |
20010044791 | Richter et al. | Nov 2001 | A1 |
20020000355 | Hattori | Jan 2002 | A1 |
20020022986 | Coker et al. | Feb 2002 | A1 |
20020003557 | Brodersen et al. | Mar 2002 | A1 |
20020029161 | Brodersen et al. | Mar 2002 | A1 |
20020029376 | Ambrose et al. | Mar 2002 | A1 |
20020042264 | Kim | Apr 2002 | A1 |
20020042843 | Diec | Apr 2002 | A1 |
20020072951 | Lee et al. | Jun 2002 | A1 |
20020082892 | Raffel et al. | Jun 2002 | A1 |
20020129352 | Brodersen et al. | Sep 2002 | A1 |
20020140731 | Subramaniam et al. | Oct 2002 | A1 |
20020143997 | Huang et al. | Oct 2002 | A1 |
20020152102 | Brodersen et al. | Oct 2002 | A1 |
20020161734 | Stauber et al. | Oct 2002 | A1 |
20020162090 | Parnell et al. | Oct 2002 | A1 |
20020165742 | Robins | Nov 2002 | A1 |
20030004971 | Gong et al. | Jan 2003 | A1 |
20030018705 | Chen et al. | Jan 2003 | A1 |
20030018830 | Chen et al. | Jan 2003 | A1 |
20030066031 | Laane | Apr 2003 | A1 |
20030066032 | Ramachadran et al. | Apr 2003 | A1 |
20030069936 | Warner et al. | Apr 2003 | A1 |
20030070000 | Coker et al. | Apr 2003 | A1 |
20030070004 | Mukundan et al. | Apr 2003 | A1 |
20030070005 | Mukundan et al. | Apr 2003 | A1 |
20030074418 | Coker | Apr 2003 | A1 |
20030088545 | Subramaniam et al. | May 2003 | A1 |
20030120675 | Stauber et al. | Jun 2003 | A1 |
20030151633 | George et al. | Aug 2003 | A1 |
20030159136 | Huang et al. | Aug 2003 | A1 |
20030187921 | Diec | Oct 2003 | A1 |
20030189600 | Gune et al. | Oct 2003 | A1 |
20030191743 | Brodersen et al. | Oct 2003 | A1 |
20030204427 | Gune et al. | Oct 2003 | A1 |
20030206192 | Chen et al. | Nov 2003 | A1 |
20030225730 | Warner et al. | Dec 2003 | A1 |
20040001092 | Rothwein et al. | Jan 2004 | A1 |
20040010489 | Rio | Jan 2004 | A1 |
20040015981 | Coker et al. | Jan 2004 | A1 |
20040027388 | Berg et al. | Feb 2004 | A1 |
20040088413 | Bhogi | May 2004 | A1 |
20040128001 | Levin et al. | Jul 2004 | A1 |
20040139433 | Blythe | Jul 2004 | A1 |
20040153545 | Pandya | Aug 2004 | A1 |
20040186860 | Lee et al. | Sep 2004 | A1 |
20040193510 | Catahan, Jr. et al. | Sep 2004 | A1 |
20040199489 | Barnes-Leon et al. | Oct 2004 | A1 |
20040199536 | Barnes-Leon et al. | Oct 2004 | A1 |
20040199543 | Braud et al. | Oct 2004 | A1 |
20040215733 | Gondhalekar | Oct 2004 | A1 |
20040249854 | Barnes-Leon et al. | Dec 2004 | A1 |
20040260534 | Pak et al. | Dec 2004 | A1 |
20040260659 | Chan et al. | Dec 2004 | A1 |
20040268299 | Lei et al. | Dec 2004 | A1 |
20050015644 | Chu et al. | Jan 2005 | A1 |
20050050555 | Exley et al. | Mar 2005 | A1 |
20050074236 | Urimindi | Apr 2005 | A1 |
20050088976 | Chafle | Apr 2005 | A1 |
20050091098 | Brodersen et al. | Apr 2005 | A1 |
20050144267 | Maron | Jun 2005 | A1 |
20050144505 | Takeuchi | Jun 2005 | A1 |
20050262183 | Colrain | Nov 2005 | A1 |
20060029037 | Chen | Feb 2006 | A1 |
20060074970 | Narayanan | Apr 2006 | A1 |
20060095572 | Burke | May 2006 | A1 |
20060120411 | Basu | Jun 2006 | A1 |
20070076585 | Kim | Apr 2007 | A1 |
20070076586 | Kim | Apr 2007 | A1 |
20070118630 | Hashimoto | May 2007 | A1 |
20070223388 | Arad | Sep 2007 | A1 |
20070268910 | Shen | Nov 2007 | A1 |
20070280111 | Lund | Dec 2007 | A1 |
20080016233 | Schneider | Jan 2008 | A1 |
20080175226 | Alperovitch | Jul 2008 | A1 |
20090177744 | Marlow et al. | Jul 2009 | A1 |
20090210360 | Sankar | Aug 2009 | A1 |
20100061476 | Kim | Mar 2010 | A1 |
20100100307 | Kim | Apr 2010 | A1 |
20100217872 | Martchenko | Aug 2010 | A1 |
20100322089 | Raja | Dec 2010 | A1 |
20100322237 | Raja | Dec 2010 | A1 |
20110007641 | Galotto | Jan 2011 | A1 |
20110153581 | Kass | Jun 2011 | A1 |
20110182191 | Jackson | Jul 2011 | A1 |
20110276982 | Nakayama | Nov 2011 | A1 |
20120030083 | Newman | Feb 2012 | A1 |
20120226804 | Raja | Sep 2012 | A1 |
20130054516 | Somogyi | Feb 2013 | A1 |
20130114130 | Stampoulidis | May 2013 | A1 |
20130310959 | Sandu | Nov 2013 | A1 |
20130326067 | Smith, II | Dec 2013 | A1 |
20140025772 | Szeto | Jan 2014 | A1 |
20140089928 | Stern | Mar 2014 | A1 |
20140161451 | Graves | Jun 2014 | A1 |
20140304352 | Chaudhary | Oct 2014 | A1 |
20140379756 | Shivarudraiah | Dec 2014 | A1 |
20140379910 | Saxena | Dec 2014 | A1 |
20150006726 | Yuan | Jan 2015 | A1 |
20150026213 | Hegde | Jan 2015 | A1 |
20150043905 | Graves | Feb 2015 | A1 |
20150149635 | Rajagopalan | May 2015 | A1 |
20150230199 | Jeong | Aug 2015 | A1 |
20150281017 | Sarkar | Oct 2015 | A1 |
20150304204 | Robitaille | Oct 2015 | A1 |
20150326441 | Smith | Nov 2015 | A1 |
20160065486 | Hariharan | Mar 2016 | A1 |
20160170978 | Michael | Jun 2016 | A1 |
20160219602 | Takeuchi | Jul 2016 | A1 |
20160274962 | Fortune | Sep 2016 | A1 |
20160300142 | Feller | Oct 2016 | A1 |
20160315862 | Shum | Oct 2016 | A1 |
20170078090 | Garay | Mar 2017 | A1 |
20170115333 | Radic | Apr 2017 | A1 |
20170201458 | Rivera | Jul 2017 | A1 |
20170223112 | Kouno | Aug 2017 | A1 |
20170230306 | Cropper | Aug 2017 | A1 |
20170264671 | Homma | Sep 2017 | A1 |
20170311183 | Cotanis | Oct 2017 | A1 |
20180019322 | Takashima | Jan 2018 | A1 |
20180019922 | Robison | Jan 2018 | A1 |
20180027060 | Metsch | Jan 2018 | A1 |
20180039678 | De Lavarene | Feb 2018 | A1 |
20180046730 | De Lavarene | Feb 2018 | A1 |
20180060377 | Kulkarni | Mar 2018 | A1 |
20180089324 | Pal | Mar 2018 | A1 |
20180150337 | Dolgov | May 2018 | A1 |
20180165469 | Ks | Jun 2018 | A1 |
20180173567 | Olshefski | Jun 2018 | A1 |
20190005047 | D'Amore | Jan 2019 | A1 |
20190075183 | Silberkasten | Mar 2019 | A1 |
20190227684 | Erez | Jul 2019 | A1 |
20190289067 | Chiba | Sep 2019 | A1 |
20190342028 | He | Nov 2019 | A1 |
20190342398 | Kasten et al. | Nov 2019 | A1 |
20200004877 | Ghafourifar | Jan 2020 | A1 |
20200067903 | Yegorin | Feb 2020 | A1 |
20200106175 | Moates | Apr 2020 | A1 |
20200127610 | Kusuda | Apr 2020 | A1 |
20200169969 | Davlantes | May 2020 | A1 |
20200236043 | Sze | Jul 2020 | A1 |
20200252201 | Sergeev | Aug 2020 | A1 |
20200365156 | Allain-Grandvalet | Nov 2020 | A1 |
20210011797 | Robison | Jan 2021 | A1 |
20210014302 | Robison | Jan 2021 | A1 |
Number | Date | Country |
---|---|---|
2973825 | Mar 2018 | CA |
1623139 | Jun 2005 | CN |
101501669 | Aug 2009 | CN |
2014030756 | Feb 2014 | WO |
2020018271 | Jan 2020 | WO |
2020074054 | Apr 2020 | WO |
Entry |
---|
Office Action for U.S. Appl. No. 16/570,729, 19 pages, dated Aug. 20, 2020. |
Office Action for U.S. Appl. No. 16/570,729, 22 pages, dated Dec. 18, 2020. |
Office Action for U.S. Appl. No. 16/593,142, 15 pages, dated Jan. 19, 2021. |
Advisory Action from U.S. Appl. No. 16/570,729, dated Feb. 22, 2021, 3 pages. |
Final Office Action for U.S. Appl. No. 16/593,142, 16 pages, dated Apr. 6, 2021. |
Office Action for U.S. Appl. No. 16/570,729, 15 pages, dated Jul. 16, 2021. |
Notice of Allowance for U.S. Appl. No. 16/660,904, dated Jul. 23, 2021, 8 pages. |
Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Jan. 6, 2023 for U.S. Appl. No. 16/593,142 (pp. 1-11). |
Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Aug. 30, 2021 for U.S. Appl. No. 16/570,729 (pp. 1-8). |
Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Sep. 13, 2021 for U.S. Appl. No. 16/570,729 (pp. 1-3). |
Office Action (Final Rejection) dated May 5, 2022 for U.S. Appl. No. 16/593,142 (pp. 1-16). |
Office Action (Non-Final Rejection) dated Aug. 8, 2022 for U.S. Appl. No. 16/593,142 (pp. 1-16). |
Office Action (Non-Final Rejection) dated Sep. 23, 2021 for U.S. Appl. No. 16/593,142 (pp. 1-19). |
Office Action (Non-Final Rejection) dated Nov. 12, 2020 for U.S. Appl. No. 16/660,904 (pp. 1-9). |
Office Action (Final Rejection) dated Apr. 12, 2021 for U.S. Appl. No. 16/660,904 (pp. 1-11). |
Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Aug. 11, 2021 for U.S. Appl. No. 16/660,904 (pp. 1-2). |
Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Aug. 25, 2021 for U.S. Appl. No. 16/660,904 (pp. 1-2). |
Office Action (Non-Final Rejection) dated Oct. 14, 2022 for U.S. Appl. No. 17/475,758 (pp. 1-19). |
Office Action (Notice of Allowance and Fees Due (PTOL-85)) dated Mar. 15, 2023 for U.S. Appl. No. 17/475,758 (pp. 1-8). |
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20220006858 A1 | Jan 2022 | US |
Number | Date | Country | |
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Parent | 16660904 | Oct 2019 | US |
Child | 17475825 | US |