Mongodb, Inc.

Cailin Anne Nelson

Eliot Horowitz

Cory P Mintz

Louisa Berger

Akshay Kumar

Dwight Allen Merriman

Mathias Stearn

David Lenox Storch

Geert Bosch

Charles William Swanson

Keith Bostic

Michael Cahill

John Morales

Dan Pasette

Viet Duc Do

Duncan Armstrong

Golam Rezwan Khan

Jonathan Balsano

Systems and methods are provided for managing a distributed database across multiple cloud provider systems. Database elements (e.g., primary, secondary, and/or read-only nodes) are distributed across multiple cloud provider systems. A provisioning component is configured to enable cross-cloud configuration options to specify the manner in which the clusters/replica set members are to be deployed across multiple cloud providers and/or geographical regions.

Cross-cloud deployments

Systems and methods are configured to identify and resolve user-based issues, architecture issues, and data model issues that are introduced into distributed database deployments. Even in the context of a pre-built distributed database system, 'bad' user behavior can have huge impacts on database performance. Various embodiments provide for analysis and resolution of architecture issues, as well schema issues, and can be configured to identify and resolve such problems in the context of dynamic schema database systems. Unlike relational database counterparts, dynamic schema databases do not enforce static database architecture or defined schemas. In such environments, database data and database formatting can be mostly unconstrained. If used properly, this flexibility enables easy configuration and execution. However, when improperly designed, small flaws magnify in significance as the database grows. Various embodiments identify anti-patterns indicative of non-optimal configuration or bad performance, and generate options for resolving them.

Systems and methods for detecting performance degradation in distributed database deployments

Various aspects provide for implementation of a cloud service for running, monitoring, and maintaining cloud distributed database deployments and in particular examples, provides cloud based services to run, monitor and maintain deployments of the known MongoDB database. Various embodiments provide services, interfaces, and manage provisioning of dedicated servers for the distributed database instances (e.g., MongoDB instances). Further aspects, including providing a database as a cloud service that eliminates the design challenges associated with many distributed database implementations, while allowing the client's input on configuration choices in building the database. In some implementations, clients can simply identity a number of database nodes, capability of the nodes, and within minutes have a fully functioning, scalable, replicated, and secure distributed database in the cloud.

Systems and methods for managing distributed database deployments

Systems and methods are provided to enable control and placement of data repositories. In some embodiments, the system segments data into zones. A website, for example, may need to segment data according to location. In this example, a zone may be created for North America and another zone may be created for Europe. Data related to operations executed in North America, for example, can be placed in the North America zone and data related to transactions in Europe can be placed in the Europe zone. According to some embodiments, the system may use zones to accommodate a range of deployment scenarios.

Systems and methods for database zone sharding and API integration

An automation system is provided to automate any administrative task in a distributed database, such that the end user can input a goal state (e.g., create database with a five node architecture) and the automation system generates and executes a plan to achieve the goal state without further user input. According to another aspect, bringing existing database systems into automated management can be as complex as designing the database itself. According to some embodiments, the automation system is configured to analyze existing database systems, capture and/or install monitoring components within the existing database, and generate execution pathways to integrate existing database systems into automation control systems. Based on the current state information, the automation system is configured to generate an installation pathway of one or more intermediate states to transition the existing system from no automation to a goal state having active automation agents distributed throughout the database.

Systems and methods for automating management of distributed databases

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Boulder, CO, United States of America

Cailin Anne Nelson