Sap Se

Long Du

Yu Wang

Le Zhang

Xiaodan Yuan

Jun Zhang

Daping Wang

Haoxing Hou

Disclosed is a framework for providing microservices for database with embedded container service in a container cloud platform. The framework includes a container cloud manager for performing distributed management of resources in a data center. The container cloud manager includes an orchestrator with a flexible job scheduler and operator pool. The flexible job scheduler and container cloud master form a flexible job management platform for managing jobs of the data center. The flexible job management framework can isolate various types of jobs as well as mix various jobs for efficient usage of hosts or resources in the data center. The operator pool includes optional components of a database. The orchestrator facilitates quick customization and release of database products, such as a HANA database with optional services, as requested by a user in the container cloud platform.

Embedded database as a microservice for distributed container cloud platform

In an example embodiment, a hardware mechanism for protecting user-level software from privileged system software is leveraged to protect in-memory databases in container implementations in a cloud. This hardware mechanism takes the form of an enclave. An enclave is a portion of a CPU that shields application code and data from accesses by other software, including higher-privileged software. Memory pages belonging to an enclave reside in the enclave page cache (EPC), which cannot be accessed by code outside of the enclave. This helps ensure that (1) applications built on top of in-memory database are securely trusted, (2) and a trusted path architecture is provided for enclaves allowing in-memory databases to run securely on top of untrusted cloud platform.

Secure in-memory database in container

In an example embodiment, a solution is used to provide container volume replication via a container storage replication log and volume buffer synchronization, which is built on top of a container cloud platform whose container metadata and replication runtime configuration are all managed by a storage manager (a service orchestrated by its job scheduler and service orchestrator). This container volume replication ensures the data security for a long-running service in the container. In the case of any disaster, the in-memory database and application data inside of the container can be recovered via volume replication. This provides container volume replication for long-running containerized applications whose states keep changing.

In-memory database-managed container volume replication

In an example embodiment, a solution is used to provide for multiple and concurrent web application accessing of a database in a database-as-a-service (DBaaS) framework. More particularly, a cloud solution is provided on a DBaaS for leveraging Docker network functionality to provide a virtual Internet Protocol (IP) address pool, while utilizing in-memory database technology to set up an entire accessing solution for multiple and concurrent DBaaS users and web applications, which serve the data-intensive jobs to the in-memory database. This allows for improved functionality, performance, concurrency, and handling of network stress.

Elastic in-memory database provisioning on database-as-a-service

A method of tenant user management in cloud database operation can be implemented. The method can receive an original job request from a user for a database service, wherein the original job request can include a login credential of the user. The method can authenticate the login credential of the user by a scheduler, verify the user has privileges for the original job request by the scheduler, create a modified job request from the original job request by the scheduler based on a predefined role corresponding to the privileges of the user, send the modified job request from the scheduler to a database service platform, and allocate an instance of database service to the user in response to the modified job request.

Tenant user management in cloud database operation

In an example embodiment, a solution is used to provide for a highly efficient image dispatch system for container-based in-memory databases in a database-as-a-service framework that provides storage and bandwidth cost savings and introduces advanced features of container techniques. This solution makes best use of the advantages of the concurrent and distributed capabilities of in-memory databases in a database-as-a-service framework. A container operator manager provides operators for various uses, such as the 'diff' operator and the 'merge' operator. A dispatch manager acts as a centralized service for diff content maintenance, patch publication and management of dispatch worker nodes. A patch worker on each node has the capabilities to execute the specified patching and validation between the images located on each side of the in-memory database in the database-as-a-service framework.

Peer-to-peer delta image dispatch system

In an example embodiment, a new solution is provided for an in-memory database provided in a cloud as a service that enables 'job cross running' instead of 'parallel job running.' Specifically, job scripts are clustered based on a shared service. A primary job script in the cluster is compiled and executed, but secondary job scripts in the cluster are not compiled until after the execution of the primary job script has begun. A mock library is inserted into each of the secondary job scripts to cause service calls for the shared service in the secondary job scripts to be replaced with mock service calls. The secondary job scripts are then scheduled and executed, and upon completion the primary job script is permitted to delete the shared service.

Cross-compilation, orchestration, and scheduling for in-memory databases as a service

This disclosure describes a trace debugger (TDB) that is used for database workload replay and database debugging. The TDB maintains consistency through synchronization of the state between the database and a corresponding database trace replay. The TDB can provide a sliding window environment for code block execution and global context sharing. The TDB can be used to interactively analyze and troubleshoot various types of database problems by debugging the database itself, query code (e.g., SQL), performance, end-to-end execution, and plan traces, which can be recorded using scripts. In some implementations, the TDB also provides reverse debugging for historical database state analysis, and/or incremental debugging for dynamic editing and debugging within a session without the need to exit the debugger and perform a full rebuild of the code.

Growing community of inventors

Xi'an, China

Long Du