IEMR, a big data storage and analysis service
IEMR provides a one-stop enterprise-level big data cluster cloud service that is fully controllable by tenants, easily runs big data components such as Hadoop, Spark, and HBase, is fully compatible with open-source APIs, and has enterprise-level feature enhancements in terms of security, reliability, and maintainability.
-
Product Advantages
-
Product functions
-
Application scenarios
-
solution
-
Product Advantages
One-click deploymentOne-click automatic cloud deployment, full web-based operation, cluster scale-out/scale-in. Scale-out does not cause problems such as data skew, and the service is automatically completed after node scale-out or scale-in.
Elastic scalingCluster elastic scaling. Apply for resources when the business is busy, and release idle resources when it is not busy.
Cluster O&MIt can easily cope with business emails and SMS with larger data volumes and more complex data types, and provide automatic inspection, one-click and automatic operation of health inspection and audit.
Separation of storage and computingIt can be connected to OSS to separate big data storage and computing, and support elastic scaling of clusters.
- Hybrid transaction/analysis
Introduce technologies such as Hudi to provide transactional/analytical integration and big data computing capabilities.
- Multi-tenant
Enterprise-level big data multi-tenant solution, resource isolation between tenants, data and business security.
- Security enhancements
It supports the Kerberos security protocol and provides single sign-on and user auditing.
- Reliability enhancement
For all nodes, HA capacities are achieved, and full backup, incremental backup, and restoration are provided.
Product functions
- Parameter configuration
It provides the parameter configuration function to set the parameters related to big data components and make them effective.
- Instance management
It provides instance management functions for each component, such as instance starting, stopping, restarting, deleting, and migrating.
- Safety certification
It supports the Kerberos security protocol and provides role-based user authentication, authorization, and auditing.
- Operation monitoring
It provides real-time monitoring of the big data running environment, such as real-time access to cluster CPUs and memory.
- Deep integration with data lakes
It is deeply integrated with services such as data integration and data lake construction to complete the full life cycle management of data.
Application scenarios
-
Realize offline data analysis based on Inspur cloud hosting service
-
Provide massive data online services based on Inspur cloud hosting platform
-
After synchronizing massive data on business servers such as web applications and mobile apps to the data nodes hosting Hadoop, you can use mainstream computing frameworks such as Hive, Spark, and Storm to quickly obtain data insights.
-
For scenarios that require timely analysis and display of large amounts of data, such as monitoring and O&M and business applications, historical big data, real-time big data, and application data are mostly aggregated to HBase, and then queried and displayed in real time, or applied to other services.
More options
Empower customers to quickly and securely migrate to the cloud，
If you have any questions about Inspur Cloud, please contact us
Are you interested in our solutions?
Please do not hesitate to contact us! We're here to help.
