Application Scenarios
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Cloud Migration
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IoV
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Finance & Insurance
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Smart Logistics
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IoE
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Smart Water Mgmt
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Gaming
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Energy
Quick Cloud Migration
You can quickly migrate big data platforms, such as IDC, CDH,
Hontonwoks, or other big data cloud service platforms to MRS.
With MRS you can move all of your services and data to the cloud in a few steps,
and you can future proof your enterprise by using the cloud environment as a
foundation to rapidly construct your off-cloud systems.
Advantages
With MRS, compute and storage are decoupled so you can leverage multi-core
Kunpeng features to deploy your services more cost-effectively.
Data silos will no longer exist with unified data storage and
multiple types of compute engines. One copy of data can be shared and analyzed
for multiple services.
You can combine multiple types of compute and storage resources and configure
automatic scale in or out, greatly reducing the cost of migrating to the cloud.
MRS is fully compatible with open-source APIs. During migration,
your services are not affected and no service code needs to be modified.
A complete set of migration tools are provided for you to quickly
complete migration without interrupting services.
Internet of Vehicles (IoV)
MRS leverages the open-source ecosystem to provide a fast and efficient data processing computing engine that helps automobile enterprises quickly migrate services to the cloud. It also flexibly builds an open, unified, and full-stack big data platform for data analysis.
Advantages
Finance and Insurance
MRS leverages the advantages of the big data platform on DeC to meet the strict requirements of the insurance industry with regards to compliance, security, and reliability. It reconstructs the IT architecture of traditional insurance enterprises, and quickly builds and deploys insurance service systems. This helps insurance enterprises achieve fast digital transformation, easy service innovation, and agile service evolution.
Advantages
Smart Logistics
MRS big data analysis platform is used to implement intelligent management of logistics activities, improving service operation efficiency and greatly reducing costs.
Advantages
Dedicated MRS Kafka clusters with high-throughput, high availability, and low latency capabilities facilitate real-time access of millions of messages.
MRS Spark supports large-scale data computing. MRS HBase can load and update logistics data in milliseconds, and query and analyze petabytes of time series data.
MRS uses AI for big data mining, and provides precise and intelligent prediction and analysis capabilities for logistics organizations, marketing, and operation management.
Internet of Elevators (IoE)
To adapt to the rapid business innovation and flexible service modes involved in IoE, MRS functions as an open one-stop big data processing platform to implement intelligent elevator management.
Advantages
MRS provides a wide variety of computing products and storage hardware for your choices to meet scenario-specific needs and build a unified and open big data platform. In addition, it offers powerful computing engines and a massive amount of storage, and enables flexible integration of service components.
MRS Kafka works with high-performance general network enhancement (C3ne) ECSs to implement real-time data access for millions of elevators.
MRS supports GPUs that provide real-time high-speed parallel computing and floating-point computing capabilities. These are applicable to video encoding and decoding, deep learning, and scientific computing.
Smart Water Management
MRS Hadoop provides high-performance, reliable, unified big data storage and analysis functions for water management scenarios.
Advantages
MRS builds an enterprise-level big data platform and provides various open-source components that can be flexibly combined, supporting real-time/offline complex service processing.
Storm can obtain real-time stream data from Kafka to implement real-time computing and analysis with high throughput and low latency.
Various structured, semi-structured, and unstructured data can be computed and processed, and traditional data warehouse data can be easily migrated, facilitating cross-source data exploration and analysis.
Gaming
Game log data is accessed through Kafka and Flume in real time. Spark Streaming processes and analyzes the data in real time and stores the analysis results to HBase or Hive for quick game advertisement analysis, data query and analysis, and revenue analysis.
Advantages
MRS functions as an enterprise-level big data platform and provides various open-source components that can be combined flexibly to meet even highly complex service processing needs.
MRS Kafka and Flume collect real-time data and integrate with high-performance general network enhancement (C3ne) ECSs to implement real-time access of massive amounts of data.
Energy
MRS provides enterprise-level big data cloud services that enable PV plant operators to easily run Hadoop, Spark, HBase, Storm, and other big data components for the purpose of predictive device maintenance.
Advantages
MRS functions as an enterprise-level big data platform and provides various big
data components that support flexible use in different combinations, meeting
customers' requirements for complex service processing.
MRS Kafka and Sqoop
support multiple data collection methods, facilitating real-time access of
millions of messages.
SQL APIs can
be used to support querying multi-dimensional data for easy
data exploration and analysis.
Scenario-Specific Clusters
Hadoop Analysis Cluster
Analysis of vast amounts of data
Uses Spark to analyze and query vast amounts of data and uses Hive to analyze TB/PB-level data.
HBase Cluster
Massive data storage
Uses HBase to store massive amounts of data and query data in milliseconds.
Kafka Cluster
Low-latency streaming processing
Uses Flume to perform real-time data ingestion, Kafka to implement real-time access of tens of thousands of data records, and Storm to achieve reliable, fault-tolerant, and low-latency online service data processing.
Product Advantages
Product Advantages
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Enterprise-class
With one-click cluster installation, deployment, and capacity expansion, you do not need to worry about purchasing and maintaining hardware. Visualized enterprise-level cluster management allows for real-time node status monitoring and provides SMS notifications when there are alarms. Needed service patches are provided in a timely manner and can be installed in a single click.With one-click cluster installation, deployment, and capacity expansion, you do not need to worry about purchasing and maintaining hardware. Visualized enterprise-level cluster management allows for real-time node status monitoring and provides SMS notifications when there are alarms. Needed service patches are provided in a timely manner and can be installed in a single click. -
Storage-compute Decoupling
Take advantage of the HUAWEI CLOUD On OBS solution. Powered by a comprehensive big data engine, OBS is fully compatible with open-source APIs, and you can use Huawei-developed Kunpeng servers. The multi-core and high-concurrency capabilities that Kunpeng provides increase hardware compute performance and reduces costs.Take advantage of the HUAWEI CLOUD On OBS solution. Powered by a comprehensive big data engine, OBS is fully compatible with open-source APIs, and you can use Huawei-developed Kunpeng servers. The multi-core and high-concurrency capabilities that Kunpeng provides increase hardware compute performance and reduces costs.
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High Elasticity
You can select different flavors and deployment configurations running on Kunpeng or x86, and hybrid deployments of bare metal servers and VMs are supported within a single cluster. Tasks in peak and off-peak hours can be automatically scaled based on preconfigured policies.You can select different flavors and deployment configurations running on Kunpeng or x86, and hybrid deployments of bare metal servers and VMs are supported within a single cluster. Tasks in peak and off-peak hours can be automatically scaled based on preconfigured policies. -
High Security
Kerberos authentication management and fine-grained enterprise management allow you to manage cluster permissions by project. Multi-tenant management is supported and compute and storage resources are isolated within clusters by tenant. Encrypted transmission and storage, including data tables and columns, ensure that sensitive data is kept secure.Kerberos authentication management and fine-grained enterprise management allow you to manage cluster permissions by project. Multi-tenant management is supported and compute and storage resources are isolated within clusters by tenant. Encrypted transmission and storage, including data tables and columns, ensure that sensitive data is kept secure.
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Multi-level Availability
Instances can be distributed across cluster nodes, so if any individual node fails, its instances can be quickly migrated to other nodes. Cross-AZ data synchronization and backup are also supported, so you can enjoy redundant backups across different AZs, and cluster metadata can be stored externally, in RDS. All service management nodes in a cluster support cross-AZ HA deployment for multi-level high reliability VMs and clusters.Instances can be distributed across cluster nodes, so if any individual node fails, its instances can be quickly migrated to other nodes. Cross-AZ data synchronization and backup are also supported, so you can enjoy redundant backups across different AZs, and cluster metadata can be stored externally, in RDS. All service management nodes in a cluster support cross-AZ HA deployment for multi-level high reliability VMs and clusters. -
High Performance
Get responses in seconds when analyzing even trillions of records thanks to Huawei-developed CarbonData indexing, materialized views, and caching. The large-scale cluster scheduler Superior, from Huawei, allows you to blast through the traditional limitations of single cluster deployments. With Superior, the scheduling capability of a single cluster can exceed 10,000 nodes, and the Huawei data acceleration engine, DataTurbor, turbocharges compute performance.Get responses in seconds when analyzing even trillions of records thanks to Huawei-developed CarbonData indexing, materialized views, and caching. The large-scale cluster scheduler Superior, from Huawei, allows you to blast through the traditional limitations of single cluster deployments. With Superior, the scheduling capability of a single cluster can exceed 10,000 nodes, and the Huawei data acceleration engine, DataTurbor, turbocharges compute performance.
Compatible with x86, ARM, and Open Source Big Data Ecosystem
Huawei-developed ARM servers are integrated with Huawei-developed OSs and databases, achieving integration of software and hardware. Various open source computing frameworks, for example, MapReduce, Spark/Spark SQL, Hive, and Storm are supported.
CarbonData, a high-performance file storage format, is supported.
Spark SQL is compatible with Hive SQL.
