Elastic Cloud Server

Scenario Description

For individual or enterprise's go-cloud demands, build websites with moderate workloads such as portals and office OA to ensure smooth operation of business and maintain a stable and reliable system.

Scenario Pain Points

Individuals and small companies need to purchase hardware facilities when deploying ordinary business, which costs a lot. Large-and-medium-sized companies need to deploy a wide range of data centers to carry out cross regional businesses, which is difficult to maintain and costly.

Product Advantages

eSurfing Cloud ECS is ready to use, delivered in minutes, and can be quickly deployed in nationwide data centers.
Specification and capacity can be scaled on demand without affecting the normal operation of the business, which takes into account both the cost and user experience.
Services are allocated to multiple ECS through LB to enhance service processing capabilities.
High concurrency support capability through ZOS helps to solve the problem of page crashes when websites are frequently visited.

Scenario Description

With the upgrading of the game industry ecology, traditional game manufacturers have higher requirements for computing, network, data processing, image rendering, etc., and urgently need to build cloud game business at low cost.

Scenario Pain Points

Large game data volume, various data types, and high real-time computational complexity. Business pressure is constantly changing, requiring flexible real-time elastic scaling.

Product Advantages

Multiple nodes and available zones help game business quickly realize large-scale layout.
Rapid elastic scaling on demand, rational use of resources and cost savings.
Professional GPU virtualization technology, process-level resource scheduling, greater concurrency of each server, and lower go-cloud cost.
Advanced codec protocols combined with optimized network transmission to ensure lower latency and experience effect.

Scenario Description

Applications with certain requirements for computing and networking, to ensure best user experience.

Scenario Pain Points

Traditional servers cannot be flexibly expanded, while existing servers cannot bear the load, resulting in poor user experience. Availability and reliability cannot be guaranteed, and capabilities such as timely backup and recovery are required.

Product Advantages

The ECS supports as-per-use expansion, which can ensure smooth access to applets for users while rationally optimizing costs and expenditures.
Data are automatically backed up to ZOS with multiple backup strategies and one-click configuration.

Recommended combination for use

Auto Scaling

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Elastic Load Balancing

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Scenario Description

High business fluctuation and memory consumption make traditional supermarkets and retailers encountered with industrial upgrading and cross-border e-commerce faced with business peaks and security threats.

Scenario Pain Points

Activities such as livestreaming and flash sale entail high website performance, and slow system response will affect user experience. Slow page loading and high network latency in case of high-visits and resource waste in case of low-visits.

Product Advantages

Automatic adjustment of elastic computing resources can cope with business peaks at any time.
Zettabyte object storage technology is used to store streaming data or file data to the cloud to solve the business pressure of high throughput and high concurrency.
For high-visits, services can be allocated to multiple ECS through LB to guarantee user experience.

Scenario Description

High requirements for memory, with ultra-high IO EVS to meet the demand for massive data processing.

Scenario Pain Points

Costly devices with high-performance memory. High load when processing data, and difficulties in capacity expansion and reduction of traditional hosts.

Product Advantages

Ultra-high IO EVS with strong read/write performance and high throughput bandwidth can meet the deployment needs of various databases (e.g. MySQL, Oracle, NoSQL).
Real-time notification of elastic scaling policy execution results enables users to keep track of the dynamic situation of scaling and facilitate timely adjustment of policies to ensure database business stability.
Quickly realize network access interconnection, and guarantee data security with multiple copies.

Scenario Description

Professional-level CAD, video rendering, graphics processing and other scenarios require powerful computing power to pursue ultimate performance experience, and ultra-high cost efficiency.

Scenario Pain Points

High GPU price and high cost for hardware upgrade and maintenance. Diversified demands with different requirements for GPU models, graphics memory and other parameters for different services.

Product Advantages

Adopt the industry's advanced GPU hardware, synchronize the industry's cutting-edge technology, and seamlessly switch to new hardware.
Fully support a variety of GPU applications and deep learning frameworks, such as OpenGL and DirectX .
Convenient and fast to provide the same usage and management functions as standard ECS.
Rich specifications provide a variety of graphics memory to meet different graphics scenarios.
Monitoring and alerting of GPU resources through cloud eye services.

Scenario Description

Massive data needs low-cost storage and high-speed data processing capabilities. Log analysis, business data analysis, traffic data analysis and other scenarios need to combine the basic cloud services and big data formation.

Scenario Pain Points

While meeting high performance processing capacity, it is necessary to reduce server costs and improve resource utilization. As business pressure is constantly changing, flexible real-time elastic scaling is required to improve processing capacity.

Product Advantages

Local ECS is used to provide highly reliable storage resources to facilitate secure storage of data, files and applications.
For key protection data, the multi-copy redundancy function of Zettabyte Object Storage can be used to achieve off-site data disaster recovery.
Online elastic scaling is provided on demand without data migration to meet the challenges of large capacity and high concurrency requests.

Scenario Description

The training or prediction platform for deep learning needs to consume a lot of computing resources to pursue excellent performance.

Scenario Pain Points

A large amount of temporary data is generated with high requirements for storage. Extremely high requirements for network latency.

Product Advantages

With the use of zettabyte object storage, cloud database, cloud eye and other services, a full-featured deep learning offline training system can be built quickly.
Fully support a variety of GPU applications and deep learning frameworks, such as CUDA, OpenCL.
Convenient and fast to provide the same usage and management functions as standard ECS.
Rich specifications provide a variety of graphics memory to meet different graphics scenarios.
Monitoring and alerting of GPU resources through cloud eye services.

Product Advantages

Scenarios

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