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Background and challenges

Background

Storage Requirements for Middleware Services in the Cloud

  1. The cloud is becoming the core of new digital experiences, and the number of middleware services such as databases and message queues on the cloud is rapidly increasing. During the migration process of stateful applications to the cloud, ensuring high performance and reliability of business applications becomes a challenge that enterprises need to overcome.
  2. In storage-computing fusion use cases of physical facilities, how to utilize existing device storage space to meet the needs of stateful applications on the cloud?
  3. As more and more critical applications move to the cloud, achieving efficient operation and maintenance of cloud storage, ensuring data storage reliability, and implementing comprehensive monitoring of application/control plane/backend device will become new challenges.

Storage Solution in Cloud-side Collaboration Scenario

In Garner's top ten cloud trend predictions for 2021, edge computing becomes the new cloud. Edge use cases also require data storage and preprocessing capabilities. On the edge side, storage-computing integration is generally adopted, but edge resources are limited. How to perform certain data storage and computation based on the edge side poses a problem to be solved in cloud edge collaboration use cases.

Challenges

Enterprise Readiness Challenge

Stateful key applications such as databases, message queues, and big data are gradually moving to the cloud, and there are new and higher requirements for the performance (throughput, latency) of cloud storage. Meeting the high-performance requirements while ensuring efficient operation and maintenance, reliable data storage monitoring, and forming full-link monitoring, including displaying monitoring data of application-level/control plane mount points and backend devices, and quickly identifying and addressing storage issues.

Agility Challenge

Cloud native use cases have very high requirements for service agility and flexibility. Many use cases expect fast container startup and flexible scheduling, which requires both storage volumes and agile adjustments to Pod changes. To achieve this:

  1. Improve the efficiency of cloud disk mounting and uninstallation.
  2. Enable the block device to be flexibly mounted and quickly switched between different nodes.
  3. Provide automatic repair capabilities for storage services, reducing human intervention.
  4. Implement online expansion capability without affecting application business to quickly expand container capacity.
  5. in cases where multiple stateful applications are containerized and deployed in the same cluster, implement automatic scheduling according to the storage type in the cluster planning business sub-regional usage scenario.

Cost Reduction and Efficiency Increase Challenge

While the computing density of data centers is increasing, the storage performance bottleneck needs to be addressed by:

  1. Locating and troubleshooting unplanned equipment failures, fault location, and recovery to solve performance and availability issues.
  2. Reducing the complexity of building, configuring, maintaining, and scaling applications (different deployment environments and software technology stacks).
  3. Solving storage bottlenecks after addressing computing bottlenecks since storage capacity can become a bottleneck restricting computing density.
  4. Perceiving business requirements and implementing resource balancing such as automatic expansion to address high costs caused by idle rates of computing and storage resources being greater than or equal to 50%.

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