Hardware requirements
Necessary condition
At present, private deployments need to be based on k8s deployment, so the hardware requirements are higher than before.
The hardware requirements vary with the demand module, the amount of requests, the amount of data and other factors, resulting in inconsistent hardware configuration requirements.
tip
If multiple products are not deployed together, the maximum value can be taken
Disk space depends on:
- Data retention policy (data retention period)
- Log retention policy
- Data size
- It is not recommended to use NAS, NFS and other network mounted disks unless you can ensure that the network transmission between the server and the network disk is very stable
- SSD or HDD with better performance is strongly recommended
The disk size resources can be appropriately increased or reduced according to the actual business volume and demand module. Data references are as follows:
MySQL: one worker generates 60-70mb screen recording files every 2 minutes with a resolution of 1920 * 1080
Minio: one worker generates about 1GB per year. 100 Task per day, 50 records per Task, 0.5kb per record
Hardware Performance Requirements
- Disk performance: The read speed is not less than 200M/s, and the write speed is not less than 200M/s
- Network performance: Intranet transmission speed not less than 512k/s
- CPU instruction set: If the product you purchased includes the OCR recognition capability (CPU version), the instruction set needs to include fma, avx, and avx2 instructions
caution
If the product you purchased includes OCR recognition capability (GPU version), please ensure that your server has a GPU graphics card and the driver is installed.
If the product you purchased includes OCR recognition capability (CPU version), please ensure that the CPU instruction set in your server contains FMA, AVX and avx2
The recommended graphics card model is NVIDIA [V100, P100, P40, T4]
Single node deployment
You can refer to the following table to count the hardware resources you need:
| Product | CPU Cores | RAM（GB） | HDD（GB） | GPU（GB） |
|---|---|---|---|---|
| Laiye RPA Commander | 8 | 16 | 500 | - |
| Intelligent document processing platform | 8 | 16 | 300 | - |
| Conversational AI platform | 16 | 32 | 300 | - |
| The Hub | 2 | 4 | - | - |
| Data Service | 2 | 2 | - | - |
| Self developed OCR go service | 8 | 16 | - | - |
| Captcha Recognition | 1 | 2 | - | - |
| [Information Extraction, Text Classification, Document Extraction, multi page extraction model, Single-page Extraction Model, text matching] CPU | 2 | 4 | - | - |
| Standard address, Information Extraction, text matching CPU | 2 | 26 | - | - |
| Text Recognition - standard GPU | 4 | 8 | - | 8 |
| Form Recognition - standard GPU | 4 | 8 | - | 11 |
| Seal identification - standard CPU | 4 | 8 | - | - |
| General Card & Certificate Recognition Standard Edition - ID card GPU | 8 | 16 | - | 8 |
| Layout analysis - standard CPU | 4 | 8 | - | - |
| Business license - standard GPU | 4 | 8 | - | 8 |
Multi node deployment
caution
For multi node deployment, three or more nodes are required. You need to create multiple access servers (LB) as the back-end portal.
If you cannot provide a load balancing (LB) address, you can provide us with a free IP, and we will use software to meet your needs.
(as far as I know, aliyuns and other third-party cloud server providers do not support this approach.)
Three nodes
The following is the configuration information of each node
| Product | CPU Cores | RAM（GB） | HDD（GB） | GPU（GB） |
|---|---|---|---|---|
| Laiye RPA Commander | 8 | 16 | 500 | - |
| Intelligent document processing platform | 8 | 16 | 300 | - |
| Conversational AI platform | 16 | 32 | 300 | - |
| The Hub | 2 | 4 | - | - |
| Data Service | 2 | 2 | - | - |
| Self developed OCR go service | 8 | 16 | - | - |
| Captcha Recognition | 1 | 2 | - | - |
| [Information Extraction, Text Classification, Document Extraction, multi page extraction model, Single-page Extraction Model, text matching] CPU | 2 | 4 | - | - |
| Standard address, Information Extraction, text matching CPU | 2 | 26 | - | - |
| Text Recognition - standard GPU | 4 | 8 | - | 8 |
| Form Recognition - standard GPU | 4 | 8 | - | 11 |
| Seal identification - standard CPU | 4 | 8 | - | - |
| General Card & Certificate Recognition Standard Edition - ID card GPU | 8 | 16 | - | 8 |
| Layout analysis - standard CPU | 4 | 8 | - | - |
| Business license - standard GPU | 4 | 8 | - | 8 |
More than three nodes
For installations with more than three nodes, master and node methods will be used to plan the hardware configuration
master：Deploy k8s basic services, such as:apiserver、 Kube controller, Kube scheduler and middleware servicesnode：The node that actually runs the service module
It can be roughly divided into the following two situations:
3 < nodes < 6: Master = 3, node = number of nodes (Master is also node)
6 =< nodes: Master = 3, node = number of nodes - number of Masters (Master is only master)
Assuming that the number of nodes provided is 4, the number of master roles is 3 and the number of node roles is 4.
Master node configuration
| Product | CPU Cores | RAM（GB） | HDD（GB） | GPU（GB） |
|---|---|---|---|---|
| Laiye RPA Commander | 6 | 12 | 500 | - |
| Intelligent document processing platform | 6 | 12 | 300 | - |
| Conversational AI platform | 12 | 24 | 300 | - |
| The Hub | - | - | - | - |
| Data Service | - | - | - | - |
| Self developed OCR go service | 6 | 12 | - | - |
| Captcha Recognition | - | - | - | - |
| [Information Extraction, Text Classification, Document Extraction, multi page extraction model, Single-page Extraction Model, text matching] CPU | - | - | - | - |
| Standard address, Information Extraction, text matching CPU | - | - | - | - |
| Text Recognition - standard GPU | - | - | - | - |
| Form Recognition - standard GPU | - | - | - | - |
| Seal identification - standard CPU | - | - | - | - |
| General Card & Certificate Recognition Standard Edition - ID card GPU | - | - | - | - |
| Layout analysis - standard CPU | - | - | - | - |
| Business license - standard GPU | - | - | - | - |
node configuration
| Product | CPU Cores | RAM（GB） | HDD（GB） | GPU（GB） |
|---|---|---|---|---|
| Laiye RPA Commander | 2 | 4 | 500 | - |
| Intelligent document processing platform | 2 | 4 | 300 | - |
| Conversational AI platform | 4 | 8 | 300 | - |
| The Hub | 2 | 4 | - | - |
| Data Service | 2 | 2 | - | - |
| Self developed OCR go service | 2 | 4 | - | - |
| Captcha Recognition | 1 | 2 | - | - |
| [Information Extraction, Text Classification, Document Extraction, multi page extraction model, Single-page Extraction Model, text matching] CPU | 2 | 4 | - | - |
| Standard address, Information Extraction, text matching CPU | 2 | 26 | - | - |
| Text Recognition - standard GPU | 4 | 8 | - | 8 |
| Form Recognition - standard GPU | 4 | 8 | - | 11 |
| Seal identification - standard CPU | 4 | 8 | - | - |
| General Card & Certificate Recognition Standard Edition - ID card GPU | 8 | 16 | - | 8 |
| Layout analysis - standard CPU | 4 | 8 | - | - |
| Business license - standard GPU | 4 | 8 | - | 8 |