Deployment Methodology
Version 9.2
BDB Data Platform follows microservice architecture and uses containers to make it highly scalable and secure. BDB Data Platform uses Kubernetes for container orchestration to automate most of the operational effort required to run containerized workloads and services. Kubernetes is an open-source system for deploying, scaling and managing containerized applications. Kubernetes handles the work of scheduling containers onto a compute cluster and manages the workloads to ensure they run as the user intended. Kubernetes eliminates infrastructure lock-in by providing core capabilities for containers without imposing restrictions. It achieves this through a combination of features within the Kubernetes platform.
A representative schematic diagram of the BDB Data Platform using Kubernetes methodology is shown below:
Before you Install
Before you finalize installing the BDB Data Platform solution in your organization, be sure to carefully evaluate the options ( On-prem OR Cloud ). For most organizations, deployment in Cloud will provide a more reliable, performant, and cost-effective solution when compared to On-prem deployment.
BDB Data Platform supports both on-premises and cloud deployments including major players like AWS, Azure & GCP.
Minimum Hardware Requirements & Recommendations
BDB recommends the following list as minimum hardware requirements for the Production environment.
Please Note: A similar configuration can be envisioned for Dev & UAT environments.
| Plugin | CPU Core | Memory (GB) | SSD/HDD (GB) | Comments |
|---|---|---|---|---|
Core Platform | 10 | 32 | 200GB/Node | Platform Services, Self Service Module |
Data Pipeline Module | 4 | 32 |
| This is the Core Data Pipeline Module with its various components |
Execution Space (Pipeline & DS Lab) | 8 | 32 |
| These are the Worker Nodes that will process the data |
Pre-requisite/dependency (Repo DB, Kafka) | 8 | 32 |
| Platform external dependency |
Dashboard Designer (Optional) | 4 | 8 |
| In case Dashboard Designer Tool for Dashboards is required |
DS Lab (Optional) | 4 | 16 |
| Data Science Lab module to Develop Algorithms |
AutoML (Optional) | 4 | 16 |
| Auto ML Setup if required |
Monitoring (Optional) | 2 | 8 |
| Data Observability Reports and Monitoring Setup |
ClickHouse Data Lake - Sharded Cluster of 2, 8 Core | 16 | 64 | | Data Base |
Network Storage | | | 1 TB |
|
|
vCPU
|
RAM ( in GB )
|
|
Dashboard Only ->
|
12
|
48
|
|
Business Story ->
|
6
|
32
|
|
Pipeline ->
|
12
|
48
|
|
Monitoring ->
|
2
|
8
|
|
K8s Master ->
|
4
|
8
|
|
Execution ->
|
8
|
32
|
As Per data Volume
|
|
44
|
176
|
|
The following table includes the minimum hardware requirements for Dev and QA tenants.
Dev Tenant | 8 | 32 | Additional for Data Base + 8 Core or 16 Core for Sharding |
QA Tenant | 8 | 32 |
|
Please Note: The required Network Storage is 1 TB.
If you have finalized to proceed with the On-prem deployment option, please refer to the section Deployment of BDB Data Platform service -- On-prem environment
If you have finalized to proceed with the Cloud deployment option, please refer to the section Deployment of BDB Data Platform service -- Cloud environment
Deployment of BDB Data Platform Service – On-Prem Environment
Deployment of BDB Data Platform Service – Cloud Environment
BDB Platform is cloud agnostic. It can be been deployed on all major cloud players like AWS, Azure & GCP. It can be also deployed on other cloud environments based on customer choice.
Outlines below are schematic flow diagrams related to BDB Data Platform service deployment on Azure, AWS & GCP cloud.
Deployment using Azure Cloud
Deployment using AWS Cloud
Deployment using GCP Cloud
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