Designing DevOps workflows for different deployment options requires careful planning to ensure scalability, flexibility, and efficiency while accommodating the unique requirements of each deployment strategy. Below is a high-level guide for designing DevOps practices tailored to different deployment options: 1. Deployment Options Overview On-Premises Deployment Applications are hosted on physical servers or private data centers. Cloud Deployment Applications are hosted on public, private, or hybrid cloud platforms (e.g., AWS, Azure, Google Cloud). Containerized Deployment Applications are packaged as containers (e.g., Docker) and orchestrated using tools like Kubernetes. Serverless Deployment Applications run as functions without managing underlying infrastructure (e.g., AWS Lambda, Azure Functions). Edge Deployment Applications are deployed closer to users on edge devices or servers for low-latency processing. 2. DevOps Design Principles Automation Implement CI/CD pipelines to automate build, test, and deployment processes. Automate infrastructure provisioning with Infrastructure as Code (IaC) tools (e.g., Terraform, AWS CloudFormation). Scalability Design pipelines to handle scaling needs for cloud and container-based deployments. Use auto-scaling mechanisms for cloud or serverless environments. Monitoring & Observability Integrate monitoring tools (e.g., Prometheus, Grafana, ELK stack) to track application performance across deployment environments. Use log aggregation and distributed tracing tools for debugging. Security Automate vulnerability scanning (e.g., with tools like Snyk or Trivy). Implement secrets management (e.g., HashiCorp Vault, AWS Secrets Manager). Ensure compliance with security policies regardless of deployment type. 3. DevOps Design for Specific Deployment Options a. On-Premises Deployment Configuration Management: Use tools like Ansible, Puppet, or Chef to manage on-premises environments. CI/CD Pipelines: Design pipelines that deploy artifacts directly to on-premises servers. Backup and Recovery: Implement robust disaster recovery and backup strategies for physical infrastructure. Monitoring: Use tools like Nagios or Zabbix for system monitoring. b. Cloud Deployment IaC Tools: Use Terraform, AWS CloudFormation, or Azure Resource Manager to provision and manage cloud resources. CI/CD Pipelines: Integrate deployment pipelines with cloud platforms using APIs or native tools (e.g., AWS CodePipeline, Azure DevOps). Cloud-Specific Features: Leverage cloud-native services like load balancers, auto-scaling, and managed databases. c. Containerized Deployment Container Image Management: Use Docker and a container registry (e.g., Docker Hub, Amazon ECR) for version control of images. Orchestration: Integrate Kubernetes or Docker Swarm for container orchestration. CI/CD Pipelines: Build pipelines to create, test, and deploy container images. Monitoring: Use tools like Prometheus, Grafana, or Kubernetes-native monitoring

1. Azure DevOps Server
Deployment

2. Azure DevOps Server Deployment Architecture
App Gateway
Azure DevOps
Server
SQL Database
Azure DevOps
Server
Azure DevOps
Search Server
Azure DevOps
Search Server
Windows Agent Windows Agents
Linux Agent
Linux Agent
DevOps Vnet
Trigger CI/CD
CI/CD Pipeline Agents
Private Link
Client
Azure Boards Azure Repos
Test Plans Azure Artifacts

3. Azure DevOps Deployment
The following scenarios might require a multiple-server deployment:
Scaling beyond 500 users
Extensive use of automated build, test, or release
Using Code Search
Using reporting features
For a team of more than 500 users, consider the following setup:
An application tier with one dual-core processor, 8 GB of memory, and a fast hard-disk drive.
A data tier with one quad-core processor, 16 GB of memory, and high-performance storage, such as an SSD.
For a team of more than 2,000 users, consider the following setup:
An application tier with one quad-core processor, 16 GB or more of memory, and a fast hard-disk drive.
A data tier with two or more quad-core processors, 16 GB or more of memory, and advanced high-
performance storage, like an SSD or high-performance SAN.
Setup & upgrade requirements - Azure DevOps | Microsoft Docs

4. Azure DevOps Deployment
Set up AD groups for use in Azure DevOps Server on-premises:
Set up deployment groups - Azure DevOps | Microsoft Docs
Get started with permissions, access levels, and security groups - Azure DevOps | Microsoft Docs
Azure Load Balancer:
What is Azure Load Balancer? - Azure Load Balancer | Microsoft Docs
Azure Application Gateway:
What is Azure Application Gateway | Microsoft Docs

5. IT/Operations
Project Lead
Quality Analyst
Business Analyst /
Product Owner
Project Manager
Developer
Approval
Pipeline
Portfolio
Tasks
Storyboards
Test Cases
Source Code
User Stories
Deployment
Build
Execute Test
Bugs
Architecture
Code Analysis
SonarQube
The Enterprise Collaboration Solution
Quality Gates
Commit /
Check-in
Develop
Plan & Track
Manual
Testing
Build/Deploy

6. Introducing Azure DevOps
Deliver value to your users faster
using proven agile tools to plan,
track, and discuss work across
your teams.
Build, test, and deploy with CI/CD that
works with any language, platform,
and cloud. Connect to GitHub or any
other Git provider and deploy
continuously.
Get unlimited, cloud-hosted
private Git repos and collaborate
to build better code with pull
requests and advanced file
management.
Test and ship with confidence
using manual and exploratory
testing tools.
Create, host, and share packages with
your team, and add artifacts to your
CI/CD pipelines with a single click.
Azure Boards Azure Repos
Azure Pipelines
Azure Test Plans Azure Artifacts
https://azure.com/devops
➔