Infrastructure as Code for Data Platforms Training Course

 Infrastructure as Code for Data Platforms Training Course 

Course Introduction 

Infrastructure as Code for Data Platforms Training Course provides comprehensive practical knowledge and technical expertise in designing, provisioning, configuring, and managing modern data infrastructure through automated, code-driven approaches. As organizations accelerate digital transformation, cloud migration, big data adoption, and artificial intelligence initiatives, Infrastructure as Code (IaC) has become essential for building scalable, secure, reliable, and cost-efficient data platforms. This course explores industry-leading technologies, including Terraform, Ansible, Pulumi, Kubernetes, Docker, AWS, Microsoft Azure, and Google Cloud Platform, equipping participants with the skills to automate infrastructure deployment, implement configuration management, establish reusable infrastructure templates, and manage cloud-native data engineering environments. 

Participants will gain practical experience in infrastructure automation, version control, continuous integration and continuous delivery, data platform orchestration, cloud resource management, automated testing, and infrastructure governance. The programme examines real-world applications of Infrastructure as Code in enterprise data lakes, data warehouses, analytics platforms, and distributed processing environments. Through international case studies, practical laboratories, and scenario-based exercises, participants will learn to implement secure infrastructure provisioning, improve operational efficiency, strengthen disaster recovery, optimize cloud expenditure, and establish standardized deployment pipelines. The course also addresses emerging practices in GitOps, policy as code, DevOps automation, platform engineering, and infrastructure lifecycle management to support sustainable, future-ready data ecosystems. 

Course Objectives 

By the end of this course, participants will be able to: 

1. Understand Infrastructure as Code principles and modern data platform architecture.
2. Automate cloud infrastructure provisioning using Terraform and Pulumi.
3. Implement configuration management using Ansible.
4. Design scalable cloud-native data infrastructure.
5. Integrate infrastructure automation with DevOps and CI/CD pipelines.
6. Apply GitOps practices and infrastructure version control.
7. Automate data lake and data warehouse environments.
8. Implement Kubernetes-based infrastructure orchestration.
9. Strengthen infrastructure security through policy as code.
10. Develop reusable infrastructure modules and deployment templates.
11. Implement automated infrastructure testing and validation.
12. Optimize cloud resource utilization and infrastructure costs.
13. Establish infrastructure monitoring, governance, and disaster recovery frameworks.

Organizational Benefits
 

1. Reduced infrastructure provisioning costs through automation.
2. Faster deployment of enterprise data platforms.
3. Improved operational consistency and standardization.
4. Enhanced cloud security and regulatory compliance.
5. Reduced manual configuration errors.
6. Improved scalability and infrastructure reliability.
7. Stronger disaster recovery and business continuity.
8. Increased collaboration between DevOps and data engineering teams.
9. Better cloud resource utilization and cost optimization.
10. Accelerated digital transformation and innovation.

Target Audiences
 

1. Data Engineers and Data Architects.
2. Cloud Infrastructure Engineers.
3. DevOps and Platform Engineers.
4. Database Administrators.
5. Big Data and Analytics Professionals.
6. Cloud Solutions Architects.
7. IT Infrastructure Managers.
8. Technology Consultants and Systems Administrators.

Course Duration: 5 days
 
Course Modules

Module 1: Fundamentals of Infrastructure as Code for Data Platforms
 

• Infrastructure as Code concepts, architecture, and automation principles.
• Declarative versus imperative infrastructure management.
• Infrastructure lifecycle management and provisioning strategies.
• Infrastructure as Code integration with modern data engineering.
• Reusable templates, modular design, and configuration standards.
• Case study: Netflix's cloud infrastructure automation and scalable deployment practices.

Module 2: Terraform and Automated Infrastructure Provisioning
 

• Terraform architecture, providers, resources, and configuration files.
• Managing Terraform state, variables, outputs, and modules.
• Automating cloud infrastructure deployment.
• Implementing reusable Terraform modules for data platforms.
• Infrastructure provisioning across AWS, Azure, and Google Cloud.
• Case study: Spotify's cloud infrastructure and automated platform engineering practices.

Module 3: Configuration Management with Ansible and Pulumi
 

• Ansible playbooks, inventories, roles, and automation workflows.
• Infrastructure configuration and environment management.
• Pulumi programming-based infrastructure provisioning.
• Managing dependencies and reusable configuration components.
• Integrating configuration management with data platform deployment.
• Case study: Red Hat's enterprise automation practices using Ansible.

Module 4: Cloud Infrastructure for Modern Data Platforms
 

• Provisioning cloud-based data lakes and data warehouses.
• Automating storage, networking, and compute resources.
• Deploying Amazon S3, Azure Data Lake Storage, and Google Cloud Storage.
• Infrastructure automation for Snowflake, Databricks, and cloud databases.
• Designing scalable and resilient cloud data environments.
• Case study: Capital One's cloud transformation and automated infrastructure management.

Module 5: CI/CD, GitOps, and Infrastructure Automation
 

• Git version control and collaborative infrastructure development.
• Integrating Terraform with Jenkins, GitHub Actions, and GitLab CI/CD.
• Automated infrastructure deployment and approval workflows.
• Implementing GitOps using Argo CD and Flux.
• Infrastructure testing, validation, and rollback strategies.
• Case study: Google Cloud's infrastructure automation and continuous delivery practices.

Module 6: Kubernetes and Containerized Data Infrastructure
 

• Kubernetes architecture and infrastructure provisioning.
• Automating containerized data engineering environments.
• Managing Helm charts, namespaces, and cluster configurations.
• Deploying Apache Spark and distributed data processing workloads.
• Implementing infrastructure scaling and workload orchestration.
• Case study: Airbnb's use of large-scale data infrastructure and distributed processing technologies.

Module 7: Infrastructure Security, Governance, and Cost Optimization
 

• Implementing secrets management and identity access controls.
• Policy as code using Open Policy Agent and Sentinel.
• Infrastructure compliance, auditing, and security automation.
• Cloud resource tagging, monitoring, and cost optimization.
• Implementing backup, disaster recovery, and infrastructure resilience.
• Case study: Microsoft Azure's enterprise cloud governance and security management practices.

Module 8: Advanced Infrastructure as Code Implementation and Capstone
 

• Designing end-to-end automated data platform infrastructure.
• Developing reusable infrastructure modules and deployment pipelines.
• Implementing infrastructure monitoring and observability.
• Testing infrastructure reliability, scalability, and performance.
• Building production-ready infrastructure automation solutions.
• Case study: JPMorgan Chase's enterprise cloud engineering and infrastructure modernization initiatives.

Training Methodology
 

• Instructor-led presentations and technical demonstrations.
• Hands-on Terraform, Ansible, and Pulumi practical laboratories.
• Cloud infrastructure provisioning and configuration exercises.
• Group discussions and international industry case studies.
• Scenario-based infrastructure automation projects.
• Practical capstone projects and knowledge assessments.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.
 
b. Upon completion of training the participant will be issued with an Authorized Training Certificate
 
c. Course duration is flexible and the contents can be modified to fit any number of days.
 
d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
 
e. One-year post-training support Consultation and Coaching provided after the course.
 
f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.