India - Terraform Devops, Terraform programmer, Terraform developer, Terraform Consultant/Contractor.

Terraform Developer and Terraform DevOps Specialist: IaC Infrastructure as Code

As a seasoned Terraform developer and Terraform DevOps specialist with many years of experience, I've honed my skills in infrastructure as code (IaC) and cloud automation. My terraform consultant expertise lies in designing, implementing, and maintaining robust, scalable infrastructure solutions primarily on various cloud platforms like aws, azure, gcp.

I'm open for short term as well long term contracts.

I'm open for providing mentorship too or ad hoc consulting.

I can work in multiple time zones as per your needs EST, PST, CST, GMT, CET etc

Here I delve into my experience, devops projects, discuss the tools and devops practices I employ, and share insights into overcoming common challenges in the field.

Key areas of expertise working as Terraform contractor:

1. Terraform development and optimization.
2. AWS cloud architecture and services.
3. AZURE and GCP infrastructure.
4. Infrastructure as Code (IaC) best practices.
5. Continuous Integration and Continuous Deployment (CI/CD) pipelines.
6. Cloud security and compliance.
7. Performance optimization and cost management.
8. Collaboration and knowledge sharing in DevOps environments.

Some Terraform Devops Consultant Projects

1. On prem to AWS cloud migration

Project overview: Led the migration of a large e-commerce platform from on-premises infrastructure to AWS, utilizing Terraform for infrastructure provisioning and management.

Key achievements as AWS terraform developer:

• - Designed and implemented a multi-region, highly available architecture using Terraform modules.
• - Automated the provisioning of ECS clusters, tasks, and services for containerized applications.
• - Implemented auto-scaling for ECS tasks to handle variable traffic patterns.
• - Reduced infrastructure deployment time from weeks to hours.
• - Achieved production uptime post-migration.

Some of the Terraform modules utilized:

• - aws_vpc.
• - aws_subnet.
• - aws_ecs_cluster.
• - aws_ecs_task_definition.
• - aws_ecs_service.
• - aws_rds_cluster.
• - aws_elasticache_cluster.
• - aws_lambda_function.

2. Microservices Orchestration Platform

Project overview: Developed a comprehensive microservices orchestration platform for a fintech company, leveraging Terraform and Azure Kubernetes Service (AKS).

Key achievements as AZURE terraform programmer:

• - Created modular Terraform code to provision and manage AKS clusters and node pools.
• - Implemented service mesh using Istio for enhanced network communication and security.
• - Designed a CI/CD pipeline using Azure DevOps, integrated with Terraform.
• - Achieved zero-downtime deployments through rolling update strategies.
• - Reduced operational overhead through automation.

Some of the Terraform modules utilized:

• - azurerm_kubernetes_cluster.
• - azurerm_kubernetes_cluster_node_pool.
• - azurerm_log_analytics_workspace.
• - azurerm_monitor_diagnostic_setting.
• - azurerm_role_assignment.
• - azurerm_container_registry.

3. Serverless Data Processing Pipeline - GCP ETL

Project overview: Architected and implemented a serverless data processing pipeline ETL for an analytics company, using various Google Cloud Platform (GCP) services orchestrated by Terraform.

Key achievements as GCP terraform devops:

• - Designed a scalable, event-driven architecture using Google Cloud Functions, Cloud Storage, and Firestore.
• - Implemented data transformation and enrichment processes using Cloud Dataflow and BigQuery.
• - Created Terraform modules for easy replication of the pipeline across multiple environments.
• - Achieved processing of over 1 billion events per day with sub-second latency.
• - Reduced infrastructure costs by 60% compared to the previous solution.

Some of the Terraform modules utilized:

• - google_cloudfunctions_function.
• - google_storage_bucket.
• - google_firestore_document.
• - google_dataflow_job.
• - google_bigquery_dataset.
• - google_bigquery_table.

Click to call/message +91-9840427955
Send me an email at info@terraform-devops.com

Terraform DevOps Toolchains Used.

While Terraform is the cornerstone of my infrastructure automation workflow, I integrate various Terraform-specific and complementary industry standards tools to create a comprehensive and efficient development pipeline.

Here's an overview of the Terraform-centric toolchain I as terraform contractor typically employ:

1. Version Control: Git with GitHub for managing Terraform configurations.
2. Terraform Cloud: For remote state management, collaboration, and policy enforcement.
3. Terragrunt: To keep Terraform code DRY and manage multi-environment deployments.
4. tflint: A Terraform linter for detecting errors and enforcing best practices.
5. tfsec: A security scanner for Terraform code.
6. Sentinel: HashiCorp's policy as code framework for Terraform.
7. Terraform Docs: Automated documentation generator for Terraform modules.

Terraform Modules and Best Practices

Over the years, I as a terraform software developer developed and utilized various Terraform modules to streamline infrastructure provisioning and maintain consistency across projects.

Some of the most frequently used modules include:

1. Network Module: Creates VPCs, subnets, route tables, and network ACLs.
2. Security Group Module: Defines and manages security groups with standardized rules.
3. Compute Module: Provisions compute resources (EC2, AKS, GCE) with predefined configurations.
4. Database Module: Sets up and manages database instances with proper security and backup policies.
5. Storage Module: Creates storage resources (S3, Azure Blob, GCS) with standardized policies.
6. IAM/RBAC Module: Manages identity and access management across different cloud providers.
7. Serverless Module: Deploys and configures serverless functions (Lambda, Azure Functions, Cloud Functions).
8. Monitoring Module: Sets up monitoring and alerting using cloud-native and third-party tools.

Best practices I adhere to in Terraform development:

1. Use of remote state storage with state locking (e.g., Terraform Cloud, S3+DynamoDB).
2. Implementation of workspaces for managing multiple environments.
3. Extensive use of Terraform modules for reusability and maintainability.
4. Consistent naming conventions and tagging strategies using locals and variables.
5. Use of data sources to query existing resources and make configurations dynamic.
6. Implementation of Terraform import to bring existing resources under Terraform management.
7. Regular use of `terraform fmt`, `terraform validate`, and `tflint` for code quality.
8. Comprehensive documentation using Terraform Docs.
9. Version pinning for providers and modules in a `versions.tf` file.
10. Implementation of proper error handling using `try()` and `can()` functions.

Advanced Terraform Techniques used by consultant.

To further optimize my Terraform workflows, I employ several advanced techniques:

1. Custom Providers: Developing custom Terraform providers for internal tools or unsupported services.
2. Provider Chaining: Using multiple provider configurations to manage cross-account or cross-region resources.
3. External Data Sources: Integrating external scripts or APIs to fetch dynamic data for Terraform runs.
4. Dynamic Blocks: Utilizing dynamic blocks for creating repeatable nested blocks in resource configurations.
5. Terraform Functions: Leveraging built-in functions for string manipulation, numeric operations, and collection handling.
6. State Management: Implementing advanced state management techniques like partial backends and state mv operations.
7. Module Composition: Creating higher-order modules that compose multiple lower-level modules.
8. Terraform Graph Visualization: Using `terraform graph` to visualize and analyze resource dependencies.

+91-9840427955
Send me an email at info@terraform-devops.com

Challenges and Solutions in Terraform Development

1. Large Terraform State Files

Challenge: Managing a Terraform state file exceeding MBs for a company infrastructure with hundreds and thousands of resources, causing slow operations and increased risk of state corruption.

Solution: Implemented state splitting using Terraform workspaces, reducing individual state file sizes to under acceptable size. Developed a custom Python script to safely perform `terraform state mv` operations, migrating resources between states. Utilized S3 backend with DynamoDB locking, setting `max_parallel` to a number for optimized concurrent operations. This approach reduced `terraform plan` execution time.

2. Terraform Upgrade Management

Challenge: Upgrading Terraform version across many projects with 1000s of lines of HCL code, while ensuring backward compatibility and minimal disruption.

Solution: Developed multi-phase upgrade pipelines:

1. Syntax check.
2. Automated updates with `terraform upgrade.
3. Custom regex-based script to update deprecated interpolation syntax.
4. Parallel testing of updated configs in isolated AWS,AZURE,GCP accounts.
5. Automated application testing.
6. Gradual rollout canary or blue/green starting with non-production environments.

3. Complex Module Dependencies

Challenge: Managing a hierarchical module structure with 5 levels of nesting and tens of interdependent modules, causing circular dependencies and unpredictable apply sequences.

Solution:

1. Implemented strict semantic versioning (SemVer) for all modules.
2. Utilized Terragrunt with a custom `dependencies` block to explicitly define module relationships.
3. Developed a Python-based dependency graph tool using NetworkX library to visualize and analyze module dependencies.
4. Refactored modules to use data sources instead of direct references where possible, reducing tight coupling implemented loose coupling.
5. Implemented a custom Terraform wrapper that performs a topological sort of modules before applying.

4. Terraform Performance Optimization

Challenge: Slow Terraform operations in a large-scale infrastructure with thousands of resources, where `terraform apply took hours.

Solution:

1. Implemented parallelization by setting `parallelism in Terraform configuration.
2. Developed a custom Golang Go-based CLI tool to perform intelligent `-target` applies based on git diff.
3. Utilized `depends_on` and `lifecycle` blocks strategically to optimize terraform resource creation order.
4. Implemented a custom provider to batch API calls for resource checks.
5. Employed Terraform's `-refresh=false` and `-parallelism=` flags for faster plan/apply operations.

5. Multi-Cloud Terraform Configurations

Challenge: Maintaining consistent Terraform configurations across AWS, Azure, and GCP for a multi-cloud infrastructure with hundreds of resources per cloud.

Solution:

1. Developed a set of cloud-agnostic modules using Terraform's `count` and `for_each.
`
2. Created a custom validation framework using `terraform validate` with many policy checks.
3. Implemented a abstraction layer using `locals` and `variables` to normalize provider differences.
4. Utilized Terraform workspaces to manage separate states for each cloud provider.
5. Developed a custom Terraform plugin in Go Golang to provide unified logging across clouds.

Click to call/message +91-9840427955
Send me an email at info@terraform-devops.com

By focusing on these Terraform-specific tools, practices, and challenges, I as a terraform devops programmer been able to maximize the effectiveness of Infrastructure as Code in my projects, ensuring scalable, maintainable, and efficient cloud infrastructure management.

Also I'm located in Chennai, India, So I can offer my services under your budget.