Multi-Cloud Strategy? Benefits and Challenges.. ( and IaC vs Control Planes )

Businesses are Business ever and they are always running away from the falacy of lockin and now they are looking to the multi-cloud stage as a way to have freedom. But managing this multi-cloud reality can feel like conducting a symphony with instruments from different orchestras, it might be complex, demanding, and potentially chaotic. This is where Infrastructure as Code (IaC) and Control Planes initiate, acting as the main heroes bringing harmony to the chaos.

IaC: The Script for Infrastructure Automation

Imagine IaC as writing a detailed script for your infrastructure. Instead of manually clicking through console menus, you define your desired state in code. Tools like Terraform, CloudFormation, and Pulumi become your stagehands, automating the creation, configuration, and versioning of resources. Need a fleet of Kubernetes clusters across AWS and Azure? IaC lets you define that declaratively, ensuring consistency and repeatability. It’s about empowering your team to treat infrastructure like software, enabling version control, collaboration, and rapid deployments. Think of it as giving your developers the power to “git push” their infrastructure into existence.

Control Planes: The Orchestrator of Multi-Cloud Complexity

As your multi-cloud environment expands, managing individual IaC scripts across multiple providers becomes a Herculean task. This is where Control Planes, like Crossplane and KRO shine. They act as the central orchestrator, extending Kubernetes to manage resources across AWS, Azure, GCP, and beyond. They abstract away the vendor-specific nuances, offering a unified API for managing everything from databases to load balancers. This means your team can define a “desired state” once, and the Control Plane ensures it’s consistently applied across all your clouds. It’s like having a universal remote for your entire cloud infrastructure, simplifying complex workflows and ensuring consistent policy enforcement.

What are the Differences Between IaC vs. Control Plane?

IaC focuses on the individual “bricks” — the resources themselves. Control Planes, on the other hand, provide the “blueprints” for the entire multi-cloud “house.”

Focus:

• Infrastructure as Code (IaC): Automating the creation and management of individual infrastructure resources.
• Control Plane: Orchestrating and managing complex infrastructure across multiple clouds, providing a unified control plane.

Functionalities:

• Infrastructure as Code (IaC): Provisioning, configuration management, version control, and resource lifecycle management.
• Control Plane: Multi-cloud resource management, abstraction of cloud-specific APIs, automated workflows, policy enforcement, and drift reconciliation.

Scope:

• Infrastructure as Code (IaC): Resource-level management, often focused on a single cloud or application.
• Control Plane: Management of the entire multi-cloud environment, providing a higher level of abstraction.

“Drift”:

• Infrastructure as Code (IaC): Detects configuration drift, but requires manual or additional automation to correct.
• Control Plane: Automatically reconciles drift, ensuring the infrastructure matches the desired state.

Tool Examples:

• Infrastructure as Code (IaC): Terraform, CloudFormation, Pulumi, Ansible.
• Control Plane: Crossplane, Anthos Config Management, Azure Arc.

Limitations:

• Infrastructure as Code (IaC): Potential for complexity in large environments, requires expertise in specific IaC tools, and challenges in managing cross-cloud dependencies.
• Control Plane: Introduces a layer of complexity, requires familiarity with Kubernetes and Control Plane concepts, and potential for vendor lock-in at the control plane level.

Benefits:

• Infrastructure as Code (IaC): Reduced manual effort, increased deployment speed, enhanced consistency, and improved collaboration.
• Control Plane: Simplified multi-cloud management, reduced operational overhead, improved security and compliance, and increased agility.

The Human Side of Multi-Cloud Challenges

Managing three or more clouds isn’t just a technical challenge; it’s a human one. Teams need to develop specialized expertise across multiple platforms, leading to potential skill gaps and increased staffing costs. Developers face the daunting task of writing code that works seamlessly across different environments. And let’s not forget the ever-present fear of vendor lock-in, where a seemingly convenient managed service can become a costly trap.

Technical Hurdles and Human Solutions

• Skill Gaps: Invest in cross-training and create shared knowledge repositories. Foster a culture of collaboration where teams can learn from each other.
• Interoperability: Embrace open standards and APIs. Use tools that abstract away cloud-specific differences.
• Cost Management: Implement cloud cost optimization tools and regularly review your spending.
• Security and Compliance: Adopt a zero-trust security model and automate compliance checks.

(Re)writing Cloud Native Features

Cost has various dimensions, including People, Process, Time, Products, and Quality, among others. When considering these factors and aiming for a cloud-agnostic approach, you may encounter challenges related to your choices of cloud-native services. This could involve deciding whether to utilize a feature available in a particular cloud service or to develop the same feature from scratch to maintain full cloud-agnosticism.

For example, AWS Step Functions is a serverless orchestration service that allows developers to coordinate multiple AWS services into serverless workflows using visual workflows and state machines. It is deeply integrated with services like AWS Lambda, ECS, Glue, and more, making it a powerful native orchestration tool. As of April 2025, Google Cloud Platform (GCP) does not offer a fully equivalent native service with the same level of integration, state management, and retry/error handling mechanisms. While GCP offers Workflows, its capabilities are not on par with AWS Step Functions in terms of features like parallel execution branches, integration with third-party APIs via connectors, and native support for AWS ecosystem services.

Choosing to use AWS Step Functions might improve development velocity and reduce operational complexity in AWS-centric environments. However, building similar orchestration logic from scratch to remain cloud-agnostic would require custom code, possibly using open-source workflow engines (e.g., Temporal or Apache Airflow), increasing the complexity, cost, and maintenance effort.

If you choose to adopt a multi-cloud strategy, you will likely need to develop and manage all features across both cloud providers to ensure consistency and to oversee their lifecycle effectively. In contrast, if you stick to just AWS, you can quickly implement the Step Functions service in just a few minutes. Additionally, in the future, you may need to hire or develop an observability tool that covers all cloud service providers (CSPs). This tool will help your team easily identify and troubleshoot any issues, as the causes may vary depending on the cloud provider.

Ultimately, navigating the multi-cloud landscape requires a blend of technical expertise and human collaboration. By embracing IaC and Control Planes, and by addressing the human challenges, organizations can unlock the potential to create workloads, but sometime you may need to re(code) something that is in just one cloud provider. Additionally, you may need more people, or more skills to manage and sustain different kinds of incidents or upgrades. It is a matter of where you want to focus on…