Cloud Architectures using IaC

Habitat3 specialises in designing, coding, and deploying AWS Cloud architectures using Infrastructure as Code with Terraform.

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Design
We collaborate with your team to understand your application’s needs and create a design that aligns with best practices. This is documented in a clear, detailed architecture diagram.

 

Coding
We translate the design into Terraform code, enabling consistent, repeatable, and efficient deployments.

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Deployment
We deliver both test and production deployments of the Terraform code — whether it’s a complete new environment or enhancements to existing infrastructure.

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What are the most common architectures?

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1. Single Server Architecture

This is the simplest form of architecture where everything runs on a single server. It’s often used for smaller applications, proof-of-concept projects, or development environments. While cost-effective and easy to manage, it lacks scalability and reliability, as everything is a single point of failure.

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Pros of Single-Server Cloud Architecture

• Cost-Effective: Running a single server reduces infrastructure costs, making it budget-friendly, especially for small-scale applications or startups.

• Simplified Management: With everything on one server, there's less complexity in managing and maintaining different services, making it easier to monitor and troubleshoot issues.

• Lower Latency for Small Loads: Communication within a single server is faster than inter-server communication, potentially offering lower latency for small, lightweight applications.

• Easier Backup and Recovery: Backup and restoration are straightforward, as all components reside on the same machine.

• Energy Efficiency: Reduced infrastructure lowers the energy footprint, which can be beneficial for companies focusing on sustainable practices.

 

Cons of Single-Server Cloud Architecture

• Single Point of Failure: If the server goes down, the entire application becomes unavailable, which risks business continuity.

• Limited Scalability: Scaling is challenging as the single server has finite resources. Once the limit is reached, transitioning to a multi-server or distributed architecture may be costly and time-consuming.

• Resource Contention: Different services (database, application, etc.) compete for the same resources, which can cause performance issues as the application grows.

• Security Risks: All components on one server increase the attack surface. If the server is compromised, every part of the application is at risk.

• Limited Redundancy and Resilience: Without replication or distributed components, data and service redundancy are minimal, increasing risks related to data loss or downtime.

 

Best Use Cases of Single-Server architecture

Single-server architecture suits small projects, MVPs (minimum viable products), or low-traffic applications where simplicity and cost savings are priorities. However, as applications grow or require high availability, transitioning to a 3-Tier or containerised environment is needed.

2. Multi-Tier Architecture
The 3-tier model is a classic architecture, typically involving a presentation layer (UI), an application layer (business logic), and a data layer (database). This architecture allows for modularity, better scalability, and separation of concerns, making it highly suitable for cloud-hosted applications that require reliability and structured data handling.

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Pros of 3-Tier Architecture

• Scalability: Each tier can be scaled independently. For example, the application layer can scale up or down based on demand, and the database layer can be managed separately, making it well-suited for fluctuating traffic loads.

• Improved Reliability: By separating each layer, failure in one tier (e.g., the database server) does not necessarily bring down the entire application. This setup enhances overall uptime and reliability.

• Enhanced Security: Each layer can have specific security configurations, like restricting direct database access to the public and implementing robust security measures for each tier.

• Maintenance and Manageability: Modifications to a specific layer are possible without affecting the others, making it easier to update or troubleshoot individual components.

• Better Performance Optimization: Each tier can be optimized individually, allowing for resource allocation tailored to specific functions, which can enhance the application’s performance.

• Flexibility and Modularity: Layers can be independently developed, maintained, and upgraded. This modular approach also supports distributed teams and different development languages for each layer.

 

Cons of 3-Tier Cloud Architecture

• Higher Cost: Maintaining separate servers or instances for each layer incurs additional costs, especially with increased traffic or higher resource demands.

• Increased Complexity: Managing and maintaining multiple layers adds complexity to deployment, monitoring, and troubleshooting, requiring a more skilled IT team and sophisticated tools.

• Latency: Communication between layers introduces latency, which can affect response times. Optimizations may be needed to mitigate delays in high-performance applications.

• Dependency Management: Synchronizing updates or ensuring compatibility between layers requires careful management, especially during deployments or version upgrades.

• Network Dependency: Network issues can impact inter-tier communication, which could slow down the entire application if one layer fails to communicate efficiently with others.

• Potential for Data Bottlenecks: The database layer, if not properly optimized or scaled, can become a bottleneck, impacting the performance of the whole application.

Best Use Cases of 3-Tier architecture

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3-tier architecture is ideal for medium to large web applications that expect growth, have variable traffic, or require high availability, performance, and security. It’s also suitable for applications that need clear separation between user interface, application logic, and data, such as e-commerce platforms, content management systems, and enterprise software.

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3. Container-Based Architecture

Containers are increasingly popular for cloud applications, offering an isolated environment for applications and their dependencies. This architecture enables microservices-based designs, allowing applications to be broken into smaller services that are easier to scale and maintain. Tools like Docker and Kubernetes make managing container-based architectures efficient.

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Pros of containerised architecture 

• Portability - Containers package applications with all their dependencies, making them highly portable across different environments, from development to testing and production, without worrying about environment-specific configurations.

• Consistency and Reproducibility - Containers help maintain a consistent environment across different stages of development and deployment. This reduces the "works on my machine" problem, as the application environment can be replicated easily.

• Scalability - Containers are lightweight and start up quickly, making them ideal for scaling applications. Orchestration tools like Kubernetes can be used to manage containerised applications, providing features like load balancing, scaling, and self-healing.

• Resource Efficiency - Unlike traditional VMs, containers share the host OS kernel, which makes them more lightweight. This can lead to better resource utilisation, allowing more applications to run on a single server, thus reducing infrastructure costs.

• Isolation - Containers offer process isolation, meaning that if one containerised application crashes, it doesn't directly affect others on the same host. This improves security and stability.

• Fast Deployment and Rollback - Containers allow rapid deployment and easy rollbacks. This is particularly useful in CI/CD workflows, as developers can build, test, and deploy applications in a streamlined manner.

• Simplified Dependency Management - By encapsulating all dependencies within the container, containers simplify dependency management, especially for complex applications that require specific library versions. 

 

Cons of containerised architecture

• Complexity in Orchestration and Management - Managing a large number of containers, especially in a microservices architecture, requires orchestration tools like Kubernetes, which can be complex to set up, configure, and maintain.

• Networking Overhead - Container networking can be complex and sometimes less efficient than traditional setups, especially in large-scale environments where inter-container communication needs to be managed and secured.

• Storage Challenges - Containers are stateless by design, making persistent storage challenging. Solutions exist (e.g., persistent volumes in Kubernetes), but setting up and managing storage for containerised applications can be complex.

• Limited Support for Certain Applications - Not all applications are suitable for containerisation. Applications with complex dependencies on the host system or those requiring specialised hardware access may be difficult to containerise effectively.

• Learning Curve and Tooling Overhead - While containers offer many advantages, there is a learning curve involved in setting up and using containers effectively, especially when adopting tools like Docker, Kubernetes, and related CI/CD integrations. 

 

​Best Use Cases for Containerised Architecture

Containerised architecture provides very high levels of portability, scalability and resource efficiency.  These and the other features of this architecture suit high-demand commercial applications including E-commerce platforms, media streaming services, and complex SaaS products that need modularity and resilience. Great CI/CD integration means SaaS applications or any web app that requires frequent updates, such as customer support portals, content management systems, or social media platforms would suit. Containers' scalability means News sites, online marketplaces, ticketing systems, and any web app with variable or seasonal traffic spikes would also benefit.

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4. Serverless Architecture

Serverless architecture allows developers to build and run applications without managing the underlying infrastructure. Instead of provisioning or scaling servers, developers write and deploy code that runs in response to events. With serverless, AWS handles server provisioning, scaling, fault tolerance, and availability automatically.

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This model enables faster development cycles and cost-effective scaling—particularly for modern, event-driven applications or microservices.

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Examples of AWS services we use in serverless environments include:

• AWS Lambda – for backend compute and event-driven functions.

• AWS App Runner – for easily deploying containerised web applications without managing infrastructure.

• AWS Amplify – for quickly deploying and hosting frontend applications with integrated backend support.

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Pros of Serverless Architecture

• No Server Management – Developers focus solely on code. AWS manages the provisioning, scaling, and operations of the backend resources.

• Automatic Scalability – Functions and applications scale automatically based on traffic or event volume, without any manual configuration.

• Cost Efficiency – You only pay for what you use (e.g., per request or per execution time), making it ideal for applications with irregular traffic.

• Rapid Deployment – Serverless platforms enable fast iterations, streamlined CI/CD pipelines, and reduced deployment overhead.

• Built-in Fault Tolerance – Services like Lambda and App Runner include high availability and retry logic by default.

• Fine-Grained Microservices – Serverless encourages modular design, allowing teams to deploy isolated services independently.

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Cons of Serverless Architecture

• Cold Starts – Functions (like those in Lambda) may experience startup latency if they haven't been recently invoked, potentially affecting user experience in latency-sensitive apps.

• Vendor Lock-In – Serverless solutions are often tightly coupled with a specific cloud provider’s ecosystem, making migration more complex.

• Complex Debugging and Monitoring – With highly distributed logic and asynchronous behaviour, troubleshooting can be harder than in traditional architectures.

• Resource Limits – AWS Lambda and similar services have execution time limits, memory constraints, and other restrictions that may not suit all workloads.

• State Management Challenges – Serverless environments are stateless by default. You’ll need to integrate with databases or storage services to maintain session data or user context.

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Best use cases for Serverless Architecture

Serverless architecture is an excellent fit for:

• Startups or MVPs needing rapid development and minimal ops overhead

• Event-driven applications, such as user notifications, file uploads, or real-time analytics

• SaaS platforms where services can be independently scaled and deployed

• Mobile and web backends that need to scale quickly and handle burst traffic

• APIs and microservices that benefit from modular, loosely coupled design

 

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