Diving into Container Diagrams for Scalable Designs

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Container diagrams are where architecture stops being abstract and starts being actionable. In my years working with teams across startups and enterprises, I’ve seen countless diagrams fail not from bad intent, but because they miss the fundamental goal: clarity under pressure. The C4 model doesn’t exist to make things more complex—it exists to cut through noise.

Too often, beginners jump into creating container diagrams by listing every microservice, database, and API endpoint. That’s not scaling. That’s clutter. The real value comes from identifying just the right building blocks: bounded, well-defined, and clearly responsible. This is where the C4 container diagram becomes a compass.

By the end of this guide, you’ll know how to define containers with purpose, pick the right technologies, and lay the groundwork for scalable design. No fluff. No magic. Just a structured, experience-based approach to modeling systems that grow with your team.

What Is a C4 Container Diagram?

Level 2 of the C4 model focuses on containers—deployable, independently running components like web applications, APIs, mobile apps, or database systems. This is where abstract architecture meets real-world deployability.

Unlike level 1 context diagrams that show users and systems in relation to your application, level 2 zooms in to reveal the actual software artifacts that make up the system.

Each container represents a unit of deployment. It can be a web application, a backend service, a mobile app, a database, or even a legacy system. The key is consistency: one container, one deployment unit.

Core Purpose of the C4 Container Level

Why does this level matter? Because it’s the first point where architecture meets operational reality. It’s where you answer: what runs where? How do they connect? What happens when one container fails?

Think of a container diagram as the blueprint for deployment teams. It’s not about code—it’s about responsibility, ownership, and scalability.

When I first started using C4, I treated containers as interchangeable with microservices. That led to confusion. The breakthrough came when I realized: a container is not defined by size or complexity—it’s defined by deployment independence and responsibility boundaries.

Identifying and Defining Your Containers

Not every component is a container. A shared library or a utility class is not a container. A container must be deployable, independently versioned, and independently managed.

Start by listing all major components that your system must manage. Ask: “Can this run in isolation? Can it be deployed independently?” If the answer is yes, it’s a candidate container.

Common Types of Containers

Web application: A front-end web app (e.g., React app deployed as static files) or a server-side rendered app (e.g., ASP.NET Core MVC).
API service: A REST or GraphQL API exposed to external clients, often written in Node.js, Python, or Java.
Mobile app: An Android or iOS application that communicates with backend services.
Database service: A persistent data store (e.g., PostgreSQL, MongoDB). Note: databases are containers, even if they’re not “code”-based.
Legacy system: An external, non-modern system (e.g., an old mainframe or ERP) that your system interacts with.

Don’t overcomplicate it. A simple e-commerce app might have four containers: web UI, order service, inventory service, and database.

Key Naming Convention

Use clear, consistent names. Avoid overly technical or vague terms like “app1” or “module-b.” Instead, use names that reflect function:

Web UI (Customer Portal)
Order Processing Service
Inventory Management Service
PostgreSQL (Orders Database)

Names should be meaningful to both developers and business stakeholders.

Choosing Technology for Each Container

Technology choice isn’t just about preference. It’s about alignment with deployment, scaling, team expertise, and integration needs.

Here’s a practical checklist to guide decisions:

What deployment platform is used? (e.g., Docker, Kubernetes, AWS Lambda)
Is it stateless or stateful? (e.g., web app → stateless; database → stateful)
Who owns and maintains this container?
How does it scale? Horizontally? Vertically?
What’s the integration pattern? (HTTP, gRPC, message queue?)

The most important rule: avoid mixing technologies unless there’s a clear reason. Diversity can be useful, but only if it’s intentional.

Technology Choice Guide

Container Type	Recommended Tech	Why
Web UI	React, Vue, Angular	Lightweight, fast rendering, great ecosystem
API Service	Node.js, Spring Boot, .NET Core	Strong enterprise support, easy to scale
Background Worker	Python (Celery), Node.js (Bull), Go	Handles async tasks, scalable
Database	PostgreSQL, MongoDB, Redis	Choose based on data model and access patterns

Don’t let tech choice become a default. Ask: “Why is this the right tool for this container’s responsibilities?”

Visualizing Interactions and Boundaries

Lines between containers represent interactions. Use arrows to show direction of flow.

Arrows should not be random. They should reflect actual communication patterns:

Web app → API service: HTTP GET/POST calls
API service → database: SQL queries
Service A → Service B: gRPC or REST API
External system → container: API calls or file exchange

Label your arrows with the communication method. For example: “REST API (GET)”, “gRPC (CreateOrder)”, or “Message queue (async)”.

Use consistent line styles:

Standard solid line: synchronous HTTP/REST
Dashed line: asynchronous (message queue)
Double line: external systems

Color can help, but use it sparingly. Stick to one or two key colors for different types (e.g., blue for internal services, green for databases).

Designing for Scalability

Scalability isn’t just about performance—it’s about how the system behaves under load, and how it’s structured to grow.

Here’s how to embed scalability thinking into your C4 container diagram:

Identify bottlenecks: Where is the single point of failure? Is the database handling all read/write traffic?
Separate concerns: Is the database handling both read and write workloads? Consider splitting into read replicas.
Decouple dependencies: Use message queues or async processing to reduce load on APIs.
Design for horizontal scaling: Ensure containers are stateless so replicas can be added easily.

Include scalability notes directly in the diagram if needed—use a small “scalability” badge or annotation.

Example: “Order service – scales horizontally via Kubernetes. Message queue handles peak loads.”

Remember: a container diagram isn’t just a map—it’s a living document. Update it as you scale.

Best Practices for Creating Container Diagrams

Even the best tools fail without good habits. Here’s what I’ve seen work consistently across teams:

Start with a single application: Don’t try to model the entire system on day one. Focus on the core.
Keep it under 10 containers: If you have more, you’re likely missing a level of abstraction or need to refactor.
Use consistent shapes: All containers should be the same style (e.g., rounded rectangle with a border).
Group related containers: Use a light box or border to group services (e.g., “Ordering Domain”) if needed.
Include a legend: Make it clear what each symbol means—especially for arrow types or colors.

One rule I’ve learned: if you need to explain the diagram to someone for more than 30 seconds, it’s too complex.

Refactor early. Refactor often.

C4 Model Container Level Guide: A Step-by-Step Workflow

Here’s a practical workflow I use with beginners:

Define the system boundary: What are you modeling? A customer portal? An internal platform?
List all deployable components: Ask, “What can be deployed independently?”
Group by function: Are there logical groupings (e.g., “Ordering,” “Payment,” “User Management”)?
Assign technology: What runs in each container?
Draw interactions: Use arrows with labels.
Review and simplify: Remove redundant connections. Merge similar containers if needed.

This process takes 20–40 minutes for a small system. It’s not fast—but it’s safe.

Remember: the goal isn’t perfection. It’s clarity.

Frequently Asked Questions

How many containers should I have in a diagram?

Start with 4–6 containers. More than 10 is a red flag—consider breaking into multiple diagrams or grouping by domain.

Can I have multiple containers in the same deployment?

Yes, but only if they share a deployment unit. For example, a web app and its API might be deployed together. But they remain separate containers.

What if my system has legacy systems or third-party APIs?

Treat them as external containers. Use dashed lines or double borders to distinguish them. Label them clearly (e.g., “AWS S3,” “PayPal API”).

Should I show database schemas in the container diagram?

No. Include only the database name (e.g., “PostgreSQL”) and its role. Schema details belong in component or code diagrams.

How do I handle containers that use multiple technologies?

Use a single container name (e.g., “User Service”) and list the technologies in a note or legend. Avoid cluttering the diagram.

Can I use tools like Visual Paradigm to create C4 container diagrams?

Absolutely. Tools like Visual Paradigm support C4 notation. Use templates and guidelines to maintain consistency. Focus on clarity over aesthetics.

Creating container diagrams is not about aesthetics. It’s about communication. A simple, clean diagram that conveys responsibility, boundaries, and interactions is far more valuable than a complex one filled with color and icons.

Use this guide as your toolkit. Apply it. Refactor it. Share it. The real power of the C4 model lies not in the diagram itself—but in the conversation it enables.