{"id":15069,"date":"2026-01-14T13:45:19","date_gmt":"2026-01-14T05:45:19","guid":{"rendered":"https:\/\/www.cybermedian.com\/in\/docs\/my-document\/module-3-level-2-diving-into-container-diagrams\/technical-decomposition\/"},"modified":"2026-01-15T14:04:11","modified_gmt":"2026-01-15T06:04:11","slug":"technical-decomposition","status":"publish","type":"docs","link":"https:\/\/www.cybermedian.com\/in\/docs\/mastering-c4-model\/module-3-level-2-diving-into-container-diagrams\/technical-decomposition\/","title":{"rendered":"Technical Decomposition"},"content":{"rendered":"
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Breaking systems into separately runnable or deployable units (web apps, microservices, databases)<\/strong><\/p>\n

The core purpose of the Container Diagram<\/strong> (Level 2) is to perform a technical decomposition<\/strong> of your software system \u2014 breaking it down from a single opaque box (as seen in the System Context<\/a>) into its major separately runnable or deployable units<\/strong>.<\/p>\n

This decomposition is not arbitrary. It reflects real architectural and operational boundaries: units that can be built, tested, deployed, scaled, monitored, secured, and (in many cases) replaced or retired independently. These are the containers<\/strong> in the C4 Model.<\/p>\n

What Makes Something a Container?<\/h3>\n

A container is:<\/p>\n

    \n
  • A distinct, cohesive piece of software that executes code<\/strong> or hosts data<\/strong>.<\/li>\n
  • Separately runnable<\/strong> or deployable<\/strong> \u2014 meaning it can be started, stopped, restarted, scaled, or moved without necessarily affecting other containers.<\/li>\n
  • Has a clear runtime boundary<\/strong> \u2014 it runs in its own process, container image, serverless execution environment, or database instance.<\/li>\n<\/ul>\n

    This definition deliberately aligns with how modern systems are actually built and operated \u2014 whether monoliths, microservices, serverless, or hybrid architectures.<\/p>\n

    Common Types of Containers You Will Identify<\/h3>\n

    Here are the most frequent categories you\u2019ll encounter when decomposing almost any real-world system:<\/p>\n

      \n
    1. Web Applications \/ Backends<\/strong>\n
        \n
      • Traditional server-side apps (Spring Boot, .NET Core, Django\/Flask, Node.js Express)<\/li>\n
      • Single-page application (SPA) frontends when hosted separately (React, Angular, Vue served from their own domain\/server)<\/li>\n
      • API-only services \/ REST\/GraphQL backends<\/li>\n
      • Example: \u201cCustomer API\u201d, \u201cAdmin Web Portal\u201d, \u201cPublic Website\u201d<\/li>\n<\/ul>\n<\/li>\n
      • Mobile Applications<\/strong>\n
          \n
        • Native iOS\/Android apps<\/li>\n
        • Cross-platform apps (Flutter, React Native)<\/li>\n
        • Treated as containers because they run independently on user devices and communicate via APIs<\/li>\n
        • Example: \u201ciOS Banking App\u201d, \u201cAndroid Field Service App\u201d<\/li>\n<\/ul>\n<\/li>\n
        • Databases & Data Stores<\/strong>\n
            \n
          • Relational databases (PostgreSQL, MySQL, SQL Server, Oracle)<\/li>\n
          • NoSQL\/document stores (MongoDB, DynamoDB, Cassandra)<\/li>\n
          • Caches (Redis, Memcached)<\/li>\n
          • Search engines (Elasticsearch, OpenSearch)<\/li>\n
          • File\/blob storage (S3, Azure Blob, MinIO)<\/li>\n
          • Example: \u201cPostgreSQL \u2013 Customer Data\u201d, \u201cRedis \u2013 Session Cache\u201d<\/li>\n<\/ul>\n<\/li>\n
          • Message Brokers & Event Streams<\/strong>\n
              \n
            • Queues (RabbitMQ, ActiveMQ, AWS SQS)<\/li>\n
            • Event streaming platforms (Kafka, Amazon Kinesis, Azure Event Hubs)<\/li>\n
            • Example: \u201cKafka \u2013 Order Events\u201d, \u201cRabbitMQ \u2013 Notifications\u201d<\/li>\n<\/ul>\n<\/li>\n
            • Serverless Functions \/ Batch Jobs<\/strong>\n
                \n
              • Individual functions or groups of related functions (AWS Lambda, Azure Functions, Google Cloud Functions)<\/li>\n
              • Scheduled\/cron jobs, ETL processes, background workers<\/li>\n
              • Example: \u201cPayment Processing Lambda\u201d, \u201cDaily Report Generator\u201d<\/li>\n<\/ul>\n<\/li>\n
              • API Gateways \/ Reverse Proxies \/ Ingress<\/strong>\n
                  \n
                • Kong, Apigee, AWS API Gateway, NGINX, Traefik<\/li>\n
                • Often act as containers when they perform routing, rate limiting, authentication<\/li>\n
                • Example: \u201cAPI Gateway\u201d<\/li>\n<\/ul>\n<\/li>\n
                • Third-Party \/ External SaaS Services (treated as black-box containers)<\/strong>\n
                    \n
                  • When they form a distinct integration point with their own identity and deployment boundary<\/li>\n
                  • Example: \u201cStripe \u2013 Payment Processing\u201d, \u201cSendGrid \u2013 Email Delivery\u201d, \u201cAuth0 \u2013 Identity Provider\u201d<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n

                    How to Perform the Decomposition (Step-by-Step)<\/h3>\n
                      \n
                    1. Start from the System Context<\/strong> Take your single \u201cSoftware System\u201d box and ask: \u201cWhat major runnable\/deployable pieces live inside this boundary?\u201d<\/li>\n
                    2. Follow the data and control flow<\/strong>\n
                        \n
                      • Where does user input arrive? \u2192 Likely a web\/mobile frontend or API gateway<\/li>\n
                      • Where is business logic executed? \u2192 Backend services<\/li>\n
                      • Where is data persisted? \u2192 Databases<\/li>\n
                      • Where are events published\/consumed? \u2192 Message brokers<\/li>\n
                      • Where are background tasks run? \u2192 Workers\/functions<\/li>\n<\/ul>\n<\/li>\n
                      • Apply the \u201cindependence test\u201d<\/strong> Could this piece be:\n
                          \n
                        • Deployed to production independently?<\/li>\n
                        • Scaled separately (e.g., more instances of the API than the database)?<\/li>\n
                        • Developed by a different team?<\/li>\n
                        • Replaced with a different technology without rewriting everything? If yes \u2192 strong candidate for its own container.<\/li>\n<\/ul>\n<\/li>\n
                        • Group logically when needed<\/strong>\n
                            \n
                          • A monolithic backend that can\u2019t be split yet \u2192 one container (\u201cMonolith Backend\u201d)<\/li>\n
                          • A set of tightly coupled microservices that always deploy together \u2192 group as one container until boundaries become clear<\/li>\n<\/ul>\n<\/li>\n
                          • Name containers clearly and consistently<\/strong>\n
                              \n
                            • Use noun phrases that describe responsibility + technology when helpful<\/li>\n
                            • Examples: \u201cWeb Application (React SPA)\u201d, \u201cOrder Service (Spring Boot)\u201d, \u201cPostgreSQL \u2013 Orders\u201d, \u201cKafka \u2013 Event Bus\u201d<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n

                              Key Outcomes of This Decomposition<\/h3>\n

                              By breaking the system into containers, your Container Diagram will reveal:<\/p>\n

                                \n
                              • The technical architecture style<\/strong> (monolith, microservices, serverless, hybrid)<\/li>\n
                              • Communication patterns<\/strong> (synchronous HTTP, asynchronous messaging, direct DB access)<\/li>\n
                              • Technology diversity<\/strong> and potential complexity<\/li>\n
                              • Deployment and scaling realities<\/strong><\/li>\n
                              • Risk hotspots<\/strong> (e.g., single shared database, heavy reliance on one broker)<\/li>\n<\/ul>\n

                                This level of decomposition is where most architecture conversations happen in practice \u2014 because it shows how the system is really built and runs<\/strong> without drowning in code-level details.<\/p>\n

                                In the hands-on section ahead, you\u2019ll take a real or example System Context and systematically decompose it into containers using C4-PlantUML Studio \u2014 identifying boundaries, assigning responsibilities, choosing technologies, and drawing the relationships that make the system function.<\/p>\n

                                Get ready to slice that big box into meaningful, deployable pieces \u2014 this is where the architecture starts to feel real and actionable.<\/p>\n<\/div>\n<\/div>\n

                                <\/section>\n
                                <\/section>\n<\/div>\n","protected":false},"featured_media":0,"parent":15065,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","doc_tag":[],"class_list":["post-15069","docs","type-docs","status-publish","hentry"],"yoast_head":"\nTechnical Decomposition - Cybermedian Indian<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.cybermedian.com\/in\/docs\/mastering-c4-model\/module-3-level-2-diving-into-container-diagrams\/technical-decomposition\/\" \/>\n<meta property=\"og:locale\" content=\"hi_IN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Technical Decomposition - Cybermedian Indian\" \/>\n<meta property=\"og:description\" content=\"Breaking systems into separately runnable or deployable units (web apps, microservices, databases) The core purpose of the Container Diagram (Level\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.cybermedian.com\/in\/docs\/mastering-c4-model\/module-3-level-2-diving-into-container-diagrams\/technical-decomposition\/\" \/>\n<meta property=\"og:site_name\" content=\"Cybermedian Indian\" \/>\n<meta property=\"article:modified_time\" content=\"2026-01-15T06:04:11+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u0905\u0928\u0941\u092e\u093e\u0928\u093f\u0924 \u092a\u0922\u093c\u0928\u0947 \u0915\u093e \u0938\u092e\u092f\" \/>\n\t<meta name=\"twitter:data1\" content=\"4 \u092e\u093f\u0928\u091f\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.cybermedian.com\/in\/docs\/mastering-c4-model\/module-3-level-2-diving-into-container-diagrams\/technical-decomposition\/\",\"url\":\"https:\/\/www.cybermedian.com\/in\/docs\/mastering-c4-model\/module-3-level-2-diving-into-container-diagrams\/technical-decomposition\/\",\"name\":\"Technical Decomposition - 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