Containerization consulting involves analyzing the runtime, dependencies, state, file system, and configuration of existing monolithic or legacy applications to transform them into a Docker-based, repeatable, and scalable microservices/container architecture.
Directly moving applications into a container environment by writing a Dockerfile can lead to session (session) loss, data security vulnerabilities, and performance bottlenecks. A successful containerization process requires an architecture analysis based on the 12-Factor App principles.
The process includes separating build/runtime, implementing Multi-Stage Build approaches, optimizing image sizes (minimal base images), managing writable layers, log/Stdout streams, graceful shutdown mechanisms, healthcheck policies, config and secret management throughout the design.
The application's runtime, stateless/stateful structure, local file system (local disk) dependencies, database connections, and network (network) requirements are analyzed according to the 12-Factor App principles.
Selection of minimal base images (Alpine, Distroless, etc.), implementation of Multi-Stage Build architecture, non-root user (non-root user) permissions, and image scanning steps are determined.
Configuration management with environment variables, Docker Secrets, persistent volume strategies, healthcheck/readiness definitions, and logging (stdout/stderr) standards are established.
Selection of pilot services, test environments with Docker Compose, integration of image build steps into CI/CD pipelines, canary/blue-green transition strategies, and rollback plan preparation.
Assess the current environment, target and dependencies
Document scope, risks, acceptance and rollback
Implement, validate and document
Theoretically, most applications can be containerized; however, the cost of transformation may increase for applications that require direct kernel access, have a desktop graphical user interface (GUI) dependency, use hardware-locked licensing, or have a highly stateful architecture.
No, because Docker uses operating system-level isolation (Namespace/Cgroups) instead of a hypervisor, the overhead on CPU and memory is negligible. Performance losses will not occur if disk I/O and network configurations are properly designed.
It may be necessary. Especially redirecting logs to stdout/stderr, moving sessions (sessions) to In-Memory Redis/Memcached, using environment variables instead of fixed file paths, and making minor code revisions for graceful shutdown processes.
We review your current environment, target and technical requirements in a 20–30 minute call. Scope, assumptions, deliverables and pricing are documented before work begins.
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