Container Runtime Basics

How Assistance treats Docker and containers in managed infrastructure engagements

Docker and OCI containers are the packaging layer many Assistance engagements use for applications, runners, internal tools, and platform services. This guide is not a generic Docker tutorial; it explains how containers fit into Assistance-operated infrastructure and what your team must own before a workload is production-ready.

When to use containers#

Situation	Fit
Consistent local, CI, and production packaging	Good fit when build inputs, base images, and runtime configuration can be made repeatable
Services moving toward Kubernetes or GitOps	Good fit when the deployment target expects immutable images and health checks
CI/CD jobs and self-hosted runners	Good fit for isolated build tools, test dependencies, and repeatable execution environments
Stateful databases or message brokers	Use only with an explicit storage, backup, upgrade, and recovery plan
Unmaintained legacy applications	Assess first; containerizing an unsafe or undocumented app does not make it operated

What Assistance operates#

Area	Assistance responsibility
Runtime baseline	Container runtime selection, host hardening, service supervision, logging, and restart policy inside the agreed boundary
Image workflow	Recommended build pattern, registry integration, tag policy, and promotion workflow
Security baseline	Non-root runtime guidance, secret handling pattern, vulnerability scanning workflow where scoped, and network exposure review
Observability	Container health checks, logs, metrics, disk and memory alerts, and escalation routing for managed hosts
Change management	Planned runtime upgrades, base-image refresh coordination, rollback notes, and maintenance windows
Incident triage	Platform-level failures such as runtime, host, registry, image-pull, and resource-exhaustion issues

What the customer owns#

Area	Customer responsibility
Application behavior	Entrypoints, readiness behavior, graceful shutdown, data compatibility, and release correctness
Image contents	Application code, dependencies, licenses, base-image choices, vulnerability remediation, and SBOM accuracy unless separately contracted
Configuration	Business settings, environment-specific values, feature flags, and application secret consumption
Data	Data classification, persistence requirements, legal retention, and acceptance of backup/restore outcomes
Release decisions	When to deploy, when to roll back, and who approves production changes

Containers are not the operating model

A container image is only one input. Production operation also needs ownership, monitoring, secrets, storage, rollback, patching, and incident procedures. Assistance accepts responsibility only for the scoped platform boundary.

Normal onboarding workflow#

Workload review — identify runtime, ports, dependencies, state, secrets, health checks, resource needs, and compliance constraints.
Image and registry plan — define Dockerfile standards, base images, tags, signing or scanning needs, and repository ownership.
Runtime design — choose host, Compose, Kubernetes, runner, or managed service target; document networking, storage, and restart behavior.
Go-live preparation — configure logs, metrics, alerts, rollback path, access, and support severity.
Operate and improve — review failed deployments, image vulnerabilities, runtime capacity, and platform drift.

Normal change requests#

Use a planned request for base-image upgrades, runtime version changes, new ports, new volumes, registry changes, resource increases, or changes to secrets delivery. Emergency requests are reserved for unavailable managed runtime, image-pull failures, host exhaustion, or security issues that affect a covered service.

Getting started#

Bring a representative application, Dockerfile or build script, deployment target, and current pain points. Assistance will map the container boundary and recommend the smallest operating model that keeps the workload safe.

Request infrastructure assessment →