Update a running Docker container with docker update or by redeploying a new image

Outline (brief)

• Opening hook: updating a running Docker container feels like a quick tune-up, not a whole rebuild.

• Path 1: Update on the fly with docker update

• What it changes: resources, restart policy, and other limits without stopping the container

• Simple examples you can try

• Path 2: Deploy a new image for bigger changes

• Build a new image, tag it, and redeploy by replacing the old container

• Quick steps for a clean swap

• Why other options aren’t updates

• Stopping/removing doesn’t refresh the live container

• docker edit isn’t a real command

• Modifying the Dockerfile means a new image, not a live tweak

• Practical tips for smoother updates

• Zero-downtime ideas, rolling updates, and data safety

• Use volumes and testing environments

• Quick-reference commands and a friendly recap

Article: How to refresh a running Docker container without the chaos

Let’s face it: sometimes a running container needs a tweak that doesn’t require a full rebuild. Maybe you want to tighten memory use, give a container a bit more CPU juice, or nudge the restart behavior so it behaves the way you expect after a crash. The good news? Docker gives you a couple of practical, lightweight routes. You don’t have to stop everything and start over every time. You can adjust what’s running now and move on.

Two clear paths to updates

The quick on-the-fly adjustment: docker update

Here’s the thing: you don’t always need to pause a mission-critical service just to change a setting. The docker update command is designed for that moment. It lets you modify certain knobs on a live container—things like how much CPU or memory it can use, or how it should restart if something goes wrong. It’s like turning a dial while the machine is still humming.

Practical examples:

• Give a container more memory and CPUs without stopping it:

docker update --cpus 2 --memory 4g my_container

• Change the restart policy so the container behaves more predictably after a failure:

docker update --restart unless-stopped my_container

If your goal is to fine-tune a running workload, this path is fast, low-friction, and keeps uptime intact. It’s ideal for a quick response to changing load or stricter limits when you notice resource contention in your environment.

A bigger shift: redeploy with a newer image

There are times when the change isn’t just a dial tweak. You’ve updated code, swapped configuration, or added a dependency that requires a fresh image. In that case, the clean, reliable move is to build a new image and redeploy. It’s the standard pattern for meaningful updates.

A simple workflow:

• Build the new image with the updated code or config:

docker build -t myapp:1.2 .

• Stop and remove the old container (or let your orchestrator do the swap):

docker stop myapp

docker rm myapp

• Start a new container using the updated image:

docker run -d --name myapp -p 80:80 myapp:1.2

If you’re using a data store or volumes, keep them attached so your data isn’t lost between the swap. This approach is about starting fresh with the latest code while keeping the same service identity, so users notice continuity rather than a sudden drop-off.

Why not the other options?

You’ll see questions about updates pop up, but not all options actually update what you’re running.

• Stopping and removing the container is tidy, but it’s not updating. You lose the live state and any in-memory data unless you’ve persisted it. It’s like turning off a car to change the engine—then hoping the replacement runs the same. Not ideal for a live system.

• The docker edit command doesn’t exist. If you hear someone mention it, they’re likely mixing up ideas about how containers are managed. There is no built-in Docker command named docker edit.

• Modifying the Dockerfile is a powerful development step, but it doesn’t affect a running container. It’s the blueprint for a future image. To see the effect, you still need to build a new image and redeploy.

So the two paths above—on-the-fly tweaks with docker update and a clean redeploy with a new image—are your go-to moves for updating a running container.

Tips that make updates kinder to your system

Smooth updates aren’t just about what you run; they’re about how you run it.

• Think about zero downtime when you can. If your app can tolerate a brief switchover, you can prepare a new container with the updated image and route traffic to it gradually. In smaller setups, swap containers with minimal interruption by using a load balancer or a reverse proxy that can pulse between versions.

• Keep data safe with volumes. If your app stores state, mount volumes so data lives outside the container. That way, replacing a container doesn’t wipe out your critical information.

• Test changes in a staging environment first. A small bug in a new image can turn a quiet update into a weekend repair job. A separate environment helps you catch issues early.

• Consider orchestration for larger setups. If you’re running multiple containers or services, Docker Swarm or Kubernetes can handle rolling updates, health checks, and rollback strategies. They’re built around the same ideas—update, verify, and continue—without pulling the rug out from users.

• Use meaningful tags. When you deploy a new image, tag it clearly (like myapp:1.2) so it’s obvious what version is running. It’s a simple discipline that pays off during debugging or audits.

• Monitor after an update. A quick check of logs and basic metrics post-update helps you confirm things are running as expected and catch any hiccups early.

A few concrete scenarios

• Tiny tweak, no downtime: You’re tweaking a memory cap to better fit a busy period. A quick docker update --memory 6g --cpus 1.5 my_app works wonders without touching the app itself.

• Major upgrade, clean slate: You push a new code base, rebuild an image, and redeploy. You stop the old container, replace it with the new image, and bring the service back up. If you’re using a persistent database, you still rely on stored data in volumes.

• Rolling upgrade in a service mesh: If you’re in a microservices setup, you might deploy a new version alongside the old one and gradually shift traffic. That’s a more advanced pattern, but it pays off in user-perceived stability.

A quick cheatsheet you can keep handy

• Live tweak:

docker update --cpus 2 --memory 4g my_container

docker update --restart unless-stopped my_container

• Fresh image path:

docker build -t myapp:1.2 .

docker stop myapp

docker rm myapp

docker run -d --name myapp -p 80:80 myapp:1.2

• Data safety basics:

docker volume create mydata

docker run -v mydata:/data --name myapp ...

• If you’re going with orchestration later:

Docker Swarm: look at docker service update

Kubernetes: think in terms of Deployments and rolling updates

A gentle reminder about mindset

Updates are a normal part of keeping software healthy. They aren’t about wasting time; they’re about keeping things reliable and responsive. When you understand the two main routes—live tweaks with docker update and clean redeploy with a new image—you’re ready for the moment when a container needs a tune or a full refresh. It’s a small skill, but it pays off with smoother operations and less anxiety when things get busy.

A small anecdote to tie it together

Imagine you’re maintaining a busy cafe’s digital order system. If you just nudge the thermostat and memory limits in the kitchen computer, the system continues serving customers with minimal hiccups. If you need to push a whole new app version, you don’t leave the kitchen in the dark—you roll out the new image, open a new server, and switch the lights on for customers with a seamless handoff. That balance between quick fixes and careful redeploys is the heart of good container management.

Wrapping it up

When a running container needs an adjustment, you’ve got practical, straightforward options. For light, on-the-fly changes, docker update is your friend. For meaningful, code-driven changes, build a fresh image and redeploy, keeping data safe and users uninterrupted. The other approaches—stopping/removing, something that doesn’t exist, or tweaking a Dockerfile without rebuilding—don’t deliver the same result.

If you haven’t tried these ideas yet, give them a spin in your own environment. A small tweak here, a clean redeploy there, and you’ll start to see how container updates can be as routine as checking your email—efficient, predictable, and quietly powerful.