Podman vs Docker for Edge Sites: Does Your Choice Matter at Scale?

Podman vs Docker comes down to one design difference: Docker runs containers through a central daemon, Podman runs them without one. Both run the same standard container images. At hundreds of sites, the engine matters less than choosing one default per operating system and managing every site the same way.

A container engine is the software on each machine that downloads container images and starts, stops and restarts the applications inside them. If your teams have brought up podman vs docker, the real questions are about risk, support and skills, and the answer repeats on every machine you run.

This article is for leaders who answer for applications across many stores, factories or machines. We compare the engines side by side, cover rootless containers, storage, networking, hardware and performance, and end with a practical way to decide.

Podman vs Docker in Plain Terms: What a Container Engine Does at Each Site

Docker is built around a daemon. A daemon is a background service that runs all the time. In Docker’s case it is called dockerd: your commands go to it, and it creates and supervises every container on the machine. By default the daemon runs as root, the all-powerful administrator account on Linux.

Podman has no daemon. Each Podman command starts the container directly, and a small monitor process watches each container on its own. Containers can run as root or as a regular user, and services start at boot through systemd, the standard Linux service manager.

When people compare docker vs podman, they often start with the commands. There the difference is small: Podman accepts most Docker commands.

Will an application built for one engine run on the other? Yes. Both follow OCI, the Open Container Initiative, a set of open standards for how container images are packaged, stored and started. An OCI image runs on Docker, Podman or any compatible runtime. We explain why this matters in OCI is the container standard, Kubernetes is not.

That portability is also why containers suit the edge so well. A container behaves the same on a store server, a line-side PC or an industrial gateway, and each application can be updated on its own instead of rebuilding a full system image per site. Gartner expects 80% of custom software at the physical edge to run in containers by 2028 (Gartner, 2023). New to the concept? Start with What are containers?.

The engine choice deserves attention because it repeats on every machine. Two illustrations, not customer stories:

• A retailer with 800 stores and two servers per store makes the engine decision 1,600 times. Every exception becomes an unplanned support case.
• A manufacturer with 40 plants has line-side machines from different years and operating system versions. Some can run current Podman, some cannot.

The Avassa Edge Platform works with both. The Avassa Edge Enforcer, the agent on every host, is delivered as a container and runs on Docker or Podman. Our install script sets up Docker by default, or Podman with a flag. Podman must be version 4.0 or later, so at least Debian 12, Ubuntu 22.04, CentOS 9 or RHEL 9.

Area	Docker	Podman
How it is built	A central daemon (dockerd) manages all containers	No daemon. Each container runs as its own process with a small monitor
Default privileges	Daemon runs as root. Rootless mode is an option	Runs as root or as a regular user. Rootless works out of the box for non-root users
Where images and data are stored	/var/lib/docker (rootless: ~/.local/share/docker)	/var/lib/containers/storage (rootless: ~/.local/share/containers/storage)
Networking at engine level	Bridge networks and firewall rules managed by the daemon	Netavark networks when run as root. User-mode networking (pasta or slirp4netns) when rootless
Start at boot and restart	The daemon starts at boot and applies restart policies	systemd units start and restart containers
Avassa Edge Enforcer support	Yes, the default install	Yes, Podman 4.0 or later

When the Avassa Edge Platform manages a site, several rows matter less: the platform handles networking, the host firewall, scheduling and restarts itself, on either engine.

Keep reading: Buyer’s guide for Machine builders: an OS or Application Orchestration decision?

Why Podman vs Docker Reaches the Leadership Table

The question usually arrives from three directions: the security team asks about root access, the IT or platform team asks what fits the machines already in place, and operations asks who supports it at 3 a.m. Behind the debate sit four business concerns:

Security exposure at unstaffed sites. Edge machines sit in back offices, on factory floors and inside customer equipment, often unwatched. A component running as root on every one of them is a larger target.

Compatibility with the hardware and operating systems already in place. You rarely choose the operating system on every machine. Older hosts may not support current Podman, and Red Hat systems ship Podman, not Docker.

Support and skills. Your teams know one engine better, and your runbooks are written for it. Switching has a training cost no feature comparison shows.

Consistency across every site. The real risk at scale is drift: stores on different engines, each configured slightly differently.

So treat it as a decision about risk and standardization, not a technology contest. Both engines are mature. What hurts is deciding differently at each site.

Rootless Containers: The Security Question Behind the Debate

Rootless containers run the container engine and its containers as an ordinary user instead of root. Inside the container, the application may still believe it is root. On the host, Linux user namespaces, a kernel feature that maps user IDs inside a container to different IDs outside it, turn that into an unprivileged account.

This matters at the edge because machines are unattended and physically reachable. An attacker who breaks out of a rootless container lands as an ordinary user, not as the machine’s administrator.

The Docker daemon risk security teams talk about follows from its design. The daemon runs as root, and anything that can talk to its API socket can, in effect, control the host.

Keep it in proportion. Rootless containers limit the damage of a breakout. They do not fix a vulnerable application, patch an image, protect data on a stolen disk or stop an attack over the network. They are one layer, not the whole defense.

Podman Rootless: How It Works and Where It Stops

With podman rootless, a regular user runs Podman, and the container’s users are mapped into a range of user IDs the host reserves for that user. Images live in the user’s home directory, and networking runs through a user-mode stack: pasta by default since Podman 5.0, or the older slirp4netns.

What it cannot do easily, according to the Podman rootless tutorial and its documented shortcomings:

• Bind to ports below 1024. The kernel reserves low ports, such as 80 and 443, for privileged processes. A kernel setting or traffic redirect works around it, on every host.
• Network like root. User-mode networking is slower, and with pasta, containers cannot reach the host’s main IP address without extra configuration.
• Reach protected host paths and block devices. Root-owned files and devices stay out of reach, and creating device nodes inside a container fails.
• Enforce resource limits everywhere. CPU and memory limits need cgroup v2, the newer Linux resource control system.

Rootless Docker: What You Gain and What You Give Up

Rootless docker runs both the daemon and the containers inside a user namespace, using a helper called RootlessKit. That differs from Docker’s user namespace remapping, where containers map to an unprivileged user but the daemon still runs as root.

What you give up, according to the Docker rootless mode documentation:

• Ports below 1024 need extra configuration, and networking runs through a slower user-mode stack.
• AppArmor profiles and overlay networks are not supported.
• Resource limits need cgroup v2 and systemd.
• Added capabilities apply only inside the container’s namespace, not to the host.

Is rootless Docker worth it? Yes, for hosts where no workload needs low ports, host devices or host networking, and a security rule says nothing may run as root. For line-side machines with cameras, fieldbus adapters and GPUs, the trade-offs add up fast, and many teams choose a rootful engine with tight per-container restrictions instead.

That is the approach we take in the Avassa Edge Platform:

• No privileged containers. As our Docker feature map explains, you grant only the capabilities, devices or system paths an application needs.
• User namespaces by default on Docker. Our install script enables Docker’s user namespace remapping, which you can turn off for sites that need host networking.
• Outbound access closed by default. A container cannot open outbound connections unless its specification allows it.
• Networking and firewall handled by the platform. The platform runs application networking and the host firewall itself, using nftables.

The Edge Enforcer itself runs on Docker or Podman with the privileges it needs to start and monitor containers, which is why we put the restrictions on the applications it runs.

Storage, Networking and Hardware Access: Where the Engines Differ on Real Sites

This is where small engine differences turn into support cases once they repeat across hundreds of machines.

Storage

Docker keeps images and data under /var/lib/docker, Podman under /var/lib/containers/storage when run as root. Rootless setups move everything into the user’s home directory, which on small machines is often the smallest partition.

On an Avassa site, images sit in the Edge Enforcer’s local registry and are copied into the engine’s cache when an application starts. Our sizing guide therefore plans for each image twice on a host, plus about 800 MB for Edge Enforcer upgrades and about 2.5 GB for system data. We recommend keeping the operating system on its own partition and mounting the engine’s storage from a separate disk, as the storage configuration guide describes.

Networking

Docker manages bridge networks and firewall rules through its daemon. Podman uses Netavark when run as root. Both fall back to slower user-mode networking when rootless.

On an Avassa site, those engine features step aside. The Edge Enforcer replaces existing iptables rules with its own nftables rules, encrypts traffic between hosts, keeps outbound access closed by default, and routes incoming traffic through ingress addresses the site provider configures.

Hardware access

Think of a camera on a production line, a USB device on a machine, or a GPU running AI in a store. Rootless engines make these harder: devices are owned by root, device nodes cannot be created inside a rootless container, and GPUs need extra setup.

In the Avassa Edge Platform, the site provider defines device labels, such as a camera matching a hardware pattern, and GPU labels, such as a GPU from a given vendor. An application asks for the label it needs, and the Edge Enforcer places it on a host that has a match. Because discovery follows the hardware, a GPU moved to another machine takes its label with it. Read more in How to place applications based on edge hardware devices.

See how the Avassa Edge Platform deploys, updates and monitors applications across stores and factories, on whichever engine your hosts run.

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Podman vs Docker Performance on Small Edge Hardware

On a site machine, performance means three things: memory use, start time, and what happens after a restart or power cut.

Docker’s daemon uses memory all the time. Podman has no daemon but runs a small monitor per container. On both, the applications almost always use far more memory and CPU than the engine. Published comparisons vary with versions and workloads, so the only answer you can trust is a test on your own hardware.

For planning, here are numbers we can stand behind, from our sizing guide:

• Minimum host: 2 GB RAM, 1 vCPU and 2 GB of disk, on Linux kernel 5.4 or later with systemd.
• Edge Enforcer memory: between 100 and 500 MB, and around 120 MB with no applications running.
• Per application: in our test with 100 application instances, the Edge Enforcer’s steady-state memory grew from 112 MB to 126 MB, around 0.14 MB per application.

After a restart, Docker brings containers back through restart policies, Podman through systemd. On an Avassa site, the Edge Enforcer restarts and reschedules applications itself, with or without a connection to the cloud.

How to Choose Across Hundreds of Sites: Decide Once, Manage Centrally

What a leader wants is simple to say: the same result at every site, regardless of who installed the machine or when.

Start From the Host Operating System

The operating system usually decides the engine for you. Red Hat Enterprise Linux ships Podman as its container engine. On Debian and Ubuntu both are available, and Docker is often the habit. Check the version floor too: Avassa’s Podman support starts at Podman 4.0, so Debian 12, Ubuntu 22.04, CentOS 9 or RHEL 9.

Red Hat-based sites often lean toward Podman. In Simplified container application management at the far edge with Red Hat and Avassa, we describe how Red Hat Device Edge, built on RHEL with Podman, gives small edge machines a stable, centrally managed base, and how Avassa adds application management on top. The Avassa Edge Enforcer is also certified on Red Hat Enterprise Linux.

A short note on SELinux: it is the mandatory access control system built into Red Hat systems, and it limits what each process, including a container, may touch, even as root. It is on by default, and security teams expect it to stay on.

Avoid Lock-In and Per-Site Decisions

A different setup at each site is a bigger risk than the choice of engine. Every exception needs its own documentation, troubleshooting and someone who remembers why. A practical approach:

1. Pick one default per operating system, for example Podman on RHEL and Docker on Debian.
2. Write it down as part of how new sites are installed.
3. Manage every site from one platform, so applications are deployed, updated and monitored the same way on either engine.

A platform that works with both engines keeps the choice reversible. Your images stay OCI images, deployed through the same Control Tower whichever engine the host runs, and you can mix Docker and Podman in the same system. A region that moves to Red Hat does not force a change elsewhere. See how this works in retail and industrial environments, and read how H&M Group pioneers edge computing in retail with Avassa.

Do you need Kubernetes as well? No. Avassa runs applications without requiring Kubernetes at every edge site. The Edge Enforcer includes scheduling, networking, secrets and storage, so there is no cluster to maintain per site, and it coexists with Kubernetes where you already run it. Read more in Avassa and Kubernetes at the edge.

Situation across your sites	Lean toward	Why
Machines already on RHEL 9 with a non-root security rule	Podman	It ships with the operating system, has no root daemon, and fits the Red Hat tooling the team already uses
Older machines on earlier operating systems	Docker	Avassa’s Podman support needs Podman 4.0 or later, which older distributions do not ship
Applications that need cameras, devices or GPUs	Either engine, run as root, with access granted per device	Rootless setups make host devices hard to reach. Grant only the devices each application needs instead of full privileges
Teams already run Docker everywhere	Docker	It keeps existing skills and runbooks. Add isolation with user namespaces instead of switching engines
A mix of operating systems across regions	One default per operating system	Follow each operating system’s natural engine and manage both from one platform

Install the Avassa Edge Enforcer on a Docker or Podman machine and test rollout, rollback and offline behavior with an application you run.

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Conclusion

Podman and Docker have more in common than the debate suggests. Both run the same OCI images, and both are mature. The real difference is the daemon: Docker has one, Podman does not. Rootless containers reduce the damage of a container breakout, but they make low ports, devices and GPUs harder to use, and they do not patch a vulnerable application. At hundreds of sites, consistency matters more than the engine.

The one piece of advice to remember: decide per operating system, not per site, and manage every site from one platform.

Book a technical architecture session with the Avassa team to map your sites, operating systems and security requirements.

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About the authors

This article was written by the Avassa team. Avassa builds the Avassa Edge Platform, used to deploy, update, monitor and secure containerized applications and AI models across hundreds or thousands of distributed sites, from stores and factories to machines and vehicles, without requiring Kubernetes at every edge site.