Minimal Distroless Images: Benefits Beyond Security

All applications have historically come with their own costs to build, test, and operate; and applications built based on container images are no different. While the main benefit of distroless minimal images is that they reduce the vulnerability and attack surface footprint for applications running in containers, a common side benefit is a reduction of the image size. 

In this blog, we’ll focus on the material and scale benefits of adopting minimal distroless container images outside of security advantages.

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Infrastructure Costs

There are many infrastructure costs that need to be considered throughout the software development lifecycle for applications running in containers.  

Direct correlations between smaller image size and reduced infrastructure costs include:  

1. Local Disk Storage on Machines: Smaller images consume less disk space across laptops, build agents, and servers, reducing hardware requirements and storage expansion costs.
2. Registry Storage Costs: Container registries typically charge based on stored data volume. Smaller images reduce total stored gigabytes, especially when multiplied across versions and environments.
3. Initial Memory Requirements on Image Start: Leaner images often require fewer resources to load into memory, improving density on shared infrastructure and reducing compute overhead.
4. Data Transfer Fees: Every image pull transfers data across networks. Smaller images reduce bandwidth consumption and cloud egress costs, particularly in high-scale or multi-region deployments.

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Even small reductions in image size can compound significantly across hundreds or thousands of builds, pulls, and deployments per day. With minimal image providers like Minimus, where images are often dramatically smaller than public equivalents, this compounding effect is amplified, multiplying savings across storage, transfer, compute, and pipeline execution at scale.

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Simplified Management

Container images are routinely pulled across developer laptops, CI runners, staging, and production clusters, often dozens or hundreds of times per day for troubleshooting, application sharing, and other day-to-day operational uses.

Smaller images pull and load faster, because less data moves across the network and is written to disk. In CI environments that start from clean runners, this is measurable in seconds per build. Across parallel pipelines and repeated executions, those seconds translate into shorter pipeline durations and lower infrastructure utilization.

For example, a 300MB reduction pulled 100 times per day equals 30GB less data transferred daily, or 900GB per month for a single image. If five services each experience the same 900GB monthly reduction, that equates to 4.5TB less data transferred per month. At typical cloud egress rates (e.g., $0.09 per GB), that alone could represent roughly $400 in monthly bandwidth savings, excluding additional compute and time efficiencies.

These savings also translate directly into improved engineering productivity and capacity. Faster pulls and shorter pipelines reduce engineer wait time and deployment friction, converting seconds saved per build into reclaimed engineering hours each week across multiple teams.

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Automation Amplifies the Impact

As container images are built and shipped, images are also generally subject to constant load through automation. This includes:

1. Continuous builds and testing in non-production environments
2. Scanning at build, test, and runtime by security tooling

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Base images are often reused as the foundation for many other images, increasing the impact of the above at an exponential level. In practical terms, this means image size affects::

• The duration of automated build and scan stages: Smaller images equal faster image pulls, load times, and scan times.
• The time required to promote artifacts across environments: Smaller images move more quickly between registries, regions, and clusters, reducing promotion latency.
• The speed at which new containers can be deployed or scaled: New images are continuously deployed into operational environments, and smaller images load faster, allowing applications to start faster.

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Seeing the Actual Material Differences of Minimal Images

Below is a size comparison of Minimus images versus their public equivalents:

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Across the ten images shown, the median reduction is approximately 141%, with an average reduction of 371% (skewed higher by extreme reductions such as Python). While not every image is drastically smaller, the majority demonstrate substantial size reduction that directly impacts storage, transfer, and pull performance at scale.

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Example of Size Reduction of a Minimus Based Image vs Its Public Equivalent

In many cases, the size difference is not incremental, it is exponential. Images such as Python, Node, and nginx show multi-hundred percent reductions in size:

nginx:

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python:

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Operational Leverage Beyond Security

Moving to distroless minimal images is not just about security. It is about operational leverage. By reducing image size, organizations decrease infrastructure consumption, accelerate CI/CD workflows, improve deployment speed, and compound efficiency gains across environments.

Minimus images extend the value beyond size alone. Additional benefits over many public variants include:

• Security-first hardening: Minimus images have 97% fewer CVEs on average, with hardened default configurations, curated package selection aligned to best practices, and built-in SBOMs for transparent component visibility and auditability.
• Compliance made easy: Support for regulatory and industry frameworks through hardened baselines, audit-ready artifacts, and alignment with standards such as FIPS, CIS, and other enterprise compliance requirements.
• Intelligence-driven prioritization: Integrated threat intelligence and action providers to automate remediation and focus on real-world risk.
• Consistency and control: Greater version consistency and visibility, lower operational drift, and proactive hardening that reduces downstream remediation effort.
• Deployment support: Custom image creator for tailored, compliant runtime environments, plus hardened Helm charts to securely extend images into Kubernetes deployments.

If you’d like to see how these efficiencies translate within your own environment, request a demo to explore Minimus in action.