---
title: "Custom EULA"
description: "It is simple to add a custom End User Licence Agreement for your package downloads in a Cloudsmith repository."
canonical_url: "https://cloudsmith.com/blog/custom-eula"
last_updated: "2020-09-29T17:47:00.000Z"
---
# Custom EULA

[Dependency confusion](https://cloudsmith.com/blog/dependency-confusion-attacks) is a software supply chain weakness that arises from how package managers resolve dependencies across multiple sources.

It does not rely on complex exploits. It relies on normal dependency resolution.

If a build resolves from both private and public registries, and a public package shares the same name as an internal dependency, the public package may be selected. That is sufficient to introduce unintended code into a build.

Modern dependency trees often include extensive transitive dependencies, increasing the number of automatic resolution decisions made during builds.

The issue was [widely documented in 2021 ](https://medium.com/@alex.birsan/dependency-confusion-4a5d60fec610)when researchers demonstrated it against more than 35 large organizations by publishing public packages that matched internal names. Since then, dependency confusion has remained a known and preventable risk in modern build systems.

## Where risk appears in practice

Modern builds commonly blend:

- Internal packages
- Public open source dependencies
- Upstream proxies
- Cached artifacts

If resolution rules are not explicit, package managers make decisions on your behalf.

Different ecosystems provide different structural protections and different pitfalls.

### Ecosystem specific considerations

#### Python

PyPI operates on a flat global namespace. There are no built-in organizational scopes and no domain bound identifiers. Package names are globally unique and first come, first served.

This means internal package names, for example acme utils or internal ml core, are structurally indistinguishable from public ones unless additional controls are applied.

Python projects frequently configure multiple indexes. It is common to see:

- Internal private mirrors
- Vendor-hosted repositories such as PyTorch wheel indexes for CUDA builds
- Regional mirrors
- Index url combined with extra index url

Python tooling such as pip, uv, and Poetry evaluates candidate versions across configured sources. If the same package name exists in more than one index, the resolver may select the highest compatible version, regardless of origin.

Real-world incidents demonstrate this behavior. [In 2022, a malicious package mimicking a PyTorch dependency](https://www.reversinglabs.com/blog/pytorch-supply-chain-attack-dependency-confusion-burns-devops) was published to PyPI and installed via pip resolution during nightly builds, leading to data exfiltration before detection.

Without explicit trust boundaries or source mapping, this multi index behavior introduces ambiguity. If an internal package name is exposed and a higher version appears on a public index included in resolution, the public package may be selected.

Python’s flat namespace model, combined with common multi index configurations, makes careful source control particularly important.

#### npm

npm supports scoped packages using the @org/package format. Once registered, a scope is controlled by that organization.

However, unregistered scopes remain claimable. If an organization uses scoped internal packages but has not reserved the scope publicly, an attacker could register it and publish similarly named packages, for example @org/app. A configuration mistake in development or CI could then result in the malicious package being resolved and executed, including via lifecycle hooks such as preinstall.

Unscoped internal package names carry exposure similar to Python.

#### Maven

Maven Central uses domain-based groupId verification, providing stronger ownership guarantees when correctly configured.

However, inconsistent repository usage or additional repositories can reintroduce ambiguity in resolution order if trust boundaries are not clearly defined.

#### NuGet

While NuGet supports ID prefix reservation to prevent public name squatting, resolution ambiguity can still arise if multiple feeds are configured.

**Key safeguards include:**

- ID prefix reservationReserve your organization’s package ID prefix on nuget.org to prevent public impersonation.
- Package Source Mapping Use NuGet 6+ source mapping to bind specific package IDs or prefixes to a single trusted feed.
- Strict nuget.config configurationClear default feeds and explicitly define approved sources to prevent unintended restores.
- Signature enforcementNuGet repository signing using X.509 certificates. When signature verification is enforced in the NuGet or .NET CLI, consumers can verify that a package originated from the expected repository and has not been tampered with.

#### Docker

Docker Hub differs from language ecosystems because image references are typically registry qualified, making classic multi-source confusion less common.

However, **related risks remain:**

- Implicit Docker Hub fallback when no registry is specified
- Unregistered namespace squatting
- Mutable tags such as latest

These are mitigated through fully qualified image references, namespace reservation, digest pinning using SHA256, and image signing.

## A layered mitigation approach

Preventing dependency confusion does not require dramatic changes to developer workflows. It requires clear trust boundaries in how dependencies are resolved.

In practice, this is implemented through an internal artifact repository that controls how dependencies are proxied, cached, and resolved.

Key elements include:

- Centralizing dependency resolution
- Defining explicit upstream trust
- Controlling namespace ownership
- Using lockfiles and reproducible builds
- Enforcing artifact signing and verification

### 1. Central artifact repository

Route all builds through a central artifact repository that acts as the single source of truth for dependencies. Public packages should be proxied and cached internally rather than resolved directly from the internet.

### 2. Define upstream trust

Explicitly distinguish between trusted and untrusted sources.

Cloudsmith provides upstream trust controls that allow repositories to designate upstream sources accordingly and control how packages are blended during resolution. If a package exists in a trusted source, it cannot be overridden by an untrusted one.

Cloudsmith’s Upstream Trust currently supports:

- Python
- Maven
- npm

Support for additional ecosystems is expanding. In addition to source trust controls, policy enforcement provides another layer of protection. [Cloudsmith’s Enterprise Policy Manager](https://cloudsmith.com/product/enterprise-policy-manager) allows organizations to define rules around what packages are permitted, including conditions based on vulnerability data, malware data, version constraints, or upstream origin. This enables teams to combine resolution boundaries with policy-based controls.

### 3. Reserve namespaces

Where supported:

- Use npm scopes
- Reserve NuGet ID prefixes
- Use domain based Maven group IDs

Namespace ownership significantly reduces collision risk.

### 4. Use lockfiles

Lockfiles improve determinism, traceability, and visibility into unexpected changes. They do not eliminate dependency confusion, but they reduce instability and make tampering easier to detect.

### 5. Require signing

Signing adds cryptographic integrity to artifacts.

Cloudsmith signs hosted packages by default. Cloudsmith supports both native and non-native signing across package formats, including native signing for [Docker, NuGet, and Swift](https://cloudsmith.com/blog/native-signing-support-in-cloudsmith-extended-to-docker-nuget-and-swift). Signature validation workflows in supported ecosystems provide an additional verification layer if substitution is attempted.

Signing strengthens integrity guarantees but does not replace resolution controls.

## Conclusion

Dependency confusion is not a sophisticated exploit. It is a consequence of ambiguous resolution behavior across multiple sources.

Preventing it requires:

- A central artifact repository serving as the single source of truth for dependencies
- Explicit upstream trust boundaries
- Namespace ownership
- Lockfiles and reproducible builds
- Artifact signing and verification

Clear boundaries remove ambiguity. Removing ambiguity removes the attack path.

  
Stop leaving your build integrity to chance. [**Book a demo**](https://cloudsmith.com/book-a-demo) today to see how Cloudsmith's enterprise-grade repository controls can remove ambiguity and harden your delivery process.

**TL;DR:** LLMOps is the operational framework for managing the lifecycle of Large Language Models (LLMs). Unlike DevOps, which focuses on deterministic code, **LLMOps artifact management** must handle probabilistic assets like prompts, embeddings, and fine-tuned models. This shift requires a move from standard CI/CD to specialized **LLM pipeline management** to ensure system traceability and trust.

## What is LLMOps?

**LLMOps (Large Language Model Operations)** is a specialized set of practices for automating and managing the end-to-end lifecycle of LLM-powered applications. It extends MLOps principles to address the unique requirements of generative AI, specifically focusing on **LLM lifecycle management**, prompt engineering, and vector-based data flows.

While DevOps focuses on application code and MLOps on traditional machine learning models, **LLMOps** handles the massive complexity of:

- **Foundation and fine-tuned models:** Managing base models and their task-specific variants.
- **Prompt artifacts:** Versioning the system instructions that dictate model behavior.
- **Embeddings and vector indexes:** Curating the "knowledge" used in Retrieval-Augmented Generation (RAG) systems.
- **Dynamic inference behavior:** Monitoring outputs that change even when input code remains the same.

In essence, LLMOps is about operationalizing AI rather than just software binaries.

## LLMOps vs DevOps: Why the difference matters

The debate of **LLMOps vs DevOps** isn't about choosing one over the other; it’s about understanding where **DevOps tooling limitations for AI** begin. DevOps is built for deterministic systems; if you deploy the same code, you get the same result. LLM pipelines are probabilistic, meaning the same "code" (prompt) can yield different outputs.

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The core takeaway is that the shift from **DevOps artifact management** to **AI artifact management** involves handling much larger, more volatile assets that directly influence the "logic" of the application.

## Why artifact management matters in LLMOps

In a traditional app, an artifact is just a compiled file. In AI, **artifacts are the system.** Without robust **artifact management for LLMs**, teams face a "black box" problem where they cannot explain why a model suddenly began hallucinating or failing.

**Effective AI artifact management solves for:**

- **Reproducibility:** Re-creating a specific model state using exact dataset snapshots.
- **Auditability:** Tracking the lineage of a prompt to meet emerging AI regulations.
- **Rollback safety:** Quickly reverting to a previous "known good" version of a prompt or embedding index.
- **Cost efficiency:** Preventing redundant training by reusing existing **model artifacts**.

## What artifacts do LLM pipelines produce?

Modern **LLM pipeline management** generates a diverse array of non-code assets across the **AI model lifecycle**. Understanding these is key to moving beyond simple script-based deployments.

#### Common LLM artifacts:

- **Model artifacts:** These include base foundation models (like Llama 3 or GPT-4), fine-tuned adapters (LoRA/QLoRA), and quantized versions for edge deployment.
- **Dataset versioning:** Snapshots of training data, evaluation sets (Golden Sets), and synthetic data used for testing.
- **Prompt artifacts:** Versioned system prompts, few-shot examples, and complex prompt chains that function as the "new source code."
- **Embeddings management:** Vector database snapshots and the specific embedding models (e.g., Ada, BERT) used to generate them.
- **Inference artifacts:** Production logs, "LLM-as-a-judge" evaluation scores, and human-in-the-loop feedback.

## MLOps vs LLMOps: Where traditional approaches fall short

Many teams assume their existing MLOps stacks can handle LLMs. However, **MLOps vs LLMOps** highlights a critical gap: **prompt versioning.** Traditional MLOps tools aren't built to treat a 50-word text string (a prompt) as a deployment-critical artifact. Furthermore, the **inference artifacts** in LLMOps are much richer, requiring semantic monitoring rather than just simple accuracy metrics.

#### Feature store vs Artifact repository

A common point of confusion is the choice between a **feature store vs artifact repository**:

- **Feature stores** are for structured data used in tabular ML.
- **Artifact repositories** (like weights and biases or MLflow) are the "System of Record" for the unstructured models and prompts that define an LLM app.

## Challenges and best practices for LLMOps

Managing these assets comes with significant **challenges of artifact management in LLMOps**, including massive file sizes and the high velocity of prompt changes.

#### LLMOps best practices:

- **Treat prompts as code:** Store prompts in version-controlled repositories, not hardcoded in your app.
- **Centralize your artifact registry:** Use a single source of truth for all models and embeddings to avoid "shadow AI" across teams.
- **Automate lineage tracking:** Ensure every inference result is traceable back to the specific model version, prompt, and dataset used.
- **Implement evaluation gates:** In your **LLM workflows**, never promote an artifact to production without passing an automated evaluation suite.

## FAQ: Frequently asked questions on LLMOps

- ### How is LLMOps different from DevOps?

LLMOps manages probabilistic AI assets like models and prompts, while DevOps manages deterministic code and binaries. LLMOps requires specialized pipelines for evaluation and fine-tuning that don't exist in traditional CI/CD.

- ### Why does artifact management matter in LLMOps?

It ensures that every AI output is traceable and reproducible. Without it, you cannot debug hallucinations, comply with AI audits, or reliably roll back failed updates.

- ### What are the most important LLMOps workflows?

Key workflows include data ingestion for RAG, automated prompt evaluation, model fine-tuning, and continuous monitoring of inference quality.

## Final thoughts

The future of software is no longer just about code; it’s about **artifacts, intelligence, and trust.** As LLMs move from experiments to core infrastructure, the transition from DevOps to LLMOps is inevitable.

Teams that master **artifact management for LLMs** today will be the ones building the most reliable, scalable, and auditable AI systems of tomorrow.

To manage LLMOps at enterprise scale, use Cloudsmith as your single source of truth. Discover how by [booking your free demo](https://cloudsmith.com/book-a-demo) today.



**Cloud migration** is rarely just an infrastructure move. For most DevOps and platform teams in 2026, it’s a once-in-a-decade opportunity to rethink tooling, eliminate legacy bottlenecks, and modernize the [**software supply chain**](https://cloudsmith.com/product/software-supply-chain-security) end-to-end. One of the most overlooked, but highest-impact, areas to revisit during this transition is **artifact management**.

As organizations shift workloads and security controls into the cloud, the limitations of [**legacy artifact repositories**](https://cloudsmith.com/blog/the-true-cost-of-legacy-artifact-management) quickly become visible. What once worked in on-premise environments often creates friction, risk, and massive operational overhead in a cloud-native world.

This is why **cloud migration** isn’t just a "lift-and-shift" event. It’s the ideal moment to reassess how you store, secure, and distribute artifacts across modern **cloud migration DevOps** workflows.

## Why legacy artifact repositories struggle during cloud migration

Traditional, self-hosted repositories were designed for static infrastructure and perimeter-based security. Cloud environments invert those assumptions.

During migration, teams commonly encounter:

- **Scaling constraints:** Legacy tools often require manual server provisioning or expensive over-capacity planning.
- **Operational toil:** Managing patches, database tuning, and storage maintenance for your own repository steals focus from your core product.
- **Performance bottlenecks:** When global teams depend on a single on-premise instance, latency sabotages developer velocity.

Keeping a legacy repository while modernizing everything else often results in a "partially modern" stack with legacy risk still embedded in your delivery pipeline.

## Cloud migration exposes hidden software supply chain risk

Modern cloud adoption increases velocity, but speed without control amplifies risk across the **software supply chain**. Common exposure points include:

- **Unverified third-party dependencies:** Cloud-scale builds pull in thousands of external packages that need immediate scanning.
- **Inconsistent provenance:** Difficulty tracking exactly "who built what and where" across fragmented environments.
- **Limited policy enforcement:** Brittle legacy controls that can't handle the dynamic nature of cloud-native deployments.

Re-evaluating artifact management during migration allows teams to embed **zero-trust** governance exactly when redesigning their pipelines.

## The modernization opportunity: Fully managed artifact repositories

Cloud migration creates the perfect window to replace self-hosted infrastructure with a fully managed** artifact repository** built for elasticity and global distribution.

Modern platforms like **Cloudsmith** deliver:

- **Infinite scalability:** No more storage planning or maintenance; the platform automatically scales with your builds.
- **Edge performance:** A built-in Package Delivery Network (PDN) delivers artifacts worldwide to reduce latency.
- **Integrated security:** Features like automated vulnerability scanning and signature verification are baked in, not bolted on.

Instead of recreating legacy architecture in the cloud, organizations can move directly to a fully managed model aligned with cloud‑native principles. This shift transforms artifact management from a maintenance task into a strategic layer of the delivery platform.

## When to move: Aligning your migration strategy

Teams often postpone modernization because migration feels complex. However, delaying the decision typically leads to "double migration" work, migrating the legacy tool today and replacing it tomorrow.

**Aligning modernization with your cloud move avoids:**

1. **Re-architecting pipelines twice:** Design your CI/CD for your final destination, not a temporary stop.
2. **Moving massive stores twice:** Cloud-native migration scripts (like the Cloudsmith CLI) handle the transfer of binaries and metadata once.
3. **Carrying legacy debt:** Ensure your new cloud environment launches with a clean, high-performance foundation from day one.

## Signs your artifact management is holding you back

Before moving to the cloud, audit your current state. If these "silent killers" sound familiar, a lift-and-shift solution will only migrate your technical debt:

- **Manual maintenance toil:** Your team spends hours every month on repository upgrades, patching, and storage "garbage collection".
- **The "slow download" tax:** Global developers or remote build agents face high latency because your on-premise repository lacks a global distribution network.
- **Compliance blind spots:** You struggle to provide a complete "bill of materials" (SBOM) or audit trail for a security incident.
- **Brittle CI/CD scripts:** Your pipelines rely on custom, "home-grown" scripts to move packages between environments because your tool doesn't support native promotion workflows.

## The strategic ROI: What actually changes?

Modernizing your **artifact repository** during a cloud move isn't just a technical swap; it delivers measurable business impact:

- **Developer velocity:** By eliminating manual bottlenecks and enabling faster access to dependencies, teams often see **43% faster release cycles**.
- **Zero-trust security:** Centralized policy enforcement and automated vulnerability scanning move security from a "final check" to an integrated part of the build.
- **Operational efficiency:** Moving to a fully managed** artifact repository** removes the "toil" of server management, allowing your DevOps engineers to focus on product innovation rather than infra-maintenance.
- **Total cost of ownership (TCO):** You trade hidden infrastructure costs and administrative salaries for a predictable, transparent, fully managed model.

## Evaluating alternatives: Beyond JFrog and Nexus

Many organizations begin cloud migration using legacy tools like **JFrog Artifactory** or **Sonatype Nexus**, only to find they were built for a different era of infrastructure. Modern cloud-native platforms eliminate the need to manage repository infrastructure while delivering stronger governance and global performance. As a result, more teams are looking for [**JFrog alternatives**](https://cloudsmith.com/switch/jfrog-artifactory) and [**Nexus alternatives**](https://cloudsmith.com/switch/sonatype-nexus) that offer a fully managed, "Zero-Ops" experience.

For teams ready to [**migrate, Cloudsmith**](https://docs.cloudsmith.com/migrating-to-cloudsmith?_gl=1*1tuvjc8*_gcl_au*MjA0MTMxOTg3MC4xNzYzMzg3ODg3*_ga*NDcwNDc1ODMuMTcyMzAyNjg2MQ..*_ga_6KCWZ6W3Y9*czE3NzAyOTA3NDEkbzE1MiRnMSR0MTc3MDI5MTAwMiRqNDEkbDAkaDA.*_ga_H5NBQJ0NGM*czE3NzAyOTA3NDEkbzMxMiRnMSR0MTc3MDI5MTAwMiRqNDAkbDAkaDkzNTk0MDIyMw..) streamlines the process to minimize disruption and accelerate value realization.

## Why global leaders migrate artifact management to Cloudsmith

As teams evaluate **alternatives to JFrog and Nexus**, they increasingly move to **Cloudsmith**, designed specifically for modern DevOps and secure software delivery for the security landscape of 2026 and beyond.

**The Cloudsmith advantage:**

- **Zero-ops architecture:** A true cloud-native, fully managed experience with no databases to manage and no servers to patch.
- **Built-in package delivery network (PDN):** Hundreds of nodes deliver artifacts from the edge, ensuring your global build agents always have high-speed access.
- **Universal format support:** One single source of truth for Docker, npm, Maven, Python, and 30+ other formats.
- **Supply chain resilience:** Automated provenance tracking and signature verification help keep you compliant with key security standards and ensure that what you ship is exactly what you built.

## Conclusion: Don’t just move to the cloud – modernize what matters

Cloud migration is a rare opportunity to fix the "foundation" of your house before you move in the furniture. By re-evaluating your **artifact management** now, you ensure your cloud-native future is fast, secure, and, most importantly, manageable.

The most successful cloud migrations don’t just replicate the past. They modernize the platform that powers everything built next.

**Planning a cloud migration?** [Book a demo](https://cloudsmith.com/book-a-migration-consultation) with our experts to simplify the process.

## Frequently asked questions

- ### What is artifact management in DevOps?

It is the practice of storing, securing, and distributing build outputs, such as Docker images or Maven packages, throughout the development lifecycle. It ensures your builds are reproducible and secure.

- ### Why reconsider artifact repositories during cloud migration?

Updating your repository during a move avoids duplicate work and ensures that a legacy on-premises artifact manager doesn’t constrain your new cloud infrastructure.

- ### What are the risks of keeping a self-hosted repository in the cloud?

[Self-hosting](https://cloudsmith.com/blog/cloud-native-vs-on-premise-artifact-management-a-complete-overview) in the cloud still requires manual patching and scaling. This increases costs and creates "visibility gaps" that can lead to security breaches.

- ### How does a fully managed artifact repository improve security?

Fully managed platforms provide centralized governance, immutable storage, and automated compliance auditing, all of which are critical to a secure **software supply chain**.



For years, the bottleneck in software was “how fast can we write code?” Today, Generative AI shifts that bottleneck to **“how fast can we secure it”**.

For years, the bottleneck in software was “how fast can we write code?” Today, Generative AI shifts that bottleneck to “[how fast can we secure it](https://cloudsmith.medium.com/is-ai-quietly-making-your-software-supply-chain-less-secure-e1364de33f9a)?”

As organizations move from experimentation to production-grade AI, they are discovering that traditional DevOps tooling wasn’t built for a non-deterministic world. For example, static software composition analysis (SCA) scanners that assume deterministic dependency graphs or CI policy gates that validate known build artifacts. When a model generates code rather than a human, the software supply chain changes overnight.

Our guide, **Securing non-deterministic systems: A practical guide for AI artifacts and LLMOps**, explores three emerging security frontiers that every organization adopting AI must address:

## 1. AI-generated code introduces supply-chain hallucinations

LLMs generate dependencies probabilistically, not deterministically. This creates the emerging **slopsquatting** attack vector, where attackers register hallucinated package names suggested by AI tools and weaponize them with malicious payloads.Without validation and artifact governance, a single copied command can silently compromise an enterprise environment.

## 2. AI models behave like executable software, not passive data

Modern model formats can execute arbitrary code during deserialization, most notably through Python pickle-based loading.This **logic-weight entanglement** means downloading an unverified model from public registries such as Hugging Face or Ollama can result in full system compromise.Secure AI development requires scanning, signing, and favoring restricted formats like **safetensors**, alongside enforcing trusted provenance for every model artifact.

## 3. AI productivity and orchestration layers expand the attack surface

Frameworks that connect models to enterprise data and automate workflows introduce a new class of high-impact vulnerabilities.Recent RCE exploits in orchestration tools demonstrate that **LLMOps infrastructure itself is now part of the software supply chain**, and must be sandboxed, authenticated, and governed like any production system.

### Ready to harden your AI supply chain?

Our full guide provides a strategic roadmap for navigating the shift from DevOps to LLMOps, deconstructing threats in frameworks like Langflow, and building a “sandbox-by-default” development lifecycle.

**[Download the full guide: [Securing non-deterministic systems](https://cloudsmith.com/campaigns/securing-non-deterministic-systems-a-practical-guide-for-ai-artifacts-and-llmops)]**

**Catch up on the series:**

- [_Why Repository Structure Matters?_](https://cloudsmith.com/blog/why-repository-structure-matters)
- [_The Hybrid Repository Structure: Balancing Control and Flexibility_](https://cloudsmith.com/blog/the-hybrid-repository-structure-balancing-control-and-flexibility)

And now, let’s dive into part three: How **access control and permissions** keep your multi-format repositories secure, consistent, and developer-friendly.

In the first two blogs of this series, we explored why repository structure matters and how Cloudsmith’s Hybrid Repository Structure balances control with flexibility. While we touched on policies and permissions, we didn’t dive into the _real_ mechanics of how access control ensures artifact security, traceability, and consistency, especially in **multi-format repositories**, where different packages, languages, and tooling coexist in a single place.

While multi-format repositories allow for more flexibility in how your repositories are set up, they can introduce a new way of thinking about how and when different artifacts can be accessed and by whom. This blog breaks down how Cloudsmith provides fine-grained, flexible, and secure controls for teams of any size.

## User roles in Cloudsmith

Cloudsmith provides the following user roles:

- Owner
- Manager
- Member
- Collaborator

These roles help limit access based on organizational need and provide the foundation for more granular permissions.

## Privileges in Cloudsmith

- Administrator
- Read
- Write

You can explore the full breakdown of Cloudsmith roles, permissions, and privileges in our documentation.

You can read more about user roles, permissions, and privileges in Cloudsmith [here](https://help.cloudsmith.io/docs/access-controls).

## Global privileges in Cloudsmith

Every Cloudsmith customer is given the opportunity to set default global privileges. These global default privileges are set for the “Member” user role in Cloudsmith, which is often suited best for individual developers. Within a customer’s global workspace privileges, organizations can choose to grant members the ability to create new teams, invite new users, and even create new repositories. Organization owners can also grant “blanket” repository privileges to all users within Cloudsmith. 

While we offer the flexibility for organizations to shift responsibility and access to the developer, we often see our enterprise customers lean away from blanket permissions and access toward more fine-grained permissions. As an example, we have a semiconductor manufacturing customer that has disabled default workspace global privileges so that only Organisation owners are the only users who can invite new users, create new teams, invite 3rd-party collaborators, and create new repositories. 

In addition, this customer has access control, and privileges are scoped down to specific teams. Default global repository privileges are disabled so that they can choose exactly which team(s) should have access to repository(s). Even Cloudsmith service accounts are grouped together within a team for ease of tracking permissions and access when it comes to build and deployment times. 

## Repository privileges in Cloudsmith

If we zoom in once and look at the repository level in Cloudsmith, we can assign a default privilege for organization members for accessing packages within the repository, and we can assign specific privileges for specific teams, users, or service accounts.

This is the stage where you’ll have to consider what packages the repository is storing and if you want developers and service accounts to have default admin, read, or write permissions to the repository. Continuing to use my customer example, they have chosen to set default read permissions for all repositories; however, specific service accounts have write and [admin permissions](https://help.cloudsmith.io/docs/manage-a-repository) to different repositories. You may be okay with your developers downloading artifacts to their local machine for testing or even service accounts requesting stored artifacts tied to staging and production environments.

On the other hand, there are customers that may not want their developers having the ability to write to every repository and would most likely want specific service accounts tied to their CI/CD pipelines to only have write permissions. While this is generally best practice, there are certainly exceptions to this rule, as we also have platform teams that choose to grant specific developer teams write access to specific artifact repositories.

## Fine-grained repository controls

On top of the permission and access control settings we’ve discussed, Cloudsmith goes even further to ensure that, through various additional settings, platform teams can decide exactly what their developers need and don’t need to be reconfigured within a repository.

Platform teams are able to grant or deny developer permissions, such as:

- Copying Packages From One Repository to Another
- Moving Packages From One Repository to Another
- Deleting Packages
- Scanning Packages
- Replacing Packages
- Managing, Using, Or Viewing Entitlement Tokens

If you thought that wasn’t enough, Cloudsmith takes it a step further by scoping down permissions to the individual developer’s generated packages. So while platform teams can restrict tampering of artifacts generated by other developers or systems, they can also decide if they would like to allow developers the ability to scan, move, copy, delete, or resync their own packages.

Most of the enterprise customers I work with allow developers to do as they please with their own packages to avoid a developer mutiny! In either case, these user actions are catalogued in our [Audit Logs](https://docs.cloudsmith.com/logs-and-observability/audit-logs) for enhanced observability across your Cloudsmith environment.

## Entitlement tokens

For instances where our customers want to be very particular about what, how, and when users can access specific packages, Cloudsmith offers [Entitlement Tokens](https://help.cloudsmith.io/docs/entitlements). These scoped tokens are read-access only, so there is never a risk of a user performing a write action against the repository they have limited access to.

Customers are able to restrict access by creating a precise search query to narrow down specific packages within a repository, should they choose not to provide visibility into all the packages within the repository. On top of visibility restrictions, customers can also add token usage restrictions to avoid prolonged access and usage of the token. Parameters include:

- Token Validity & Expiry Dates
- Maximum Downloads
- Maximum Clients/IPs
- Maximum Download Bandwidth

Typically, we see our customers use entitlements for 3rd party software distribution or even for systems that don’t require logins to Cloudsmith.

## Geo/IP Restrictions

For our security-conscious customers, Cloudsmith also offers the ability to configure [geo-based restrictions](https://help.cloudsmith.io/docs/geoip-restriction) based on country, with an easy-to-use preconfigured list of countries to choose from. Choose to deny or allow access from specific countries. Although keep in mind that theoretically, no unauthenticated user should have access to your Cloudsmith workspace in general. This restriction applies more towards open-source repositories that you may be hosting in Cloudsmith, but it’s always a good idea to practice defence-in-depth!

If geo-based restrictions are too broad, you can scope down to IP-based restrictions to either allow or deny client access based on IP address. This added protection ensures that requests coming from clients with an unapproved IP address do not have access to your repositories. 

## We’re here to help

With all of these configuration options, it can be tricky to decide how you want to best enable your developers while balancing security and flexibility. Not to worry—the Cloudsmith Customer Success team is here to help you in your decisions throughout the onboarding process. We’ve walked through these decisions with many customers and have outlined decision impacts for you so you’re not left wondering “what if”. Learn more about Cloudsmith [here](https://cloudsmith.com/) to get started with us. See you on the other side! 

## FAQs (Frequently asked questions)

### 1. What is access control in a multi-format repository?

Access control defines who can read, write, or administer artifacts across different package formats stored in the same repository. It ensures secure, consistent governance across diverse tooling.

### 2. How do permissions work in Cloudsmith for multi-format repositories?

Cloudsmith supports global, repository-level, team-based, and user-specific permissions, allowing organizations to tailor access to packages, teams, service accounts, and even individual artifact actions.

### 3. Why is fine-grained access control important in software supply chain security?

Fine-grained controls reduce the blast radius of errors, prevent unauthorized writes, and help organizations enforce policies required by modern software supply chain frameworks like SLSA and SSDF.

### 4. What are entitlement tokens used for in Cloudsmith?

Entitlement tokens provide scoped, read-only access to specific artifacts without requiring user accounts, making them ideal for external distribution, automation, or least-privilege workflows.

### 5. Can developers manage their own packages in Cloudsmith?

Yes. Cloudsmith allows permissions that let developers manage only the packages they personally created—without putting others’ artifacts at risk.

### 6. How does Cloudsmith support secure CI/CD pipeline access?

Service accounts can be granted precisely the permissions needed for pipeline operations (like write or admin) while keeping developers and collaborators restricted to read-only or scoped access.

### 7. What’s the difference between global and repository-level privileges?

Global privileges affect the entire workspace, while repository-level privileges enable granular control over specific teams, users, or service accounts interacting with a particular repository.



In a world where software ships in seconds, teams are still chained to legacy systems built for a different era. What once passed as “good enough” for storing and distributing builds has become a drain on productivity - adding risk, slowing delivery, and quietly inflating costs year after year.

In this post, we’ll break down the hidden cost of legacy artifact repositories, discuss the importance of modernizing through cloud-native artifact management, and demonstrate how you can leave the old infrastructure that has been slowing your software supply chain.

## What is legacy artifact management?

Legacy artifact management involves older on-premise artifact repositories or in-house custom systems. These tools were designed in another era, when teams used monolithic applications and updates were done once a year or even less.

The modern reality is very different. Cloud-native development, continuous CI/CD pipelines, and distributed engineering teams need a modern artifact management approach that delivers scalability, uptime, and built-in security.

This is where legacy artifact repositories fall behind. Many teams assume that on-prem systems are “more secure” because they’re isolated, but isolation no longer protects against today’s threats. Most attacks now originate upstream, through open-source dependencies that already contain vulnerabilities, malicious code injections, or compromised packages. 

With the volume and speed of issues emerging in the open-source ecosystem, an isolated, self-hosted repository cannot keep pace without continuous scanning, real-time visibility, and automated updates. Without these protections, legacy artifact management becomes a blind spot in the software supply chain - quietly storing and distributing unverified or unsafe artifacts.

## The hidden costs of legacy or on-premise artifact repositories

Legacy systems can feel safer to stick with - they’re already in place and “working.” But maintaining the status quo often hides bigger costs: outdated infrastructure, ongoing maintenance, and mounting security risks from unpatched or unsupported components.

### 1. Complexity and maintenance overhead

Legacy repositories need to be manually patched, updated, backed up, and scaled. Teams spend valuable engineering time on server management instead of innovation. Each new project or environment increases the complexity of configuration and slows down the development.

### 2. Unrecognized infrastructure costs

Hosting artifact repositories either in on-prem or in self-managed cloud VMs requires continued expenditure on storage, bandwidth, and compute. The costs increase unintentionally as the size and volume of artifacts grows (especially large Docker images or build artifacts). Beyond infrastructure, many older systems also require costly vendor support contracts for upgrades, patches, and troubleshooting. These fees often increase over time and are non-negotiable.

### 3. Security and compliance risks

Legacy systems often lack built-in scanning, access control, or software bill of materials (SBOM) capabilities. Lacking transparency in dependencies leaves teams exposed to vulnerabilities and unmet compliance requirements - something that enterprises will not be able to afford in 2025 and beyond's regulatory environment.

### 4. Scalability limitations

As repositories grow, performance bottlenecks emerge - developers face slower downloads, failed builds, and pipeline downtime, all of which directly slow release velocity and drain productivity.

## Why cloud-native artifact management is a change worth making

Legacy tools may have provided the groundwork for early DevOps, but they cannot keep up with the current software landscape. Modern organizations need next-generation artifact management - cloud-native solutions designed for speed, security, scalability, and seamless integration with cloud-native CI/CD pipelines.

A [cloud-native artifact management](https://cloudsmith.com/product/cloud-native-artifact-management) platform is more than just a storage location for packages - it’s a critical pillar of your software supply chain security. It guarantees that every artifact, from source to deployment, is verified, traceable, and instantly accessible, regardless of where your teams are working.

These capabilities are exactly why more organizations are moving to modern, cloud-native platforms that combine speed, security, and scalability to support today’s software delivery demands - reasons we explore in detail below.

### 1. No maintenance and always up to date

With legacy artifact repositories, engineering teams spend hours managing servers, applying patches, and juggling storage. A truly [cloud-native artifact management platform](https://cloudsmith.com/blog/artifact-management-a-complete-guide) is different from simply hosting a repository in the cloud—it’s built to auto-scale, self-update, and deliver continuous security without manual intervention. There’s no server downtime, no upgrade windows to schedule, and no need to plan for storage expansion - everything is handled seamlessly in the background.

### 2. Scalability without complexity

Self-hosted systems cannot keep pace with the growth in artifact volume size. A cloud-native artifact management platform dynamically boosts its capacity to manage millions of artifacts across multiple teams, regions, and projects, [without compromising performance](https://cloudsmith.com/product/global-software-distribution).

Using elastic storage and edge caching CDNs, developers are always guaranteed a [quick download and high uptime](https://cloudsmith.com/blog/scaling-for-extreme-performance).

### 3. Built-in security and compliance from the ground up

In today’s world, threats move faster than ever. With malicious packages and supply chain attacks on the rise, cloud-native artifact repositories integrate vulnerability scanning, access controls, and SBOMs (Software Bill of Materials) directly into your pipelines.

This ensures that all artifacts maintained and shared are validated, trackable, and consistent with the industry regulations such as SOC 2, ISO 27001, and FedRAMP.

No extra patching or standalone security tools - modern artifact management [integrates security](https://cloudsmith.com/product/software-supply-chain-security) into every phase of your software supply chain.

### 4. Performance and speed that empower developers

A truly cloud-native artifact repository ensures artifacts are forwarded to the closest edge location, which significantly decreases both the time spent building and deploying, which has a direct impact on increasing developer productivity and CI/CD throughput.

Engineers can focus on building features rather than waiting on downloads or troubleshooting failed builds, making software delivery faster, more reliable, and predictable.

### 5. Seamless integration with the modern DevOps toolchain

Legacy repositories often require plugins or manual scripting to integrate with CI/CD tools. Cloud-native artifact management platforms offer native integrations with [GitHub Actions](https://cloudsmith.com/product/integrations/github-actions), [GitLab CI](https://cloudsmith.com/product/integrations/gitlab-cicd), [Jenkins](https://cloudsmith.com/product/integrations/jenkins), [CircleCI](https://cloudsmith.com/product/integrations/circle-ci), and more - all via robust APIs.

This ensures that artifacts flow seamlessly through your CI/CD pipelines, maintaining consistency, traceability, and reliability from development all the way to production.

### 6. Single visibility and governance between teams

In large organizations, artifacts are often scattered across multiple repositories and sometimes duplicated, making governance and visibility a constant challenge. A cloud-native artifact management system provides a centralized, single platform for managing visibility, audit, and access.

Administrators can also manage published, promoted, or consumed artifacts - to ensure compliance and reduce the risk of unauthorized access or obsolete dependencies.

### 7. Predictable, transparent costs

In contrast to self-managed solutions that have unpredictable infrastructure charges, cloud-native artifact management follows a usage-based pricing scheme, which is predictable.

You pay for what you use. You do not expect to incur costs for hardware, maintenance, or downtime. This will ultimately lead to a reduced total cost of ownership (TCO) and a better understanding of the ROI of engineering time.

Moving legacy artifact management to a new, modern, cloud-native repository is not just a technical choice but a strategic one that enhances both the security, performance, and user experience of developing a product or service, as well as reduces costs in the long run.

Migrating from legacy artifact management to a modern, cloud-native repository improves security, performance, and the overall developer experience while helping reduce long-term operational costs. By centralizing control, simplifying scalability, and strengthening the software supply chain, teams can focus on building software more efficiently and securely.

## How to upgrade from escape legacy artifact management (step-by-step)

The idea of moving away from on-premise or legacy artifact systems to a modern, cloud-native solution can be overwhelming, but with the correct plan, it is achievable.

1. **Audit your existing repositories – **Review what you store (packages, containers, Helm charts, etc.) and where.
2. **Analyze utilization and access patterns -** Learn which teams, pipelines, and tools rely on which repositories.
3. **Select a modern artifact management platform – **Seek capabilities such as universal format support, security scanning, policy management, global availability, and automation through integrations.
4. **Plan your migration strategy – **Migrate critical projects first, automate uploads, and validate integrations.
5. **Decommission legacy infrastructure – **Once migration and validation are complete, phase out outdated systems to eliminate ongoing maintenance, reduce operational overhead, and free up resources for modern, cloud-native artifact management.

🔥**Top tip: **Cloudsmith’s [Migration](https://cloudsmith.com/campaigns/cloudsmith-migration-guide) Toolkit, combined with expert support, makes the transition seamless - preserving your history and metadata while enabling improved security and scalable infrastructure.

## The real ROI of leaving legacy, on-premise artifact management behind

Teams that modernize and migrate to cloud-native artifact management see measurable returns:

- Reduce infrastructure expenses by up to 60%.
- Faster build and deployment times across CI/CD pipelines.
- Improved developer satisfaction through simplified workflows.
- Better compliance posture with automated vulnerability management.

Time spent maintaining a legacy repository directly impacts productivity and costs. Migrating to a modern, cloud-native artifact repository preserves operational efficiency and supports long-term software delivery improvements.

## How Cloudsmith makes modern artifact management effortless

All of these challenges, including scalability, security, automation, and visibility, can be solved with a truly cloud-native approach to artifact management. And if you are planning a migration to the cloud, it is worth doing it right rather than sticking with your existing provider simply because it feels easier. A migration is already a major change, and it is the perfect opportunity to elevate your entire artifact management program. 

Cloudsmith was built from the ground up as a fully cloud-native platform that helps teams break free from the limits of traditional repositories, delivering seamless automation, built-in security, and scalable reliability in a single unified system.

Here’s how Cloudsmith enables that transition seamlessly:

- **Fully managed, always available:** Cloudsmith is truly cloud-native which means hosting, scaling, and security are built in. Teams can focus on development without worrying about infrastructure maintenance and downtime.
- **Universal support for all formats:** Whether you manage containers, packages, Helm charts, or custom binaries - with multi-format repositories, Cloudsmith provides one centralized platform for all your artifacts.
- **Unified security and compliance:** Each artifact is scanned, signed, and tracked. Cloudsmith also has vulnerability scanning, dependency metadata, and SBOM generation built-in to ensure end-to-end security for your software supply chain.
- **Global performance and distribution:** Artifacts are served over Cloudsmith’s global edge network and minimizing latency and providing fast and reliable builds across the globe.
- **Seamless CI/CD integration:** Cloudsmith integrates seamlessly with the latest DevOps platforms: GitHub Actions, GitLab CI, and Jenkins - enabling teams to automate artifact workflows, reduce manual errors, and accelerate software delivery.

A modern, cloud-native artifact repository like Cloudsmith simplifies operations, strengthens security, and accelerates software delivery - without the hidden costs or complexity of legacy systems.

## Summary: don’t let legacy on-premise artifact management hold you back

Legacy artifact management is not only dated - it’s also costly, risky, and non-sustainable. The emerging generation of cloud-native artifact management platforms, such as Cloudsmith, transcends complexity with confidence, enabling teams to achieve the visibility and velocity required to build securely at scale.

The faster you retire legacy systems, the sooner your organization can build securely, on a truly modern, cloud-native platform.

## Frequently asked questions (FAQs)

#### 1. What is legacy artifact management, and why is it a problem?

The management of legacy artifacts encompasses older systems (typically [on-premise artifact management](https://cloudsmith.com/blog/cloud-native-vs-on-premise-artifact-management-a-complete-overview)) used to store and distribute software packages. Such systems do not offer the automation, scalability, and integrated security that are needed in modern DevOps, resulting in inefficiencies and increased operational costs.

#### 2. What are the unknown expenses of legacy artifact repositories?

Beyond licensing, teams also bear the costs of infrastructure maintenance, downtime, manual updates, and security risks. These hidden expenses can quickly add up, often exceeding the investment required for a modern, cloud-native alternative.

#### 3. How do I migrate to a modern artifact repository?

Begin by auditing your existing repositories, determining dependencies, and automating the migration with the help of migration tools (such as Cloudsmith’s Migration Tool). The advantage is to retain the integrity of artifacts with the purpose of avoiding manual management.

#### 4. Why choose a cloud-native artifact repository over self-hosted options?

Uptime, scaling, and security are automatically managed on cloud-native platforms. They are CI/CD integrated, can distribute faster worldwide, and can eliminate maintenance overhead, allowing your developers to focus on their core tasks

#### 5. How does modern artifact management improve security and compliance?

Modern artifact systems integrate vulnerability scanning, SBOMs generation, and access control. This will ensure artifacts are secure, traceable, and compliant – which is essential to securing your software supply chain.



  
As a vendor, understanding your bandwidth usage is an invaluable insight into how packages are distributed across your user base and how specific users have grown over a timeframe.

As a user base grows from 10s, 100s, and 1000s of users and package downloads are many multiples of your total number of users, it's essential to understand the distribution of your bandwidth utilisation by a user (or more precisely, entitlement token's) to aid in the identification of token's that make up a large percentage of your overall traffic.

When providing an entitlement token to a user under a specific license, you trust an entitlement token will be used to download packages upon the agreed-upon terms. However, an increase in your total bandwidth may start off slow and continuously grow over several months until it's suddenly become a massive increase in your overall bandwidth. Understanding this usage and precisely where this growth originates helps identify where/where change occur and provides options to mitigate runaway bandwidth from specific entitlement tokens by changing how those specific users are managed.

**How does it work?**

Whenever a user downloads a package from a private repository using an entitlement token, the exact number of bytes transmitted from our servers to the user host is stored for that specific token as an individual log entry. At the end of each day, we calculate the total bandwidth for every user across all of our repositories containing one or more packages and store the result as a daily aggregated value representing bandwidth usage.

The easiest way to get started exploring these metrics is to check out the metrics command within the Cloudsmith CLI. Alternatively, to get more fine-grained metrics, you can implement a programmatic solution using our API or one of the API binding libraries published in various languages.

**Getting started quickly!**  
  
Using the Cloudsmith CLI you can quickly and easily query the total bandwidth usage for your repository by running the following command with your organisation/repository.

```json
{
  "_key": "14963c41eb54",
  "_type": "code",
  "code": "cloudsmith metrics tokens your-organisation/your-repository",
  "filename": null,
  "language": "text",
  "markDefs": null
}
```

```json
{
  "_key": "a291f5764c32",
  "_type": "image",
  "alt": null,
  "asset": {
    "_createdAt": "2025-06-05T07:58:56Z",
    "_id": "image-e6b4220116a9154e4e7ebaf70a09d24e911ed279-1072x402-png",
    "_rev": "gnJeqIUmT5gWK5E6lfoINB",
    "_type": "sanity.imageAsset",
    "_updatedAt": "2025-06-05T07:58:56Z",
    "assetId": "e6b4220116a9154e4e7ebaf70a09d24e911ed279",
    "extension": "png",
    "metadata": {
      "_type": "sanity.imageMetadata",
      "blurHash": "D127E#.SxutljbRkRjozt8j[",
      "dimensions": {
        "_type": "sanity.imageDimensions",
        "aspectRatio": 2.6666666666666665,
        "height": 402,
        "width": 1072
      },
      "hasAlpha": true,
      "isOpaque": true,
      "lqip": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAAAAICAYAAAD5nd/tAAAACXBIWXMAABYlAAAWJQFJUiTwAAABHElEQVR4nI2S6XKCMBRGrQJtWYql6Esom4QAYQfb93+jr3Mvytg64/jjzGSZnNz7JStLtLBFCyudeT/VMGIFPZTQQ4H1McPqIJ/HUyO8csQ2H2CmDfRIQQsLaEGOTSCxPhL5wst/DnfCCV45YVsMsESD17i6J6lvxhVfTLwlNbRIsXgROnKAk/Xcti0aWKJmsXki6guXeUr7LT6LkaEzRlxx5YvQLSa4+QBXdnDzGUdSnlStgh5Q+zN6WMCIFOdsJjWMqMQmKP62vW9+sG++savO8KsJu2qCr+iSng9eW50fqmQxSYgl11uhTyJ15kchyVc5gdZoTu19yJ47oDGJuaJHj+JkHeys44ApcCebJdfvQ7nZouO9Wfb42/wCA3rnJZolzHsAAAAASUVORK5CYII=",
      "palette": {
        "_type": "sanity.imagePalette",
        "darkMuted": {
          "_type": "sanity.imagePaletteSwatch",
          "background": "#274c56",
          "foreground": "#fff",
          "population": 4.03,
          "title": "#fff"
        },
        "darkVibrant": {
          "_type": "sanity.imagePaletteSwatch",
          "background": "#042c34",
          "foreground": "#fff",
          "population": 67.71,
          "title": "#fff"
        },
        "dominant": {
          "_type": "sanity.imagePaletteSwatch",
          "background": "#042c34",
          "foreground": "#fff",
          "population": 67.71,
          "title": "#fff"
        },
        "lightMuted": {
          "_type": "sanity.imagePaletteSwatch",
          "background": "#b3cdcf",
          "foreground": "#000",
          "population": 0.12,
          "title": "#fff"
        },
        "lightVibrant": {
          "_type": "sanity.imagePaletteSwatch",
          "background": "#83e2f5",
          "foreground": "#000",
          "population": 0,
          "title": "#000"
        },
        "muted": {
          "_type": "sanity.imagePaletteSwatch",
          "background": "#648c96",
          "foreground": "#fff",
          "population": 0.04,
          "title": "#fff"
        },
        "vibrant": {
          "_type": "sanity.imagePaletteSwatch",
          "background": "#12c8ec",
          "foreground": "#000",
          "population": 0,
          "title": "#fff"
        }
      }
    },
    "mimeType": "image/png",
    "originalFilename": "Screenshot-2020-09-01-at-16.24.31-1.png",
    "path": "images/rafvlnhi/production/e6b4220116a9154e4e7ebaf70a09d24e911ed279-1072x402.png",
    "sha1hash": "e6b4220116a9154e4e7ebaf70a09d24e911ed279",
    "size": 27507,
    "uploadId": "k6jpsTiYs7hk87F20nLhw0W5vYUVAJIZ",
    "url": "https://cdn.sanity.io/images/rafvlnhi/production/e6b4220116a9154e4e7ebaf70a09d24e911ed279-1072x402.png"
  },
  "caption": null,
  "link": null,
  "markDefs": null
}
```

The following screenshot shows an example repository contain a number of active and inactive entitlement tokens alongside the total bandwidth used. The statistics table provides a simple insight into min/max/average token usage.

You can also retrieve usage metrics for one or more specific tokens by providing a comma separated list of Entitlement token (identifiers)

`cloudsmith metrics tokens cloudsmith/example --tokens=ZGCV58VqT8Sl`

```json
{
  "_key": "015de39c6fa5",
  "_type": "image",
  "alt": null,
  "asset": {
    "_createdAt": "2025-06-05T07:58:57Z",
    "_id": "image-6b3fcd5f074bf416ab4a59a7c4f25bb2e3f251e6-1082x392-png",
    "_rev": "yO7itY9PAzaQqagh0UPB3M",
    "_type": "sanity.imageAsset",
    "_updatedAt": "2025-06-05T07:58:57Z",
    "assetId": "6b3fcd5f074bf416ab4a59a7c4f25bb2e3f251e6",
    "extension": "png",
    "metadata": {
      "_type": "sanity.imageMetadata",
      "blurHash": "D12Gya?^tRx]j[NHRQoztRf6",
      "dimensions": {
        "_type": "sanity.imageDimensions",
        "aspectRatio": 2.760204081632653,
        "height": 392,
        "width": 1082
      },
      "hasAlpha": true,
      "isOpaque": true,
      "lqip": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAAAAHCAYAAAAIy204AAAACXBIWXMAABYlAAAWJQFJUiTwAAABAklEQVR4nJWR23KCMBRFrVC0iCKtWv+hggxKCJGrlvb/v2h39gHHy1sf1oSTCSvn7IzmqsZCNZinNd6SAs7ewI40rFDBClO8fCmM/sOHuYAEusXsUIrQiXK8ClpW+w7Wzr6HtbXLHi9d6hbEVw28Qwk3KeAmXK/fBVzZ7/GOFQJ9Fry0lgbGu+wm5IEbJWZkEExjg8nQTY+RfV5OGJEd6scOV+aC1elbxn7Pz0KQt1ioWoROpPsIQi0/kz4K5vwkI9vqB9vqF+tBuik6bMpOxHwodrJkHMcK0/gkD8YRBQrvxyWfZYd10cHPWhFQTKmfNZIRu5daNZjEBuMwE8mV51f+A2jmy39XhSsLAAAAAElFTkSuQmCC",
      "palette": {
        "_type": "sanity.imagePalette",
        "darkMuted": {
          "_type": "sanity.imagePaletteSwatch",
          "background": "#284e55",
          "foreground": "#fff",
          "population": 2.65,
          "title": "#fff"
        },
        "darkVibrant": {
          "_type": "sanity.imagePaletteSwatch",
          "background": "#042c34",
          "foreground": "#fff",
          "population": 67.82,
          "title": "#fff"
        },
        "dominant": {
          "_type": "sanity.imagePaletteSwatch",
          "background": "#042c34",
          "foreground": "#fff",
          "population": 67.82,
          "title": "#fff"
        },
        "lightMuted": {
          "_type": "sanity.imagePaletteSwatch",
          "background": "#a6ccd1",
          "foreground": "#000",
          "population": 0.01,
          "title": "#fff"
        },
        "lightVibrant": {
          "_type": "sanity.imagePaletteSwatch",
          "background": "#83e2f5",
          "foreground": "#000",
          "population": 0,
          "title": "#000"
        },
        "muted": {
          "_type": "sanity.imagePaletteSwatch",
          "background": "#648494",
          "foreground": "#fff",
          "population": 0.03,
          "title": "#fff"
        },
        "vibrant": {
          "_type": "sanity.imagePaletteSwatch",
          "background": "#12c8ec",
          "foreground": "#000",
          "population": 0,
          "title": "#fff"
        }
      }
    },
    "mimeType": "image/png",
    "originalFilename": "Screenshot-2020-09-01-at-16.25.52.png",
    "path": "images/rafvlnhi/production/6b3fcd5f074bf416ab4a59a7c4f25bb2e3f251e6-1082x392.png",
    "sha1hash": "6b3fcd5f074bf416ab4a59a7c4f25bb2e3f251e6",
    "size": 25433,
    "uploadId": "f9BIqbAbcRuTcifnHMD22TCH8bSUKGL3",
    "url": "https://cdn.sanity.io/images/rafvlnhi/production/6b3fcd5f074bf416ab4a59a7c4f25bb2e3f251e6-1082x392.png"
  },
  "caption": null,
  "link": null,
  "markDefs": null
}
```

If you wish to drill down further into a specific period of usage for a token, you can supply am epoch timestamp for the `start` and `finish` parameters to include only usage within that period. In this example, a single token is displayed for all of 2019.

```json
{
  "_key": "d987e8b3a7e5",
  "_type": "code",
  "code": "cloudsmith metrics tokens cloudsmith/example --tokens=ZGCV58VqT8Sl --start=2019-01-01T00:00:00Z --finish=2019-12-31T00:00:00Z",
  "filename": null,
  "language": "text",
  "markDefs": null
}
```

```json
{
  "_key": "168888e565a5",
  "_type": "image",
  "alt": null,
  "asset": {
    "_createdAt": "2025-06-05T07:58:56Z",
    "_id": "image-3c34afed7d4612c33c98e3c1333802cb149e5cf9-1084x408-png",
    "_rev": "2MVa2LY6RC9Yy6hPJdhUfX",
    "_type": "sanity.imageAsset",
    "_updatedAt": "2025-06-05T07:58:56Z",
    "assetId": "3c34afed7d4612c33c98e3c1333802cb149e5cf9",
    "extension": "png",
    "metadata": {
      "_type": "sanity.imageMetadata",
      "blurHash": "D127E#.StRx]j[RkRjozt8jZ",
      "dimensions": {
        "_type": "sanity.imageDimensions",
        "aspectRatio": 2.656862745098039,
        "height": 408,
        "width": 1084
      },
      "hasAlpha": true,
      "isOpaque": true,
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```

It's that simple to get started!

At Cloudsmith, we want to be your “one central source of truth” for your dependencies and package management needs. And in keeping with this ideal, we are extremely pleased to announce that we have added fully configurable transparent Proxying and Caching support for Debian packages.

## **Why does this matter?**

Well, in short, it means that you can now use your private Cloudsmith repository for all of your Debian package needs – whether that is your own private packages or packages that you need from public upstream sources. Your private Cloudsmith repository is all that you need to handle both.

If you request a package from your Cloudsmith repository, and that package isn’t present in the repo, then Cloudsmith will automatically check any upstream repos that you have configured and will then fetch (and optionally cache the package for future requests) from the upstream.

This brings you several important benefits:

- ****Easier setup****. Your Cloudsmith repository is the only repository you need to configure on your clients. No more need to configure multiple repos, and handle multiple authentication credentials etc. Configure the upstreams once in Cloudsmith, and that’s it done.
- ****Isolation****. If you have cached packages and dependencies that you require in your Cloudsmith repository, then if the upstream repo goes down, is otherwise unavailable, or if the packages are removed then you can still access your cached versions. No more breaking of build or deployment process due to an unreliable upstream.
- ****Visibility****. You can view details on what specific packages were requested from the upstreams. Gain insights into what you have, and what’s missing – or who and what else you are currently relying on.
- ****Performance****. Cloudsmith repositories are backed by a performant, global CDN. This means that your own packages and those cached from an upstream are delivered with the same low latencies and speeds. Going further than this, with edge nodes in almost all geographic regions, your users will experience this performance wherever they are located. Distributed teams all benefit equally.
- ****Security and Control****. All of your packages and dependencies in one place means it’s easier for you to implement the controls and security policies that you need. Multiple sources mean multiple management tasks. Keep everything in one place and keep a tighter hold on what you have.

## **Sounds Great!. How do we set this up?.**

Well, it’s easy. In your Cloudsmith repository, you’ll see a menu item called “Upstream Proxying”. This is where we will configure our upstreams. Simply click the “Create Upstreams” button and select “Debian” to create a new Debian upstream:

You are then presented with the “Edit Debian Upstream” form. This is where we enter the details of the Debian upstream we wish to use.

We add a Name for the upstream, it’s URL and a priority weighting- in cases of multiple upstreams this will determine the order in which they are checked for a package.

We can then choose to fetch and cache any requested package (instead of just fetching them), and to verify the SSL certificates provided by the upstream. In addition, we can choose to enable this upstream for source packages too.

Next, we select the distributions and architectures that we wish to use this upstream for, and finally, we can add optional authentication headers (for private repositories that require authentication) and also optional arbitrary headers, if you wish to send something custom along with your request.

And that’s it, we have now added a new Debian upstream to our Cloudsmith repository.

Behind the scenes, Cloudsmith will now start to index the packages available in the upstream repository. The upstream will be ready for use as soon as the indexing is complete.

So now, for the next request for a package that isn’t present in this repository, Cloudsmith will check the upstream and fetch it if it is available there and also cache it in the Cloudsmith repo (if you enabled caching) for future requests. It’s that simple.

## **Summary**

Debian upstream proxying and caching support is just another step on our path to providing you with the centralized controls, security, management and visibility that you need to enable a modern, high-velocity and DevOps-first workflow for your package management needs. It means fewer things to worry about, less exposure to change and most importantly....

Well, what's most important to you? [Let us know](https://cloudsmith.com/company/contact-us/)!

Today managing your licenses with Cloudsmith has become incredibly simple.

Now, with the help of our License Compliance UI, not only can you update the license associated with a package without needing to modify a package, plus you can also view statistics of how your overall licenses appear across all packages within a repository. Don't believe me? Have a look at the screenshot below:

```json
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```

From the overview section, we can see the breakdown of total packages by format, types of licenses used across all packages in the repository, and the number of unlicensed packages in the repository.

In this example, we want all our licenses to be uploaded with the MIT License; however, several packages are missing licenses, and one package has uploaded with the wrong license. Let's open the edit view for the django-guardian package and update it to use a MIT License.

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```

At Cloudsmith, we endeavor to match the license defined within a package's metadata as accurately as possible. For example, the BSD license defined within this package's metadata is checked against a valid SPDX license.

> The SPDX License List is a list of commonly found licenses and exceptions used in free and open source and other collaborative software or documentation. The purpose of the SPDX License List is to enable easy and efficient identification of such licenses and exceptions in an SPDX document, in source files or elsewhere. The SPDX License List includes a standardized short identifier, full name, vetted license text including matching guidelines markup as appropriate, and a canonical permanent URL for each license and exception.

Anytime Cloudsmith matches a license automatically, we will always provide a description of what the license was defined as within the package's metadata, our confidence of how accurate the match is, and the new license that has been applied. You can find the following description on the edit page for any license that has been automatically applied:  
  
> The **BSD** license provided within this package’s metadata is a **0.79% match** to a **BSD Protection License** SPDX license and was automatically added to this package.

Anytime the match is not accurate to a high percentage, or the license is not supplied, we leave the license empty for you to decide how you want to resolve it.

To change this license or add a new one, select a new license from the autocomplete/dropdown and click the Edit button to save this change.

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Once all the packages within a repository have been updated with a license, the overview provides an easy way to confirm all packages are using the same license and all packages are licensed.

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## **What is GitLab CI/CD**

GitLab CI/CD is a tool that is built into GitLab. It allows you to create automated tasks that you can use to form a Continuous Integration and Continuous Delivery / Deployment process.

You configure GitLab CI/CD by adding a yaml file (called `.gitlab-ci.yml`) to your source repository. This file creates a pipeline, which will then run when a code change is pushed to the repository. Pipelines are made up of a series of stages, and each stage can each contain a number of jobs or scripts. The GitLab Runner agent will then run these jobs.

For an on-premise instance of GitLab, you can install the GitLab runner agent on your own instances, and it supports many different operating systems (thereby creating your own fleet of instances to run your pipelines). But to keep things simple in the following examples, we will use gitlab.com and the default hosted GitLab runner environments provided.

## **Why use Cloudsmith with GitLab CI/CD**

So why would you want to use Cloudsmith with your Gitlab CI/CD pipelines? Well, there are a few reasons:

1. Universality – Cloudsmith supports over 20 package formats, so whatever artifacts your project produces, you can find a home for them in a private Cloudsmith repository
2. Control – Cloudsmith private repositories provide extensive security and access controls, that have been designed to accommodate workflows such as internal development, deployment or even distribution to external customers. The fine grained permissions system available enables you to craft bespoke access control, and lock down or open up your repository as much or as little as you need.
3. Automation and Integration – Thanks to the Cloudsmith CLI and also native support for format-specific package managers, a Cloudsmith private repository can fit in seamlessly with other tools in your development or distribution processes. It provides you with a single source of truth across your packages and dependencies.
4. Performance and Reliability – As a cloud-native platform, Cloudsmith manages the availability and performance of your repositories. You don’t need to worry about managing a fleet of servers, containers or virtual machines. Global performance, backed by our ultra-fast CDN and multi-region infrastructure, ensures that your packages are delivered worldwide. Reliably, quickly and securely.

That’s not all. With features like custom domain support, configurable upstream proxying and caching, configurable edge caching rules, download logs / statistics and more, Cloudsmith aims to provide the best solution for all your package management needs. It really is the ideal tool in a high-velocity CI/CD workflow – precisely the type of workflow that GitLab CI/CD is intended to enable you to create.

## **Let’s work through an example.**

OK, so let’s get started with a worked example. The very first thing you will need is some source code in a GitLab repository that you want to build. For this example, we will build Ruby source code into a [Ruby Gem](/product/formats/ruby-repository) package.

Our project on GitLab has the following structure:

The important thing here, as previously mentioned, is the .gitlab-ci.yml file. This is where we define the GitLab CI/CD pipeline that will run when we push a change to the GitLab repo.

Let’s take a look at the .gitlab-ci.yml file:

```json
{
  "_key": "ed3258cf0790",
  "_type": "code",
  "code": "image: \"ruby:2.5\"\nvariables:\nRUBYGEMS_HOST: \"https://ruby.cloudsmith.io/demo/examples-repo\"\nstages:\n- build\n- push\nbuild:\nstage: build\nscript:\n- gem build cloudsmith-ruby-example.gemspec\nartifacts:\npaths:\n- cloudsmith-ruby-example-*\npush:\nstage: push\nscript:\n- mkdir -p ~/.gem\n- mv $CLOUDSMITH_API_KEY ~/.gem/credentials && chmod 0600 ~/.gem/credentials\n- gem push cloudsmith-ruby-example-1.0.1.gem",
  "filename": null,
  "language": "text",
  "markDefs": null
}
```

The first thing we have specified is the image that will be used when creating the Docker container for the GitLab runner that will execute this pipeline, in this case, Ruby 2.5.

Next, we add an environment variable, RUBYGEMS_HOST. This is where we define the URL of the Cloudsmith package repository that we will push the result of the build to.

We then define two stages in this pipeline, the build stage and the push stage.

****The Build Stage****

```json
{
  "_key": "09b891969c3d",
  "_type": "code",
  "code": "build:\nstage: build\nscript:\n- gem build cloudsmith-ruby-example.gemspec\nartifacts:\npaths:\n- cloudsmith-ruby-example-*",
  "filename": null,
  "language": "text",
  "markDefs": null
}
```

This stage is pretty straightforward. We just run the `gem build` command to build our Ruby source as defined in our cloudsmith-ruby-example.gemspec file. Following this, we have defined an `artifact` job, as we need to temporarily store the output of the build so that the push stage next can use it.

This is because different stages in a pipeline will run on a new runner instance, so a subsequent stage wouldn’t have the access to the package built in a previous stage. You could also perform any jobs required to build and push within the same stage, and therefore on the same runner to avoid this, but for more complex pipelines you’ll likely have many stages.

****The Push Stage****

```json
{
  "_key": "e5c4254df65b",
  "_type": "code",
  "code": "push:\nstage: push\nscript:\n- mkdir -p ~/.gem\n- mv $CLOUDSMITH_API_KEY ~/.gem/credentials && chmod 0600 ~/.gem/credentials\n- gem push cloudsmith-ruby-example-1.0.1.gem",
  "filename": null,
  "language": "text",
  "markDefs": null
}
```

The push stage is a little bit more complex. This is due to the fact that we are going to push our package to a private Cloudsmith repo, which requires authentication. The Ruby package manager, gem, allows you to store your authentication credentials (in our case, the Cloudsmith API Key) in a credentials file, located at ~/.gem/credentials – But of course, we don’t want to check this credentials file into our GitLab repository along with our source!

So we can make use of GitLabs ability to add variables to the source code repository. We can create a file variable called “CLOUDSMITH_API_KEY”, and then as part of the push step, we add a job to move this variable into the required location before we run the `gem push` command.

You add this file variable in your GitLab repository settings:

Now, when our push step runs, the `mkdir` and `mv` jobs will create the required ~/.gem/credentials file (with our Cloudsmith API Key in it), and all without exposing our API Key in any logs on the runner instance, nor checked in with our source code.

The final job in our push step simply runs `gem push` to upload the package we have built to our private Cloudsmith repo, as Cloudsmith repositories offer full native support for the `gem` package manager.

****Triggering the pipeline****

All that is left to do is for us to make a change to our source, and the commit and push the change to our Gitlab repo. Let’s see what happens when we do that.

We make a change, commit it and push:

The Gitlab CI/CD pipeline starts, and the build stage executes:

The build stage runs `gem build` to build the package and then stores it in GitLab’s temporary artifact storage:

The Push stage then starts to execute once the Build stage completes:

The push stage downloads the package from the temporary artifact storage, creates the required `~/gem/credentials` file, and runs `gem push` which uploads the package to our private Cloudsmith repository:

And that’s it, the pipeline is now complete and reports as "Passed":

If we now go and login to Cloudsmith, and check our `examples-repo` repository, we can see that the Ruby gem we just built is present:

## **Final Thoughts**

Integrating a private Cloudsmith repository with GitLab CI/CD pipeline is easy, whether you are building a package that Cloudsmith provides native tooling support for (like Ruby) or even if you are using the Cloudsmith CLI to push a raw file, or other binary artifact. You can add your own private Cloudsmith repository with just a couple of lines of configuration, and it just works.

Package management can be complex and difficult, and doubly so if you are trying to manage your own package management solution and infrastructure at the same time. Try it for yourself, and see the productivity and efficiency gains that you can get from a centralized, hosted, secure package management service.