--- title: "Getting Started with Unity and Cloudsmith | Cloudsmith" description: "A short demo of how to get started with Unity packages and Cloudsmith, including pushing a package to a private Cloudsmith repository and then adding a package to a Unity project. " canonical_url: "https://cloudsmith.com/blog/getting-started-with-unity-and-cloudsmith" last_updated: "2021-06-01T00:00:00.000Z" --- # Getting Started with Unity and Cloudsmith | Cloudsmith [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. ```json { "_key": "5a4b45476f69", "_type": "tableBlock", "caption": "LLMOps vs DevOps", "firstRowIsHeader": true, "markDefs": null, "table": { "rows": [ { "_key": "d673a428-3c6a-49c3-87fa-b7dfdff2ec98", "_type": "tableRow", "cells": [ "Category", "DevOps", "LLMOps" ] }, { "_key": "453e4f7a-37ed-4c9c-8bd9-1610932f52de", "_type": "tableRow", "cells": [ "Primary focus", "Application code and services", "Large language models and AI systems" ] }, { "_key": "8bef99c7-76e1-4dc0-81f3-8f96bc8be683", "_type": "tableRow", "cells": [ "Pipeline type", "Linear CI/CD pipelines", "LLM pipelines (training, fine-tuning, evaluation)" ] }, { "_key": "30efc20f-d752-4f94-b718-b4bac0e30ace", "_type": "tableRow", "cells": [ "Artifact types", "Software artifacts (containers, binaries)", "AI artifacts (models, prompts, embeddings)" ] }, { "_key": "30be9c5f-912a-4b10-b7ba-8a3d3b594016", "_type": "tableRow", "cells": [ "Behavior", "Deterministic and reproducible", "Probabilistic and context-dependent" ] }, { "_key": "17362cff-191b-4f7a-9c4a-3c2b2a8be477", "_type": "tableRow", "cells": [ "Change frequency", "Deliberate versioning", "Rapid iteration of prompts and datasets" ] }, { "_key": "b1fc02b1-3d99-4d38-aa79-6a8215086984", "_type": "tableRow", "cells": [ "Traceability", "Moderate (log-based)", "Critical (lineage-based for compliance)" ] } ] } } ``` 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. It’s official: regulations by the US and UK governments are coming down the track to secure the software supply chain. Earlier this month, President Biden signed an [Executive Order](https://www.whitehouse.gov/briefing-room/presidential-actions/2021/05/12/executive-order-on-improving-the-nations-cybersecurity/) (EO) to increase cybersecurity defences across the U.S, with an emphasis on enhancing the security of the software supply chain. Now, the [UK government](https://www.gov.uk/government/publications/call-for-views-on-supply-chain-cyber-security/call-for-views-on-cyber-security-in-supply-chains-and-managed-service-providers) is following suit, having announced their own call for advice on defending against software supply-chain attacks. The supply chain attacks at SolarWinds and [CodeCov](https://cloudsmith.com/resources/blog/thoughts-on-the-codecov-breach) have shaken governments. The EO targets the software industry when it says, “Too much of our software, including critical software, is shipped with significant vulnerabilities that our adversaries exploit.” The US wants to know what is in the software they rely on and how securely it is built. ## **How could this affect your DevOps and Software Engineering teams?** Within 60 days of the EO, the US government will publish the following: - Minimum elements for a Software Bill of Materials (SBOM). - Guidelines recommending minimum standards for vendors’ testing of their software source code, including identifying recommended types of manual or automated testing (such as code review tools, static and dynamic analysis, software composition tools, and penetration testing). The SBOM is a critical element of the EO, essentially a record of all of the components and dependencies used in building software. Most software contains libraries and packages sourced from the open-source community or commercial software. The end-user can use the SBOM to perform vulnerability or license analysis, both of which can evaluate risk in a product. The EO specifically calls out actions to prove the security and provenance of open-source software (OSS). There is a fear that the OSS supply chain is a potential avenue of attack for hackers. Most modern software relies on many OSS packages, which will only increase moving forward as software becomes more and more complex. The EO indicates that OSS packages used in software will need to be checked for: - 3rd party dependencies. - Known security or reliability issues. The EO may force Software developers and DevOps Engineers to change their practices and update their CI/CD pipelines to increase the visibility of the software composition, increase automation and attest to their security practices. ## **The EO's 10 steps to securing your software supply chain** 1. Secure software development environments using administratively separate build environments, controlling access, 2-factor authentication and by monitoring operations on the build environments. 2. Provide proof that your software was developed in a secure software development environment when requested by a purchaser. 3. Use automation to maintain trusted source code supply chains, thereby ensuring the integrity of the code. 4. Automation tools checking for known and potential vulnerabilities and fixes shall operate regularly. 5. The Purchaser may request proof of Automation and a summary report of risks and mitigations. 6. Maintain accurate and up-to-date data, provenance (i.e., origin) of software code or components, and controls on internal and third-party software components, tools, and services present in software development processes, and regularly perform audits and enforcement of these controls. 7. Provide a purchaser with a SBOM. 8. Participate in a vulnerability disclosure program that includes a reporting and disclosure process. 9. Attest to conformity with secure software development practices. 10. Attest to the integrity and provenance of OSS used within any portion of a product. ## **Secure your supply chain with Cloudsmith** Cloudsmith is uniquely positioned to help Engineers secure their supply chain and meet the new requirements the US and UK government will be introducing. Cloudsmith provides an entirely managed cloud-native ‘single source of truth’ for all software and its dependencies, isolating and protecting you and your customers from supply chain attacks. Using continuous packaging (CP), we offer the observability and control to ensure that your software is always verified, packaged and ready to deliver. Build and ship your software with Cloudsmith to secure your supply chain and comply with future regulations. At Cloudsmith, we believe that packaging should be at the centre of any modern build and deployment process. In fact, we think that Continuous Packaging is the glue that ties Continuous Integration and Continuous Deployment or Delivery together. So with that in mind, in this blog, we will take a walk through how easy it is to integrate Cloudsmith with a Semaphore CI workflow and push the artifacts and packages that you build to a private repository. ****TL:DR**** – It’s super easy. You just need to add a block to a pipeline in a Semaphore CI workflow that installs the [Cloudsmith CLI](https://help.cloudsmith.io/docs/cli), and then uses the CLI to push your package. We will step through how you do that! ****What is Semaphore CI?**** Semaphore CI is a Continuous Integration and Continuous Deployment or Delivery platform. It’s cloud-native, fast, easy to get started with and supports any platform or language. You can create your workflow and pipelines by writing the YAML configuration files directly, committing them along with your source code, or using the intuitive Visual Builder that Semaphore includes. Building a workflow from scratch is beyond the scope of this blog, but we have created a straightforward example workflow that we can walk through to see where Cloudsmith fits in and how to set things up. ****Let’s get started!**** When you first log into Semaphore, you can authorise it to connect to your GitHub account and then choose which repository you want to use to create a Semaphore Project. Once you do this, Semaphore automatically installs the required hooks in your source repo so that new pushes can trigger your workflows on all or specific branches, or even for pull requests: The next thing that we need to set up is to add our Cloudsmith API Key as a secret for this Semaphore project, as the Cloudsmith CLI requires the API Key to authenticate to Cloudsmith to push a package. It’s easy to add a secret to a Semaphore project and then use it as an environment variable in a pipeline: Remember ALWAYS to store secrets used in your build or deployment processes in a secrets manager (here were are using the built-in Semaphore secrets store) or encrypted in some form. Never, ever add secrets or credentials to your configuration files as plain text, or commit any in your source. OK, that’s the basics of our project settings configured. Now let’s take a look at the centrepiece of a Semaphore build and deployment process – the Workflow. ****Semaphore Concepts**** At this point, it’s probably worth running over a few of the terms we will come across when describing this workflow and what they mean. First, you have the workflow itself, which may consist of multiple pipelines, perhaps one to run tests and another for deployment. Pipelines then consist of one or more blocks. Blocks run on an agent, which defines the execution environment, and they also specify which Jobs need to run. Jobs themselves then specify the commands that you want to execute. In our example workflow here, we just have two blocks – A “Build Package” block and a “Push Package” block: This is how things look in the Semaphore Visual Builder, and we can also drill down into individual blocks here to see the jobs within them. For example, this is what the “Checkout and Build” Job from the “Build Package” block looks like: As previously mentioned though, all configuration in Semaphore is specified in YAML files. The initial pipeline is sourced from .semaphore/semaphore.yml. So let’s go and take a look at that now and see what it contains. The semaphore.yml file starts by declaring a name for the pipeline and the agent that defines the hardware and software environment that the blocks will use: ```json { "_key": "8387128e8200", "_type": "code", "code": "version: v1.0\nname: Initial Pipeline\nagent:\n machine:\n type: e1-standard-2\n os_image: ubuntu1804", "filename": null, "language": "text", "markDefs": null } ``` Next we declare our blocks. The first block we declare is the “Build Package” block: ```json { "_key": "f361703d298a", "_type": "code", "code": "- name: Build Package\n task:\n jobs:\n - name: Checkout and Build\n commands:\n - cache clear\n - checkout\n - make\n - fpm -f -s dir -t deb -v 1.3.1 -n cloudsmith-semaphore-demo .\n - cache store package cloudsmith-semaphore-demo_1.3.1_amd64.deb\n prologue:\n commands:\n - sudo apt-get update\n - sudo apt-get -y install ruby ruby-dev rubygems\n - gem install --no-document fpm", "filename": null, "language": "text", "markDefs": null } ``` There are a few things to note here. First, is that any commands listed in the prologue are executed before each job, and here we use these to install the required tooling that we need to for our project (in this case, the rubygem “fpm”, which we will use to create a Debian package once our source is built) Then, the commands in our “Checkout and Build” job will run. Going through these one at a time, the first command clears the Semaphore cache, so any artifacts from previous runs of this pipeline will be removed. Next, we check out our project source and run “make” to build our source. We then use “fpm” to package the results of our build into a Debian package, and finally, we store the built package in the Semaphore cache with the cache key “package”. We need to use the Semaphore cache to pass files between blocks and jobs as each job runs in a separate, isolated machine that starts with a clean environment. The second block that we declare is our “Push Package” block: ```json { "_key": "f57b1640e925", "_type": "code", "code": " - name: Push Package\n task:\n secrets:\n - name: Cloudsmith-API\n jobs:\n - name: Push\n commands:\n - cache restore package\n - cloudsmith push deb demo/examples-repo/debian/buster cloudsmith-semaphore-demo_1.3.1_amd64.deb\n prologue:\n commands:\n - sem-version python 3.7\n - pip install cloudsmith-cli", "filename": null, "language": "text", "markDefs": null } ``` Things to note here are that we use the prologue to install the required tooling for the Block, namely the Cloudsmith CLI. We also use the secret that we added to the project here, which sets up our Cloudsmith API Key as an Environment Variable when the job runs. In the “Push” job, we simply restore the package from the Semaphore cache. Then we use the “cloudsmith push” command with the Cloudsmith account called “demo”, our repository called “examples-repo”, and we are using “Debian” and “Buster” as the distribution and version for this package. So putting that all together, our complete semaphore.yml file looks like this: ```json { "_key": "c747da443945", "_type": "code", "code": "version: v1.0\nname: Initial Pipeline\nagent:\n machine:\n type: e1-standard-2\n os_image: ubuntu1804\nblocks:\n - name: Build Package\n task:\n jobs:\n - name: Checkout and Build\n commands:\n - cache clear\n - checkout\n - make\n - fpm -f -s dir -t deb -v 1.3.1 -n cloudsmith-semaphore-demo .\n - cache store package cloudsmith-semaphore-demo_1.3.1_amd64.deb\n prologue:\n commands:\n - sudo apt-get update\n - sudo apt-get -y install ruby ruby-dev rubygems\n - gem install --no-document fpm\n - name: Push Package\n task:\n secrets:\n - name: Cloudsmith-API\n jobs:\n - name: Push\n commands:\n - cache restore package\n - cloudsmith push deb demo/examples-repo/debian/buster cloudsmith-semaphore-demo_1.3.1_amd64.deb\n prologue:\n commands:\n - sem-version python 3.7\n - pip install cloudsmith-cli", "filename": null, "language": "text", "markDefs": null } ``` That’s all we need for this job to push the package to our private Cloudsmith repository. Now, because Semaphore configured our Github repository automatically when we initially set up the project, all that is left for us to do is make a change to our source, add and commit the change, and then “git push”: This push then triggers the Semaphore workflow to start: Our pipeline is now running, and we can see that the “Build Package” block is executing the “Checkout and Build” Job: We can view a live tail of the logs from this block, and we can watch for the output of each command in the job: The job completed all commands successfully, and now the “Push Package” block starts and executes the “Push” job: Again, we can view the logs from this block, and we can see that the “cloudsmith push” command succeeded and pushed our package to our private Cloudsmith repository: That’s everything complete. Our Semaphore workflow ran successfully, and the package we created in our build process was uploaded to Cloudsmith. We can take a look now at our Cloudsmith repository and see our new package: ****Summary**** It is easy to add a private Cloudsmith repository to a workflow that you have in Semaphore CI. You don’t need to make sweeping changes to your build process. Cloudsmith and its universal package support means that, in reality, you are just a “cloudsmith push” away from adding your own central, single source of truth for your package management needs. In doing so, you are one step closer down the path of Continuous Packaging. Continuous Integration, Continuous Packaging, Continuous Deployment / Delivery. The modern DevOps workflow, helping you secure and control your software supply chain. At Cloudsmith, our mission is to make it as easy and straightforward as possible to get your packages into our system from where you can manage and distribute them to your heart's content. To this end, we recently spent some time with Atlassian's Bitbucket team at [AppWeek in Berlin](http://go.atlassian.com/awspace) to build a [Bitbucket Pipe](https://confluence.atlassian.com/bitbucket/pipes-958765631.html) that makes it simple for Bitbucket users to easily turn their source code into distributable packages and deploy to Cloudsmith in just a few lines of YAML. > _Put that in your pipe and ship it._ ## How it works Pipes build on top of Bitbucket's excellent [Pipelines](https://bitbucket.org/product/features/pipelines) functionality which allows users to automate their build and deploy processes, whatever form they may take. Bitbucket Pipes are, at their simplest, the combination of a Docker container and some YAML-formatted configuration. Pipes are designed to remove what would otherwise be repeated or verbose configuration from a user's pipeline. Pipes can be shared across repositories or organisations and make many common tasks almost trivial. ### Using Pipelines The Cloudsmith pipe is included in Bitbucket's collection of officially maintained pipes and is available by default for any user that wishes to include it in their pipeline. To use the pipe you'll first need an application or library that can be packaged into one of the formats that Cloudsmith support. You can see examples of Python and Javascript libraries in [Cloudsmith's Bitbucket account](https://bitbucket.org/cloudsmith-io/). For the purposes of this example we'll assume you're using the Python example from the link above. First, ensure that you can package your code using a Bitbucket pipeline by editing `bitbucket-pipelines.yml` in your repository. You can do so either via Bitbucket's web UI or using your normal editor and Git workflow. For the example library, a basic pipeline that builds a package when a new tag is created looks like so: ```json { "_key": "b84b268143e2", "_type": "code", "code": "image:\n name: atlassian/default-image:2\n\nbuild: &build\n step:\n name: Build Python Package\n image: python:3.7\n script:\n - python setup.py sdist\n artifacts:\n - dist/**\n\npipelines:\n tags:\n release-*:\n - <<: *build", "filename": null, "language": "text", "markDefs": null } ``` This pipeline will build a new package each time you push an appropriate tag you your Bitbucket repository. The built package is then discarded as we have not yet added further instructions to tell Bitbucket what to do with it. ### Configuring the Pipe Next we'll add publish the package to Cloudsmith using our official pipe. We'll need to provide an API Key that the pipe can use to authenticate with Cloudsmith. You can find the official documentation for pipeline variables in the [Bitbucket documentation](https://confluence.atlassian.com/bitbucket/variables-in-pipelines-794502608.html). The API Key should be added as a "secure" variable (so it doesn't leak into logs) with the name `CLOUDSMITH_API_KEY`. ```json { "_key": "36b0072d52dd", "_type": "image", "alt": null, "asset": { "_createdAt": "2025-06-05T07:57:57Z", "_id": "image-17ac024985aa121ff59058a42f5cb76e49a150fe-1938x650-png", "_rev": "2MVa2LY6RC9Yy6hPJdh5s2", "_type": "sanity.imageAsset", "_updatedAt": "2025-06-05T07:57:57Z", "assetId": "17ac024985aa121ff59058a42f5cb76e49a150fe", "extension": "png", "metadata": { "_type": "sanity.imageMetadata", "blurHash": "D5SF@VSj?b~q^+tnRk%Mxt-:", "dimensions": { "_type": "sanity.imageDimensions", "aspectRatio": 2.9815384615384617, "height": 650, "width": 1938 }, "hasAlpha": true, "isOpaque": true, "lqip": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAAAAHCAYAAAAIy204AAAACXBIWXMAAAsSAAALEgHS3X78AAABHklEQVR4nFVR7Y7DIAzr+7/lTdXabS2Ur0II4FPSSrv7YSUKieOYKVMD94FSCO+PwWNe8TOvWF4bQkgoRDcqSqlX1JwUWWqFQLWitY7JJQZxBxFjMx7zsuHx/GBedqxvi804GOtgDw9jPYzEO7dHuOHhQ0KtjMknRuWOooQB87pjXozi+TJ4fYT0wG7cBRuw2YjdRjifEGKCjwlnLpfCszS0NkCVYV1URbrVRcXhApyPqkARM3w8NaZckPVsQmVG7x1TOBnMHcwN6cyIKSNn8efyKstQLl8fpfaHhFu7wKw+TlEIW1e5IjvEEykJQdUl0kRU1Z/W5JqmubyJojGGRqnJkol5YAyg96EF8URIhVCW/CeQ4Yvgmw/tk0+VmV/27x8j7xNakgAAAABJRU5ErkJggg==", "palette": { "_type": "sanity.imagePalette", "darkMuted": { "_type": "sanity.imagePaletteSwatch", "background": "#4c4c4c", "foreground": "#fff", "population": 0, "title": "#fff" }, "darkVibrant": { "_type": "sanity.imagePaletteSwatch", "background": "#28335c", "foreground": "#fff", "population": 0, "title": "#fff" }, "dominant": { "_type": "sanity.imagePaletteSwatch", "background": "#acb4d7", "foreground": "#000", "population": 0.48, "title": "#fff" }, "lightMuted": { "_type": "sanity.imagePaletteSwatch", "background": "#acb4d7", "foreground": "#000", "population": 0.48, "title": "#fff" }, "lightVibrant": { "_type": "sanity.imagePaletteSwatch", "background": "#bcd4fc", "foreground": "#000", "population": 0, "title": "#000" }, "muted": { "_type": "sanity.imagePaletteSwatch", "background": "#737c84", "foreground": "#fff", "population": 0.05, "title": "#fff" }, "vibrant": { "_type": "sanity.imagePaletteSwatch", "background": "#8e9cce", "foreground": "#000", "population": 0.02, "title": "#fff" } } }, "mimeType": "image/png", "originalFilename": "bitbucket_cloudsmith_api_key.png", "path": "images/rafvlnhi/production/17ac024985aa121ff59058a42f5cb76e49a150fe-1938x650.png", "sha1hash": "17ac024985aa121ff59058a42f5cb76e49a150fe", "size": 91464, "uploadId": "q5Ue6EyKqz4hQULjIJGilbu3tF1J2517", "url": "https://cdn.sanity.io/images/rafvlnhi/production/17ac024985aa121ff59058a42f5cb76e49a150fe-1938x650.png" }, "caption": null, "link": null, "markDefs": null } ``` Once authentication is configured, you can add the pipe configuration to your pipeline. If using the web UI to configure your pipeline, you can select the Cloudsmith pipe right from your browser, from within the list of supported pipes as in the image below: ```json { "_key": "3318854f7732", "_type": "image", "alt": null, "asset": { "_createdAt": "2025-06-05T07:57:56Z", "_id": "image-fcfae07021137502ffe72a588b90c2c88c499ea5-2000x943-png", "_rev": "2MVa2LY6RC9Yy6hPJdh5Ra", "_type": "sanity.imageAsset", "_updatedAt": "2025-06-05T07:57:56Z", "assetId": "fcfae07021137502ffe72a588b90c2c88c499ea5", "extension": "png", "metadata": { "_type": "sanity.imageMetadata", "blurHash": "M5Ss52~W4oM|xu_3IVRiM|t7D*s,bI-pRj", "dimensions": { "_type": "sanity.imageDimensions", "aspectRatio": 2.1208907741251326, "height": 943, "width": 2000 }, "hasAlpha": true, "isOpaque": true, "lqip": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAAAAJCAYAAAAywQxIAAAACXBIWXMAAAsSAAALEgHS3X78AAABIElEQVR4nI2Sy2rFMAxE8/9f2GUXhVJoEz8kW35lyiiLXmh6qWFIENHJaKwtRsERMkIUpCRIWVFqQ+vjRh0iBewRNVTrqNZgfNYG0Yot5YIQxIE5C7RU9D6w1vqlMSeyFOxHQkzqAKVKRdaKI2ZsLByH4GtPSDnDzLz57qx1Qos5MMTswFIMpZrXYxJspVzAfU8QVfTecZ7nLZB1Nu9HdNGZtY7mGj7+dmWiyPln1L8OgWyiO7qp1TzbMaaL7z6yKoMl7N7ZI9CsIYt6dnQ3xvS+OZdf2sYPWJzrxHMcM1w+cgiXQ+bHqeZaF7AR2Brm5F94k+dTsYkjc7V421wVupTSETLXxrAxBw+2/0Pt2jvuqcOsQWvD24fi5TXh/VPxDRoPwBSYx8PKAAAAAElFTkSuQmCC", "palette": { "_type": "sanity.imagePalette", "darkMuted": { "_type": "sanity.imagePaletteSwatch", "background": "#444b55", "foreground": "#fff", "population": 0.03, "title": "#fff" }, "darkVibrant": { "_type": "sanity.imagePaletteSwatch", "background": "#1644b9", "foreground": "#fff", "population": 0.01, "title": "#fff" }, "dominant": { "_type": "sanity.imagePaletteSwatch", "background": "#2d61ca", "foreground": "#fff", "population": 0.16, "title": "#fff" }, "lightMuted": { "_type": "sanity.imagePaletteSwatch", "background": "#adafce", "foreground": "#000", "population": 0.07, "title": "#fff" }, "lightVibrant": { "_type": "sanity.imagePaletteSwatch", "background": "#9db0ec", "foreground": "#000", "population": 0.02, "title": "#fff" }, "muted": { "_type": "sanity.imagePaletteSwatch", "background": "#606980", "foreground": "#fff", "population": 0.11, "title": "#fff" }, "vibrant": { "_type": "sanity.imagePaletteSwatch", "background": "#2d61ca", "foreground": "#fff", "population": 0.16, "title": "#fff" } } }, "mimeType": "image/png", "originalFilename": "cloudsmith_bitbucket_pipeline.png", "path": "images/rafvlnhi/production/fcfae07021137502ffe72a588b90c2c88c499ea5-2000x943.png", "sha1hash": "fcfae07021137502ffe72a588b90c2c88c499ea5", "size": 243096, "uploadId": "qTmiAIOXZQWch3JnhsO4Ie9zUa0CW2lY", "url": "https://cdn.sanity.io/images/rafvlnhi/production/fcfae07021137502ffe72a588b90c2c88c499ea5-2000x943.png" }, "caption": null, "link": null, "markDefs": null } ``` If using your local editor, you can follow the instructions in the [official README on Bitbucket](https://bitbucket.org/cloudsmith-io/publish). Once added, your pipeline YAML should look something like so: ```json { "_key": "6db63f6f5c45", "_type": "code", "code": "image:\n name: atlassian/default-image:2\n\nbuild: &build\n step:\n name: Build Python Package\n image: python:3.7\n script:\n - python setup.py sdist\n artifacts:\n - dist/**\n\npublish: &publish\n step:\n name: Publish Python Package\n script:\n - pipe: cloudsmith-io/publish:0.1.1\n variables:\n CLOUDSMITH_REPOSITORY: 'cloudsmith/examples'\n CLOUDSMITH_API_KEY: $CLOUDSMITH_API_KEY\n PACKAGE_FORMAT: 'python'\n PACKAGE_PATH: 'dist/*.tar.gz'\n\npipelines:\n tags:\n release-*:\n - <<: *build\n - <<: *publish", "filename": null, "language": "text", "markDefs": null } ``` This configuration instructs the pipe to push artifacts to the [cloudsmith/examples](https://cloudsmith.io/~cloudsmith/repos/examples/packages/) repository, with the API key we stored earlier. We're uploading a `python` package which is located at `dist/*.tar.gz`. ### Using the Pipe And that's it! Your pipe is now configured and ready to run. You should be able to push a new tag to Bitbucket and see your pipe run. Bitbucket's pipeline UI provides a great overview of the status of your jobs: ```json { "_key": "3c4a8db1936b", "_type": "image", "alt": null, "asset": { "_createdAt": "2025-06-05T07:57:56Z", "_id": "image-c53d017dd822d85b4a96914878ef3f42901c49c0-1494x824-png", "_rev": "2MVa2LY6RC9Yy6hPJdh5YC", "_type": "sanity.imageAsset", "_updatedAt": "2025-06-05T07:57:56Z", "assetId": "c53d017dd822d85b4a96914878ef3f42901c49c0", "extension": "png", "metadata": { "_type": "sanity.imageMetadata", "blurHash": "M~KUp5~qRjIUt7R%WUfRj]juRjR*jtoLj[", "dimensions": { "_type": "sanity.imageDimensions", "aspectRatio": 1.8131067961165048, "height": 824, "width": 1494 }, "hasAlpha": true, "isOpaque": true, "lqip": "data:image/png;base64,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", "palette": { "_type": "sanity.imagePalette", "darkMuted": { "_type": "sanity.imagePaletteSwatch", "background": "#1c2434", "foreground": "#fff", "population": 37.68, "title": "#fff" }, "darkVibrant": { "_type": "sanity.imagePaletteSwatch", "background": "#04152a", "foreground": "#fff", "population": 0.02, "title": "#fff" }, "dominant": { "_type": "sanity.imagePaletteSwatch", "background": "#1c2434", "foreground": "#fff", "population": 37.68, "title": "#fff" }, "lightMuted": { "_type": "sanity.imagePaletteSwatch", "background": "#b2c3cc", "foreground": "#000", "population": 0.92, "title": "#fff" }, "lightVibrant": { "_type": "sanity.imagePaletteSwatch", "background": "#88e8b8", "foreground": "#000", "population": 0.01, "title": "#fff" }, "muted": { "_type": "sanity.imagePaletteSwatch", "background": "#5cae83", "foreground": "#fff", "population": 5.38, "title": "#fff" }, "vibrant": { "_type": "sanity.imagePaletteSwatch", "background": "#3ca074", "foreground": "#fff", "population": 0.01, "title": "#fff" } } }, "mimeType": "image/png", "originalFilename": "cloudsmith_bitbucket_pipeline_ui.png", "path": "images/rafvlnhi/production/c53d017dd822d85b4a96914878ef3f42901c49c0-1494x824.png", "sha1hash": "c53d017dd822d85b4a96914878ef3f42901c49c0", "size": 68852, "uploadId": "Pz1P1cyaags8bli5y20Sq50e56ipmkML", "url": "https://cdn.sanity.io/images/rafvlnhi/production/c53d017dd822d85b4a96914878ef3f42901c49c0-1494x824.png" }, "caption": null, "link": null, "markDefs": null } ``` Once pushed, you should see your shiny new package in the Cloudsmith UI, ready for download and install using your preferred tools: ```json { "_key": "7e85e97eb6b7", "_type": "image", "alt": null, "asset": { "_createdAt": "2025-06-05T07:57:57Z", "_id": "image-293b6b26210d9ff68d9bc076ddf5f673ed7d97cc-2000x977-png", "_rev": "2MVa2LY6RC9Yy6hPJdh5lQ", "_type": "sanity.imageAsset", "_updatedAt": "2025-06-05T07:57:57Z", "assetId": "293b6b26210d9ff68d9bc076ddf5f673ed7d97cc", "extension": "png", "metadata": { "_type": "sanity.imageMetadata", "blurHash": "M5SF@U019F_4N_-=IrIot7oz~WRj%Mt5s+", "dimensions": { "_type": "sanity.imageDimensions", "aspectRatio": 2.0470829068577276, "height": 977, "width": 2000 }, "hasAlpha": true, "isOpaque": true, "lqip": "data:image/png;base64,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", "palette": { "_type": "sanity.imagePalette", "darkMuted": { "_type": "sanity.imagePaletteSwatch", "background": "#5a514c", "foreground": "#fff", "population": 0.05, "title": "#fff" }, "darkVibrant": { "_type": "sanity.imagePaletteSwatch", "background": "#77450d", "foreground": "#fff", "population": 0, "title": "#fff" }, "dominant": { "_type": "sanity.imagePaletteSwatch", "background": "#4a74a0", "foreground": "#fff", "population": 0.99, "title": "#fff" }, "lightMuted": { "_type": "sanity.imagePaletteSwatch", "background": "#9bb1c9", "foreground": "#000", "population": 0.19, "title": "#fff" }, "lightVibrant": { "_type": "sanity.imagePaletteSwatch", "background": "#fccc8a", "foreground": "#000", "population": 0.01, "title": "#000" }, "muted": { "_type": "sanity.imagePaletteSwatch", "background": "#4a74a0", "foreground": "#fff", "population": 0.99, "title": "#fff" }, "vibrant": { "_type": "sanity.imagePaletteSwatch", "background": "#eca454", "foreground": "#000", "population": 0, "title": "#fff" } } }, "mimeType": "image/png", "originalFilename": "cloudsmith_bitbucket_upload.png", "path": "images/rafvlnhi/production/293b6b26210d9ff68d9bc076ddf5f673ed7d97cc-2000x977.png", "sha1hash": "293b6b26210d9ff68d9bc076ddf5f673ed7d97cc", "size": 354328, "uploadId": "HKrkv0uHeEeJSCMdA4DfehxXbmbn0uEK", "url": "https://cdn.sanity.io/images/rafvlnhi/production/293b6b26210d9ff68d9bc076ddf5f673ed7d97cc-2000x977.png" }, "caption": null, "link": null, "markDefs": null } ``` ## Conclusion Cloudsmith's Bitbucket pipe provides the easiest and simplest way for Bitbucket users to push their assets to Cloudsmith. Our official pipe is maintained by the Cloudsmith team and you can be sure it'll be kept up to date with all changes and features as we release them. As always, if you have any questions about the pipe (or anything else), we're available at support@cloudsmith.io. Today, almost every service now is offered in a “Cloud” variant. But what does that really mean? Are all clouds services equal? It’s easy to see why so many vendors rush to add a Cloud edition/variant of established software they sell. Undoubtedly, there has been a move to Cloud services across the industry, as more and more organizations seek to take advantage of the higher reliability and lower total cost of ownership that Cloud platforms promise. The thing to watch out for is the major difference between Cloud Hosted and Cloud-Native. When Cloud providers started to emerge; spearheaded by AWS who saw the opportunity to monetise the tooling and spare capacity they had in their data centres. We began to see other vendors jump to offer their software (which had previously been sold for on-prem use) on these Cloud platforms, hoping to capitalize on the emerging trend. A lot of “enterprise” software was never designed to run on a Cloud platform. It was never architected to take advantage of the paradigm shift that cloud computing enables, and you are left with effectively paying (a premium, in some cases) for the same software, just running on a virtual machine on a Cloud platform. This is Cloud hosted. A self-contained software solution, typically cannot take advantage of what the Cloud offers - for instance, how would it know to load balance requests? Or scale up. Most of the time, it is limited by the resources it has to hand. The fixed cpu and memory it has been allocated. On the other end of the spectrum, you have software that has Cloud built into its DNA. Software that relies on features that are only possible on Cloud platforms in order to work as it does - think fully distributed workloads, fault tolerance, and scaling for global performance. Every superhero has an origin story. This is ours. Cloudsmith is designed from the ground up as a Cloud-Native application. From day one, it has been architected to take advantage of all the technology that Cloud provider platforms offer. This is why we don’t offer Cloudsmith in an on-prem variant. It’s not just a package management solution, it’s a secure, ultra-fast delivery platform for software, harnessing the power and flexibility of the Cloud and Edge computing. It’s a smart CDN for software. In this blog, we will walk through the process of configuring a private Cloudsmith repository as an artifact source for a Harness Continuous Deployment pipeline. Harness is a Continuous Deployment platform that allows you to easily automate the deployment of your software to your infrastructure and environments. The Harness Platform has two main components: - ****The Harness Manager:**** The Harness Manager is where you manage your deployment pipelines and also where you store your deployment configurations. It is available as a SaaS or on-premises running in your own infrastructure. In this blog, we will use the SaaS version at app.harness.io. You can use the Harness Manager (or the API, or a trigger in your pipeline) to start and view your pipeline execution. - ****Harness Delegate:**** the Harness Delegate is software you install in your environment (locally or on a cloud platform of your choice), and run as a service. The Delegate connects to the Harness Manager to receive tasks and then executes these pipeline tasks on your chosen platforms. Installing the Harness delegate and building a pipeline from scratch in the Harness manager is beyond the scope of this blog, but Harness provide [excellent documentation](https://docs.harness.io/) and [tutorials](https://docs.harness.io/category/kh1sxpvd7x-common-deployments) to get you up and running. ****Let’s get started**** We are going to set up our Cloudsmith repository as a docker registry in Harness and then use Harness CD to deploy a docker image to AWS Elastic Container Service. First, we log into the harness manager, and then go to “Setup”: At this point it’s worth explaining some of the Harness key concepts, particularly Cloud Providers, Connectors and Applications : ****Cloud Providers**** Cloud Providers describe your infrastructure, such as AWS, GCP, Azure or even your own Physical Data Center. I’ve configured AWS as my Cloud Provider here and I have provided the AWS Access Key and Secret Access Key. I’ve added my AWS Secret Access Key as an encrypted secret using the included Harness Vault, and it’s always correct to use an encrypted secret and a secrets manager of some sort. Never, ever add your credential or secrets as plain text as part of a deployment pipeline. ****Connectors**** Connectors are where you integrate repositories, registries, or monitoring tools. The Connector type we will configure here is an “Artifact Server”. This is the important bit for this blog, as it is where we add our Cloudsmith repository. This is really simple, as Cloudsmith repositories are fully compatible as a native docker registry. All you need to add is your Cloudsmith registry URL – (docker.cloudsmith.io/v2/), your Cloudsmith username and your encrypted password. I’ve added my Cloudsmith API key as an encrypted secret, again using the included Harness Vault. You could also use a Cloudsmith Entitlement Token, and you can see our [Docker documentation](https://help.cloudsmith.io/docs/docker-registry) to find out how to authenticate to a Cloudsmith repository using a token. ****Applications**** The next thing we configure is an Application. Applications are how you organize a deployment project in harness and consist of Services, Environments, Workflows, Pipelines, Triggers and Infrastructure Provisioners: ****Services**** Services represent your applications and microservices, and this is where you declare the artifacts that you wish to use, any configuration variables and container specifications. This is the first thing we define for our application. I have selected my Cloudsmith artifact repository as the source server, and for my docker image name I have entered my Cloudsmith organization name “demo”, my repository name “examples-repo”, and my docker image name “cloudsmith-example-app”. I also choose here to deploy this docker image to AWS ECS: ****Environments**** An environment represents your deployment infrastructure, such a test, staging or production. This is the second thing that we define for this application. We have defined a “TEST” infrastructure here on AWS here, and this is also where wer define things like the region and cluster to be used, and the IAM execution role to use: ****Workflows**** A workflow includes the Service, Environment, and Infrastructure definitions we have added already, and then uses these for the deployment steps. A workflow is the third thing we define for this application. There are different types of Workflows, such as basic, canary and blue/green. For this example, we will use a blue/green workflow that configures an AWS load balancer, and then deploys or upgrades the containers running on our ECS cluster. You can also add things like rollback steps and notifications: ****Pipelines**** A pipelines model is a collection of one or more stages, containing Workflows for Services and other deployment and verification steps, such as Approvals We have set up a very simple single-stage pipeline here that just runs the Workflow we defined above: ****Triggers**** A Trigger is used to automate deployment in response to an event, such as Git events, a new artifact in a repository, a schedule or even the success of another pipeline. We have set up a trigger here that will start the Pipeline when a new docker image is pushed to our Cloudsmith Repository: Running the Pipeline. We have a simple python flask project, that just prints a simple message. We just need to create a docker image from this project using the ‘’docker build’ command: ```json { "_key": "19d6cafdc0aa", "_type": "code", "code": "docker build -t docker.cloudsmith.io/demo/examples-repo/cloudsmith-example-app:latest -t docker.cloudsmith.io/demo/examples-repo/cloudsmith-example-app:2.0.0 .", "filename": null, "language": "text", "markDefs": null } ``` This command also adds two tags to the image, a ‘latest’ tag and a ‘2.0.0’’ tag. Now, we just push this docker image and tags to our Cloudsmith repository, exactly as you would do with any docker registry: ```json { "_key": "8bf090077da3", "_type": "code", "code": "docker push docker.cloudsmith.io/demo/examples-repo/cloudsmith-example-app:latest docker push docker.cloudsmith.io/demo/examples-repo/cloudsmith-example-app:2.0.0", "filename": null, "language": "text", "markDefs": null } ``` That’s the docker image pushed to Cloudsmith, and we can see it now in our Cloudsmith Repository: As we have set up a Trigger in Harness, Harness will then poll any configured artifact repositories every 2 minutes for the presence of a new artifact. As a result, our Pipeline will then start to execute: We can follow the stages in our pipeline, and the steps in our workflow here, and see the log output. For example, you can see the output of the upgrade containers step here: Once the deployment has completed successfully, we can hit the address of our AWS Load Balancer in a browser and we can confirm that our docker image has been deployed to our ECS cluster, and the message that this example application prints: Our automated deployment to AWS ECS was successful, our docker image was pulled from our private Cloudsmith repository, and it was all managed and controlled by Harness CD.