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Speed, reliability, and security are now essential in modern software delivery. With organizations increasing the speed of their engineering processes, software artifacts, including Docker images and npm packages, have grown to be the foundation of the development lifecycle. It is crucial to manage these artifacts effectively in order to enable teams to deliver to users faster and with greater confidence.

Historically, artifact management, like many parts of the CI/CD pipeline, was managed in-house, with organizations setting up their own artifact repository and infrastructure. Although such a strategy was viable at smaller scales, it frequently resulted in issues, particularly the lack of storage capacity, bottlenecks in performance within a region, and a high maintenance overhead.

In recent years, organizations have been shifting 

 towards the cloud. This move to cloud-native infrastructure removes the physical limits of on-prem systems and allows teams to scale across the world, reduce latency, and sustain high performance on each stage of the CI/CD pipeline.

This blog will discuss seven aspects of how a 

 system can enhance your software delivery processes by scaling and enhancing their performance, enabling teams to deliver software more quickly, dependably, and globally.

1. Elastic scaling of storage and distribution

Conventional artifact repositories often run into difficulties when engineering teams scale their usage. As developers begin generating hundreds of thousands of versions of Docker images, packages, or libraries, traditional on-premise systems require manual maintenance. This often involves increasing on-premise systems, more hardware, manual configuration, and frequent maintenance.

In contrast, cloud-native artifact management leverages elastic scaling to automatically expand storage as demand grows. This guarantees that as engineers produce more artifacts; performance will remain constant. With physical infrastructure deletion, scalability with artifacts is easily accomplished without capacity bottlenecks, and doing incremental upgrading is costly.

 performance does not only hinge on the storage of artifacts, it also depends on how quickly they can be accessed in different regions of the world to support globally distributed teams. The problem of latency is a significant problem in globally spread enterprises when teams are compelled to draw artifacts in one, centralized on-premise repository, which is often very distant from where builds are occurring. It may cause slow builds, delays in deployments, and exasperated developers.

Cloud-native artifact management systems address this issue through replication and caching. Replication is the process of storing copies of the artifacts in more than one location, in places near the teams that require them. Caching goes a step further: When an artifact is initially requested, it is momentarily stored, or rather cached, in edge servers at key points around the world. The next time a team in that region orders the same artifact, it can be delivered directly out of the cache, and they do not have to take a long, latency-intensive journey back to a central repository.

Systems and developers can retrieve the closest copy of an artifact, which can significantly reduce their retrieval time. This type of cloud-native scaling makes global distribution a strength and not a weakness, meaning that the performance of artifacts will not be weakened when teams are operating in North America, Europe, or Asia.

3. Seamless integration with CI/CD pipelines

Automation is the core of the new-generation software delivery, and artifacts are the key to any build, test, and release. Using cloud-native artifact management, repositories have been built into CI/CD pipelines, and artifacts have been made a first-class citizen in the delivery process.

New builds are automatically checked, analyzed and subsequently validated. Integration with other tools (i.e., Jenkins, GitHub Actions, and GitLab CI) through webhooks and APIs allows pipelines to continue running seamlessly. Such integration enhances the DevOps artifact management that helps in delivering much faster with a lesser amount of manual work and risk.

 repositories are often offline due to maintenance, upgrades, or other unexpected loss of online accessibility, thereby making development difficult. Cloud-native systems provide reliability by design, with redundancy and auto-healing load balancing being part of the infrastructure. This guarantees the presence of artifacts even when the demand is high.

For engineering teams, that means repeatability, uninterrupted workflows, and confidence that outages won’t disrupt delivery. By removing the fear of downtime, organizations can stay on schedule and ensure developers always have the artifacts they need.

Scaling artifacts with traditional infrastructure is typically expensive in terms of procurement costs, such as servers, storage, and licenses. Cloud-native models typically remove this limitation by allowing users to paying-as-you-go, aligning cost directly with their use.

Enhanced capabilities, such as deduplication, avoiding storage redundancy, and tiered storage, aim to keep commonly used artifacts from high-performance systems and archive older versions in lower-cost ones. This is an efficient way to enable scale as well as prevent overspending because of team growth. When artifact scalability and economic efficiency combine, so do performance and cost in cloud-native platforms.

The larger your store of digital artifacts becomes, the more critical it is to ensure their integrity and compliance. Cloud-native repositories often have built-in security controls, as they help to keep them trustworthy and auditable. Immutability characteristics disallow alterations from being made to published artifacts, and access restrictions stop undesired users from publishing or retrieving artifacts. 

Artifacts are encrypted both at rest and in transit and are integrated with SBOM reporting to achieve regulatory (SOX, HIPAA, GDPR) compliance. This is a security-first approach that guarantees both speed and trust to enterprises, as artifact performance is coupled with integrity and compliance.

7. Future-proof scalability for innovation

Technology does not stand still, and neither should your artifact management strategy. Cloud-native systems are futuristic and therefore can be scaled as organizations start adopting new architectures like microservices, edge computing and AI-driven development.

An OCI-aligned open standard helps an enterprise achieve long-term tool- and platform-portability. Such flexibility denotes that cloud-native scalability can be used to accommodate new workloads and worldwide growth without subjecting teams to re-engineering artifact handling. Organizations prepared today receive a platform that keeps in step with tomorrow’s innovation.

How Cloudsmith delivers cloud-native scalability and performance

Cloudsmith has been created to address these problems through its fully managed and cloud-based 

. Our platform is elastic, globally distributed, and tightly integrated with CI/CD pipelines without the complexity of managing infrastructure yourself.

 Allow storage and bandwidth to scale automatically as your volumes of artifacts expand.

 Deploy artifacts to 225+ edge sites around the world to be close to immediate access.

 Be able to plug directly into pipelines to securely store, scan, and deploy artifacts.

 Artifacts are available all the time, and 99.99 percent uptime makes this possible with redundancy.

 Immutability, RBAC, encryption, and SBOM capabilities keep your supply chain compliant.

 with global reach, performance, and security, Cloudsmith transforms artifact management from a bottleneck into a competitive advantage.

As the volume and complexity of software artifacts grow, organizations must ensure both speed and scalability in how they manage them. With cloud-native artifact management, businesses unlock global distribution, resilient infrastructure, and built-in performance optimization.

With cloud-native scalability of artifact storage, your teams will have faster innovation, more reliable shipping, and the trust of your customers—today and beyond.

1. What kind of software artifacts are best suited to use cloud-native storage?

Containers, language packages (Python, npm, and Java), Helm charts, and operating system packages can all be scaled in a cloud-native environment.

2. How does artifact performance differ between cloud-native and on-prem repositories?

Cloud-native utilizes multi-region replicating, distributed caching, and scalable infrastructures in order to minimize the latency and accelerate the speed of retrieval at a global level.

3. Do large enterprises only use cloud-native artifact management?

No, startups, medium-sized teams, and enterprises all enjoy it. Cloud-native is cost-effective at each scale of size because of its pay-as-you-go model.

Parul Jhawar

Marketing

7 Ways Cloud-Native Improves Artifact Management Scalability and Performance

I learned to code in BASIC on a Commodore 64 in the early 1980s. BASIC was actually a pretty neat high-level abstraction of assembly language, which itself was an abstraction sitting on top of machine code! Since then, I’ve seen a steady stream of higher-level abstractions - relational databases, object-oriented languages, package dependencies, open source libraries, cloud-native development, containers, serverless - that have made software developers more productive, and helped us build ever more powerful applications with them.

AI is the latest abstraction layer that sits on top of existing technology, making the underlying components more powerful and easier to use. A huge amount of R&D and startup capital in the past few years has gone towards exploiting this new abstraction.

The newest and best ideas naturally attract top talent and funding. Companies and startups building cool new AI-powered apps have their choice of tech stack. And many of them are creating their new software development tool chains around Cloudsmith, which is very satisfying to Cloudsmithers.

, who built an AI-powered platform pathologists use to diagnose cancers. They manage binary packages in Cloudsmith that they use to build for a wide variety of target environments. Or 

, who builds industrial computer vision applications that improve quality and productivity, using Cloudsmith to manage binary artifacts that go into their build pipelines. 

 provides a machine learning platform for document processing and automation, built on Cloudsmith for internal development and external distribution of containers and packages. And 

, who have built an AI-powered due diligence platform, using Cloudsmith as their single source of truth for binary artifacts.

Companies that build critical infrastructure for use by other AI companies are also gravitating to Cloudsmith. Take 

, who helps organizations use, manage, and govern AI metadata with their enterprise-grade context platform. They chose Cloudsmith to make sure their artifacts are reliably and securely distributed to enterprise developers. Or 

, who distributes their SDKs and runtimes via Cloudsmith for delivery of AI-driven perception solutions to robotics and computer vision tool companies. Then there’s 

, an open source AI search platform used to develop and run large-scale applications, combining big data, vector search, machine-learned ranking, and real-time inference to enable AI applications like retrieval-augmented generation, recommendation, and intelligent search at enterprise scale. Cloudsmith supports distribution for Vespa, streamlining delivery for their open source community as well as enterprise users.

And then it’s companies who deliver AI directly to the hands of end users. 

 calls itself “the world’s most private AI,” assisting users in real time across a wide range of personal tasks. They use Cloudsmith to build and distribute packages across the software supply chain.

Cloudsmith is best known for our enterprise-grade artifact management platform, which controls and secures the software supply chain for the world’s most demanding Fortune 500 and Global 2000 organizations. But there’s a reason we also show up so often as the platform of choice for innovative AI startups and spinoffs. These companies are typically run by lean teams of seasoned software engineers. They know what they need, and they want to do it right the first time. They want developer-friendly, well-documented tools that just work.

 to manage their Hugging Face models and datasets, and we’re increasingly powering our own development of new features with AI tools. But it’s also notable that the world’s most interesting AI companies are also choosing Cloudsmith - not just to manage ML models, but to power their entire software supply chain. That’s a vote of confidence that makes us proud to be Cloudsmithers.

Glenn Weinstein

The platform of choice for AI companies

In the world of artifact management, a repository structure refers to how software artifacts—such as Docker images, Python packages, npm modules, and more—are organized, stored, and accessed. It defines how repositories are named, grouped, and managed, often aligning with how software development teams build, release, and consume software binaries across an organization.

Repository structure is a fundamental foundation of secure, efficient artifact management practices. Your goal is to create the right structure that meets the needs of your developers.

Cloudsmith has an intrinsically flexible approach to repositories. We don’t force you to have a separate repository for each format type, like most other artifact management systems do. This presents you with an opportunity to define a more meaningful structure for your repositories, and this means you have many more interesting options!

We see some common patterns among Cloudsmith users that fall into the following groups:

We’ll be covering each structure in greater detail in our upcoming blogs as part of our Repository Structure Best Practices series.

Now that we’ve identified the “what” behind repository structures, we can dig into the “why” a little bit.

We address repository structure at the beginning of our onboarding process for new customers. If you get the repo structure wrong, then over time, artifact repositories can become a ‘dumping ground’ for all manner of software artifacts. When platform engineering teams are migrating to Cloudsmith, we find that there’s often a newfound interest in organization and consolidation of software artifacts, in order to ‘do better next time’ than they were able to with their legacy solution.

Perhaps the number one question we get at this point is, “How do we balance software supply chain security best practices with a great developer experience?”

While there isn’t really one simple answer to this question, the good news is that the flexibility Cloudsmith offers in choosing the repository structure can help you to check both boxes – security AND productivity.

Key benefits of the right repository structure

Choosing a clear, intuitive structure removes significant friction for developers. If they are able to easily locate the packages they need, pull the open-source dependencies for their builds in a central location, and integrate quickly with CI/CD pipelines, you’re winning as a platform team already.

Many enterprise customers of Cloudsmith leverage a dedicated repository for all ingress packages, where open-source dependencies are proxied and cached for developers and pipelines to begin accessing. This centralized repository makes it easy for developers to remember the direct path URL for pulling on their local machines and even easier for updating their CI/CD pipelines.

With our API and UI, a developer can quickly review what packages are within a specific repository. No digging through countless folders and subfolders to find what you’re looking for!

You’ll want your developers to be able to pull dependencies, create repositories, and configure upstream sources easily. But you also want to ensure developers are working securely. Repository structure directly influences how platform teams will be able to configure repository access controls, set permissions, review vulnerabilities, and inspect audit trails for suspicious signals.

In Cloudsmith, platform teams can restrict repository access by designating only specific developer teams to have access to specific repositories. At the permissions level, you can set read/write/admin permissions for each repository. This allows for granular access control, self-serve ownership, multiformat flexibility, and better visibility into team-by-team usage.

Observability and auditability of packages within your artifact management environment are directly correlated to how fine-grained your repositories are structured. The more segmented you configure them (i.e., by specific team, application, or environment), the clearer an observability team is able to view when a package was pulled and by whom. On the contrary, if an organization just has “non-prod” and “prod” repositories with many different service accounts and users pulling packages, it might be more difficult to pin down a specific action or event.

The right repository structure really impacts an organization’s CI/CD pipelines. When pipelines are tightly coupled to poorly structured repositories, the result can be pipeline failures due to ambiguous package resolution, security risks from pulling artifacts from the wrong stage, and even increased build times due to inefficiencies in caching.

As your organization grows, what originally worked for your first few developers will often break at scale. Without a flexible, scalable repository structure, you will quickly become susceptible to artifact sprawl, naming collisions, and access control issues. Cloudsmith’s fully cloud-native architecture helps enterprise customers scale tremendously while also maintaining order and consistency across repositories.

Managing Artifacts Across Multiple Formats

Your organization is building all kinds of software, with software development across many different language formats, development teams, and environments to consider. It helps to have an artifact management platform that can support multi-format repositories, flexible upstream configurations to open-source registries, and easy-to-use package tagging.

Balancing Security With Developer Velocity

Tighter security controls and a lack of freedoms can oftentimes frustrate developers, while open policies may create security gaps. A well-thought-out repository structure strikes a balance by allowing autonomy with clear guardrails. This is part of the developer “golden path” that can be architected by a platform team. 

How the right repository structure delivers business value

Faster Software Delivery & Reduced Operational Overhead

When artifacts are easy to find, manage, and deploy, your development teams spend less time figuring out where their artifacts are and more time building great software. Reducing toil and time to market is critical for any business creating software.

Improved Agility for New Development Teams

A well-structured repository architecture supports growth by paving the way for new teams – which may include contractors – to spin up new environments (repos, teams, service accounts, tokens, etc.) by enabling replication across teams. A clear, concise, repeatable structure that only requires a few API calls makes it easier to scale without worrying about the underlying infrastructure to support globally distributed teams.

Reduced Risk With Better Visibility And Controls

Platform teams are tasked with enabling development teams to write software efficiently and securely. By having a well-defined repository structure that every development team can follow, platform teams can create clear access control policies, artifact retention policies, and user permissions. Having this visibility and control lowers the risk of shipping insecure or unverified software.

Cloudsmith’s approach to repository structure

 is a trusted advisor, helping customers design and implement the optimal repository structure that balances security, scalability, and developer productivity to support their software delivery goals.

Stay tuned for the next part of the blog series, where we will discuss the “hybrid” repository approach that factors in an organization’s services, teams, and environments in Cloudsmith.

Why does repository structure matter for developers?

A clear repository structure saves time for developers by making it easy to find and pull the right packages. It also helps avoid confusion in CI/CD pipelines and improves overall productivity.

How does repository structure improve CI/CD pipelines?

When repositories are well-structured, pipelines resolve dependencies faster, reduce build failures, and pull the right artifacts for each stage (dev, test, prod) — making delivery more reliable.

How does repository structure affect security?

Repository structure impacts how access controls, permissions, and audit logs are managed. A good structure ensures that only the right people or services can access sensitive packages.

How does Cloudsmith support flexible repository structures?

 and supports multi-format repositories, fine-grained access controls, upstream proxying for open-source, and automation via API — making it easy to design the structure you need.

How do I choose the right repository structure for my organization?

The right structure depends on your scale, security needs, and workflows. Many teams use a hybrid approach, combining team, environment, and service-based structures for flexibility and control.

Cristian Garcia

Senior Customer Success Manager

Why Repository Structure Matters

In modern enterprise software delivery, security and speed must work together—without compromise. As the development team expands, the number of software artifacts they build, like containers, packages, binaries, configuration files, and Helm charts, grows rapidly.

 is a cornerstone of DevOps and CI/CD pipelines. Not only does it centralise the results of your builds, but it also stores, secures, and distributes them so that developers, automation services, and production systems can use the right version of software at the right time.

In the case of enterprises, the potential of making the wrong choice of platform may result in integration troubles, regulatory risk and deployment delays. The right artifact platform, however, can transform your software supply chain into a secure, globally accessible, and automation-ready ecosystem.

This guide explores why artifact management is important at enterprise scale, what features to prioritise, and how to select a solution that connects both technical and business goals.

Why artifact management is essential for enterprises

Enterprise DevOps teams have their own special scale and governance problems that are more than just larger versions of those seen in small organisations. Without a dedicated artifact management solution, artifacts may be scattered across cloud buckets, file servers, and developer machines—leading to versioning chaos, security blind spots, and delivery bottlenecks.

Common enterprise-level challenges include:

A single enterprise CI/CD pipeline might generate thousands of new artifacts per day across multiple teams, languages, and microservices. It is necessary that these are stored, retrieved and prioritised efficiently.

Organizations rarely build in only one package format. You might need to store Docker images, Python wheels, npm packages, Java JARs, Helm charts, and even proprietary binary formats.

Distributed teams need fast, reliable artifact access no matter where they are. Build and deployment times may escalate without worldwide replication and/or CDN caching.

Enterprises in regulated industries (finance, healthcare, government) must track, verify, and audit artifacts to meet compliance standards like ISO 27001, SOC 2, HIPAA, or FedRAMP.

Malicious actors increasingly target artifact repositories to inject backdoors into the software supply chain. Without artifact signing, vulnerability scanning, and access control, these risks multiply.

An enterprise-grade artifact management platform is not just storage—it’s a secure, scalable, policy-driven system for managing the entire artifact lifecycle.

Key features to look for in an artifact management platform

When evaluating an artifact management solution, enterprises should prioritize these capabilities:

An effective artifact management solution must deliver enterprise-grade security. This includes built-in vulnerability scanning and SBOM generation, role-based access controls, and artifact signing and verification. All these characteristics combine to give end to end supply chain security to the whole pipeline.

At enterprise scale, an artifact management platform must easily adapt as new teams and projects are created. The solution of choice must be able to cope with increasing workloads without interrupting performance, and it must be able to integrate with any DevOps toolchain. This elasticity ensures artifacts remain accessible and reliable, even as organizational demands evolve.

The right artifact management platform should handle all major package formats (Docker, npm, Maven, Python, Helm, etc.) and integrate with CI/CD pipelines like GitHub Actions, GitLab CI, or Jenkins.

High availability and global distribution

Businesses cannot afford to go down. Search for multi-region replication and content delivery acceleration, which minimizes latency in geographically distributed teams.

An artifact management solution must help enterprises meet strict compliance requirements. Features like audit logs, retention policies, immutability, and automated expiry ensure artifacts remain both secure and compliant.

To improve operational efficiency, enterprise teams should consider a solution that provides storage optimization, automated cleanup, and predictable pricing models. A scalable software artifact repository prevents uncontrolled growth in costs while keeping systems clean.

How to evaluate and select the right artifact management platform

Choosing an enterprise artifact management platform isn’t just a technical decision—it’s a strategic investment that impacts cost, security, and development velocity.

Your platform should support the full spectrum of artifacts your teams produce, whether that’s containers, language-specific packages (npm, Maven, PyPI, RubyGems), or OS packages. (RPM, DEB), binaries, Helm charts, or even configuration files. Broad format support reduces tool sprawl, simplifies workflows, and prevents the overhead of maintaining multiple systems for different artifact types.

An artifact management solution should connect seamlessly with your CI/CD pipelines, version control systems, and DevOps workflows. Native integrations with tools like GitHub Actions, GitLab, Jenkins, and Kubernetes ensure artifacts move securely and automatically from build to deployment without manual intervention or fragile custom scripts.

Enterprises must ensure their artifact management platform includes vulnerability scanning, artifact signing, and audit logging. Framework compliance built in (SOC 2, HIPAA, FedRAMP, GDPR) mitigates risk and enhances 

. Using a platform that eases compliance avoids disruption during audits.

The platform must be able to scale in the case of increased workload as the number of teams and projects increases. Look for elastic scaling that accommodates thousands of developers, global teams, and massive artifact libraries without downtime. Scalability ensures that your repository grows with your enterprise, supporting continuous uploads, downloads, and artifact access without becoming a bottleneck.

Enterprises have to find an equilibrium between scalability and cost. Consider platforms based on features such as auto-cleanup, retention, and immutable storage, which lower overhead. Transparent pricing models and strong governance controls ensure your software artifact repository remains sustainable as usage scales.

Best practices for enterprise artifact management

Picking the proper platform is one half of the equation – what you do with it will determine if you’re truly benefiting from its features. These best practices will help enterprises maximise efficiency, maintain security, and keep artifact repositories healthy over time.

The security must begin as soon as possible in the software development lifecycle (SDLC).

Integrate vulnerability scanning, artifact signing, and integrity checks directly into your build pipelines.

Early security problem detection and remediation minimize the cost and the risk of shipping vulnerable software.

Once an artifact is published and tagged for release, it should never be altered.

 Make production artifacts read-only and use versioning to publish updates instead of modifying existing builds.

It guarantees that reproducibility prevents tampering and that the deployments are repeatable across environments.

Over time, unused artifacts accumulate, driving storage costs and clutter.

 Implement retention rules to automatically delete old or unused artifacts after a defined period.

it minimises the costs of infrastructure, enhances repository performance, and makes storage manageable.


Consistent naming across teams avoids confusion and makes artifacts easier to locate.

 Adopt and enforce a repository naming convention to include project names, version schemes, and branch markers.

It enhances collaboration, minimizes the issue of human error, and accelerates search and automation tasks.

For global teams, distance from the artifact source can create deployment delays.

Use a platform with multi-region replication or CDN-based caching so artifacts are served from the closest location to the consumer.

 It reduces latency, makes build and deployment much faster, and makes performance consistent across the globe.

At enterprise scale, artifact management is not just about storing files—it’s about ensuring trust, speed, and governance in every step of software delivery. In a world where software supply chain attacks are accelerating, your artifact management platform is the fortress that safeguards your software assets and the delivery engine that keeps your teams moving fast.

 is no longer just a technical decision—it’s a strategic investment in enterprise resilience, security, and scalability. By prioritising cloud-native design, robust security, and compliance, enterprises can ensure that their software artifact repository supports both current and future business goals.

1. What is an artifact management platform? 

A tool that stores, secures, versions, and distributes software artifacts like Docker images, packages, and binaries.

2. Why is artifact management important for enterprises? 

It centralizes artifacts, improves security, ensures compliance, and speeds up delivery.

3. What should I look for in an enterprise artifact management platform?

Support of multiple formats, high availability, robust security, CI/CD integration, and worldwide distribution.

4. How does artifact management improve software supply chain security? 

By scanning for vulnerabilities, enforcing signed artifacts, and keeping an immutable audit trail.

5. Can artifact management platforms be integrated with CI/CD pipelines? 

Yes, to automate artifact publishing, scanning, and promotion.

6. How does a cloud-native artifact management platform benefit global teams? 

It provides high speed, worldwide availability based on CDN publishing, and no server administration.

7. Can an artifact management platform help with compliance? 

Yes, by enforcing policies, maintaining logs, and ensuring only approved artifacts are deployed.

Choosing the Right Artifact Management Platform for Enterprise Scale

Where to host your software artifacts is one major decision in this fast-paced DevOps world, where success is pegged on scalability, security, and velocity. Organisations have stored and held binaries, packages, and container images in on-prem artifact repositories. Cloud-native artifact management is increasingly significant as cloud consumption becomes mainstream.

Then what is causing this shift? So why are teams shifting towards cloud-based systems instead of on-premise solutions? Let us simplify that.

Understanding cloud-native artifact management

Cloud-native artifact management is a contemporary approach to storing, securing, and distributing software artifacts—such as packages, container images, and binaries—using scalable, resilient, and fully managed cloud infrastructure.

What does “cloud-native” really mean?

Fundamentally, "cloud-native" is about developing and operating applications with cloud technologies in mind for speed, scalability, and automation. Rather than using physical machines or static infrastructure, cloud-native infrastructure employs dynamic environments—such as containers, microservices, and serverless functions—that can change and scale based on requirement.

For the Cloud Native Computing Foundation (CNCF), cloud-native approaches allow companies to develop and deploy software "at scale, in a programmatic and repeatable way" across public, private, or hybrid clouds. This is translated to faster releases, reduced manual touch points and a shorter development cycle.

Bringing It Together: Cloud-Native + Artifact Management

On-premises conventional artifact stores require internal infrastructure, handiwork upgrades, and specialised facilities to be ready and responsive. Cloud-native 

It is not a tool; it is a DevOps catalyst. Whether you are dealing with internal builds or open-source packages, cloud-native solutions provide more reliability and speed, and less operational worry.

What is so important in the context of the modern software supply chain?

While the software supply chain is becoming more sophisticated and security-oriented, embracing a cloud-native artifact management platform comes with several key advantages:

 Can grow and shrink on demand to take advantage of sudden demand spikes (e.g, CI/CD cycles, releases) without new hardware.

Scaling is tedious and costly since buying and setting up additional infrastructure is necessary.

Edge nodes/CDNs are distributed in the world so it uses edge nodes/CDNs to distribute artifacts in such a way that they are closer to their covers thereby reducing latency in distributed teams.

Locations are fixed on this plane of existence to the location of your physical data center and your remote teams might have slower downloads.

3. Intermediate availability & resilience

Constructed of redundant, fault-tolerant architectures that have uptime SLAs and are self-failing-over.

Can only be used with dedicated DR infrastructure and requires plans for failover, which is sometimes expensive and complicated.

The vendor is in charge of patching, scaling, back-ups, upgrades, and security monitoring.

Your team is forced to deal with maintenance, upgrades, and monitoring- distracting them off the ability to deliver software.

Common are continuous security patches, access controls, encryption and compliance certifications (SOC 2, ISO 27001, FedRAMP, and more).

Your security depends upon in-house capabilities and budget; compliance checks require manual action and are time-consuming.

6. Content with shorter innovation cycles

 Features, additional integrations, and performance updates are released automatically- no downtimes to upgrade.

There is a feature lag in on-prem, as well as upgrades that need scheduled maintenance windows.

Rather than large capital costs and idle capacity, pay-as-you-go or subscription models eliminate large capital expenses and idle capacity.

Large initial CAPEX, and continuous Overhead


In brief, cloud-native artifact management integrates the most advantageous features of DevOps, cloud computing, and security. It is highly efficient in terms of software building, storing, and delivery without the complexities associated with traditional infrastructure.

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