JFrog Software Supply Chain Platform

What do you like best about the product?

I use JFrog mainly as an artifactory for Docker images and npm packages. I love its universal package management, and my favorite feature is virtual repositories, which provide my team with a single URL for all our dependencies. I really appreciate how well JFrog integrates with the rest of our 2026 stack, especially GitHub Copilot. JFrog's curation is excellent for blocking malicious zero-day packages before they can even hit our local cache. Using the JFrog app for GitHub, I can link my source code directly to the final binary, making traceability automatic. The 2026 stack integration allows me to see security alerts directly in my IDE, so I don't have to switch to a dashboard. Lastly, the technical setup through Docker was a breeze.

What do you dislike about the product?

I dislike the false positives and high entry fee. The configuration setup was a bit of a maze.

What problems is the product solving and how is that benefiting you?

I use JFrog to prevent outages by caching dependencies and solving 'worked on my machine' issues with binary linking to commits. It integrates well with my stack, blocks malicious packages, and streamlines dependency management with virtual repositories.

What do you like best about the product?

I like how JFrog simplifies and secures the entire software delivery process. The platform brings together artifact management and security scanning and I appreciate how strongly it focuses on DevOps and automations. Having a single trusted source of dependencies removes a lot of friction instead of pulling packages from multiple external repositories, and the security scanning features add another layer of confidence.

What do you dislike about the product?

I don't like the complexity of setup and configuration, especially for large DevOps teams. Clearer onboarding and documentation for new users would really help since it took some time to figure out the initial configuration.

What problems is the product solving and how is that benefiting you?

I use JFrog to streamline the development and integration process. It simplifies and secures our software delivery, managing artifacts and conducting security scans, providing a single trusted source of dependencies and reducing friction by avoiding multiple external repositories.

What do you like best about the product?

I like using JFrog for packaging projects because it helps ensure environment consistency, especially with Docker. This makes deploying my projects easy and professional. I also use it for automations.

What do you dislike about the product?

I find the complexity and learning curve challenging. It would be great if pre-configured templates were available. The initial setup was manageable but not plug and play.

What problems is the product solving and how is that benefiting you?

JFrog helps me package projects, making deployment easy and professional. It ensures environment consistency.

My main use case for JFrog Artifactory  is to store Docker  images and other build artifacts from our Java applications.

In our workflow, JFrog Artifactory  acts as a centralized repository where we push all our artifacts, and being a SaaS company, we have a lot of releases happening very frequently. We also have a Kubernetes  cluster where we run our worker nodes. As we release something, we ensure that it is stored and sent to the proper repository, in this case JFrog Artifactory, from where Kubernetes  will pull and deploy those images.

The best features JFrog Artifactory offers include JQL, which is very helpful for finding particular artifacts that are older or identifying items that need to be cleaned up. We also appreciate the caching mechanism that allows us to cache images in different locations in our AWS  infrastructure, ensuring that we do not always have to go to a central location but can fetch those artifacts from a nearby cached location.

JFrog Artifactory caching has improved our deployment speed and cost. In AWS , pulling an image from a cross-location incurs charges, and we run many jobs on an event basis, necessitating frequent image pulls from JFrog Artifactory. Since we operate in the same location, we end up paying less to our cloud provider by reducing the total network cross AZ network usage.

For usability, JQL is valuable, as it allows us to fetch particular artifacts and do cleanup efficiently.

JFrog Artifactory has positively impacted my organization, especially in terms of cost savings. We used to have a centralized repository, but with JFrog Artifactory, we can cache artifacts in different locations close to our production and development servers, significantly reducing costs.

Although JQL is a great tool, I have noticed that JQL queries can be hard to learn. A more user-friendly query language or improved UI would be beneficial, as the current UI requires deep technical knowledge for effective use.

I have been using JFrog Artifactory for three years.

JFrog Artifactory has been stable in my experience.

JFrog Artifactory is definitely highly scalable. When we deploy in serverless environments, especially ECS, JFrog Artifactory scales effectively to handle a lot of requests for serving images.

I have not interacted with their support team, so I cannot comment on customer support.

We initially used Amazon ECR , but it did not work well for us when scaling, which led us to switch to JFrog Artifactory, especially for multi-cloud stability.

I purchased JFrog Artifactory through the AWS Marketplace .

Although JFrog Artifactory is slightly high-priced, we are willing to pay for it because it is a critical part of our technology operations and DevOps processes. While there are free tools available, we find it worth the investment.

I evaluated ECR from Amazon before choosing JFrog Artifactory.

JFrog Artifactory still has room for improvement, particularly with the user interface and documentation. However, JFrog Artifactory has helped us scale faster and is a highly available, robust artifact repository that boosts our confidence in production.

My advice for others considering JFrog Artifactory is to start with free tools available in the market. If you encounter bottlenecks while scaling, that is when you may need a dedicated tool like JFrog Artifactory. Larger companies will need a robust artifactory to ensure their production does not struggle.

My company does not have any business relationship with JFrog Artifactory other than being a customer. I rate JFrog Artifactory a nine out of ten.

Public Cloud

Amazon Web Services (AWS)

JFrog Artifactory  serves as our main tool for managing and distributing software artifacts across our deployment pipelines. We use it primarily for storing, versioning, and securely sharing binaries, Docker  images, and dependencies across multiple client environments, ensuring consistent builds and faster release cycles.

In a recent project, we used JFrog Artifactory  to manage Docker  images and dependencies for a multi-service application deployment across several client environments. By pulling versioned artifacts directly from JFrog Artifactory, we ensure consistent builds, faster deployments, and reduced errors, which helped the team deliver updates reliably across both cloud and on-premises systems.

We also use JFrog Artifactory for dependency management and release promotion, moving artifacts from deployment to QA to production in a controlled, versioned way. This streamlines CI pipelines, ensures traceability, and reduces deployment errors across multiple clients.

The best features JFrog Artifactory offers are the universal artifact repository, versioning and immutability, secure access control and permissions, Docker and Helm registry support, artifact promotion workflows, high availability, and scalability.

The universal artifact repository in JFrog Artifactory lets us store and manage all types of artifacts, Docker images, binaries, and dependencies in one place, which simplifies CI/CD pipelines across multiple client environments. Secure access control ensures only authorized users and CI/CD jobs can access or deploy artifacts, reducing the risk of accidental overwrites or unauthorized deployments. For example, during a recent multi-client release, this setup ensured consistent builds and prevented deployment errors, even across different cloud and on-premises environments.

JFrog Artifactory has streamlined our build and deployment process across multiple clients and environments. We have seen faster, more reliable releases, reduced build errors, and improved JFrog Artifactory traceability, which helps with auditing and compliance. Overall, it has saved time in CI/CD pipelines and ensured consistency across cloud and on-premises deployments.

JFrog Artifactory could be improved with a more intuitive user interface and faster search capabilities, especially when managing large multi-client repositories. Setup and configuration for multi-tenant environments can be complex, and better out-of-the-box monitoring and alerting features would help reduce operational work overhead.

Faster replication for global deployments and more native integration with security scanning tools would be helpful.

I have been using JFrog Artifactory for three years.

JFrog Artifactory is stable.

JFrog Artifactory is scalable from small and medium enterprises to larger enterprises and very large enterprises.

My overall experience with JFrog Artifactory's customer support has been good for standard issues with reasonable quick responses and helpful guidance. However, when there are complex or multi-cloud deployment issues, resolution sometimes takes a longer time.

Positive

Previously, we used a combination of local artifact repository and manual versioning, which was prone to errors and inconsistent builds. We switched to JFrog Artifactory because it provides centralized artifact management, version control, CI/CD integration, and better reliability across multi-client environments.

The initial setup was good, but it took a lot of time to complete.

We have clearly seen a return on investment with JFrog Artifactory. Due to its centralized artifact management, which has reduced build and deployment times by twenty percent, prevented multiple rollback incidents, and freed our team from manually managing dependencies, saving several hours per week. For example, during a recent multi-service deployment across several client environments, consistent artifact versioning eliminated five potential errors, ensuring a smooth and reliable release.

JFrog Artifactory pricing and licensing are enterprise-level, which means it is relatively costly, especially for high availability and replication across regions.

We evaluated other options such as GitHub  Packages and Nexus Repository Manager . We chose JFrog Artifactory because it offered the broadest universal artifact support and better scalability for multiple client hybrid cloud environments.

I would rate JFrog Artifactory nine out of ten.

I chose nine out of ten because JFrog Artifactory greatly improved build consistency, CI/CD efficiency, and artifact traceability, which are critical across multiple client environments. I did not give it a perfect score of ten due to the user interface complexity, slower search in large repositories, and some setup challenges for multi-tenant deployments, which could be improved.

JFrog Artifactory should provide better documentation for advanced multi-client and multi-cloud setups, which would also reduce time and troubleshooting effort.

I would recommend that you plan your repository structure, take advantage of versioning and artifact promotion, and access control to ensure consistent builds and secure releases. Also, prepare for initial setup effort in multi-client or multi-cloud environments to maximize efficiency and reliability.

Public Cloud

Amazon Web Services  (AWS )