JFrog Reviews & Product Details

I primarily use JFrog Artifactory as a centralized repository manager to handle the lifecycle of my software packages, and it effectively eliminates the friction that slows down a high-stakes development cycle. I love how it serves as the ultimate safety net and speed booster for our entire software supply chain. Thinking of JFrog as a 'safety net' and 'speed booster' isn't just marketing—it literally describes the difference between a smooth release and a weekend spent fixing a broken production environment. It's particularly beneficial when juggling the responsibilities of a Senior Full Stack Developer in a fast-paced environment. JFrog acts as the 'connective tissue' that links my code to my infrastructure, and its key integrations keep my workflow moving smoothly. Review collected by and hosted on G2.com.

While I’m a big advocate for JFrog, being a Senior Java Full Stack Developer means I also have to deal with its 'rougher' edges. No tool is perfect, especially one that tries to do as much as the JFrog platform. Based on my experience as a Senior Java Full Stack Developer, there are several technical and workflow-specific areas where I’d like to see JFrog push further. While it’s the backbone of our supply chain here in Seattle, these improvements would significantly reduce the daily 'to-do' list for a senior dev. Review collected by and hosted on G2.com.

Building on our existing use of JFrog for artifact management and CI/CD, several newer capabilities stand out:

AI Model Governance is a big one. JFrog AI Catalog lets teams identify and access AI models approved for use within their org, with governance controls over AI added to applications JFrog — essential as AI adoption accelerates across teams.

Shadow AI Detection adds visibility we didn't have before. It gives enterprises control over unmanaged AI models and API usage, guarding against security and compliance risks from uncontrolled AI adoption. JFrog

Auto-remediation is a real time-saver. JFrog can now automatically replace risky packages with approved compliant versions JFrog, reducing manual triage significantly.

Proven ROI makes the investment easy to justify. A Forrester study found the platform delivered 282% ROI and saved 38 hours per developer on onboarding. Review collected by and hosted on G2.com.

Beyond the earlier feedback on complexity and pricing, a few additional areas stand out:

UI Cohesion — As JFrog adds products like AppTrust, AI Catalog, and Advanced Security, the experience between modules still feels disjointed. A more unified interface would help daily usability.

Pricing Transparency — It's not always clear which newer features are included in existing plans versus requiring upgrades, making budgeting harder for smaller teams.

Documentation for Advanced Use Cases — Complex setups like multi-repo configurations or custom SBOM workflows often require piecing together answers from community forums rather than official docs.

Uptrust Timeline — JFrog's supply chain trust product isn't expected until September 2026 Investing.com, leaving a gap for teams who need those capabilities now. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

I dislike the false positives and high entry fee. The configuration setup was a bit of a maze. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

I like JFrog because it is very user-friendly and easy to use. I can integrate it with CI/CD, which is super useful, and the initial setup was quite easy. Although it requires understanding the process at the beginning, everything is all good now. My team switched from AWS for something that feels more like an upgrade, easier to use, and aesthetically pleasing. Review collected by and hosted on G2.com.

Maybe the setup could be a bit easier. Just a lot of going back and forth and can be a bit exhaustive. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

JFrog is one of the best tool we have come across for ML model build and deployment from end to end. It also provides central model repository to store artifacts and all other related data. It is very easy to implement and very easy to use. Review collected by and hosted on G2.com.

JFrog has all the required features for ML model build and deployment so I don't think it has any dislike from my end. Review collected by and hosted on G2.com.

1. The unification of all the requirements for a DevOps team

2. Ability to support various out-of-the-box registry support Review collected by and hosted on G2.com.

1. It is difficult to get started and understand how to use CLI from your local environment to the cloud

2. Cloud Pro account requires business email but logging in from Github works with personal account (perplexing access policies)

3. JFrog CLI is separately downloadable and configurable, the use of which remains a big mystery since we can use cURL to do pretty much everything in Artifacts (again perplexing strategy)

4. Setting multiple Repositories is required for simple task of pulling packages from public registries Review collected by and hosted on G2.com.

1. Provides end-to-end automation by integrating with Kubernetes, Helm, Terraform, and other DevOps tools.

2. Supports hybrid cloud environments and is offered as SaaS or on-premises.

3. Easily integrates with Jenkins, GitHub Actions, and other CI/CD tools to manage artifacts.

4. Stores build artifacts in a centralized, versioned including Docker images.

5. Supports a variety of package formats Maven, Gradle, and npm.

6. Serves as a private Docker registry for safely managing and storing container images. Review collected by and hosted on G2.com.

1. High Time taking for integration for the first time.

2. Comparatively high cost with other of same type

3. Customer support delays sometimes Review collected by and hosted on G2.com.

JFrog Xray have not seen that in actio i nother dev ops softwares Review collected by and hosted on G2.com.

not a lot of people know about it, it should have more reach Review collected by and hosted on G2.com.