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MLOps Your Way with the JFrog Platform

MLOps Your Way with the JFrog Platform

Just like in traditional software development, creating AI applications isn't a one size fits all approach. However, many of the challenges and concerns facing AI/ML development teams share common threads - difficulties getting models to production, tangled infrastructure, data quality, security issues, and so on. Regardless of how you build it, to accelerate production-ready AI,…
Now Available: Evidence Collection with JFrog

Now Available: Evidence Collection with JFrog

There is an increasing need for traceability and attestation of the actions taken as software moves across the SDLC. Emerging regulations and policies around secure software development are rapidly evolving, and it’s important to stay ahead of the changing landscape. Some organizations have taken a proactive approach with home-grown solutions or manual processes, but despite…
Breaking Silos: Unifying DevOps and MLOps into a Cohesive Software Supply Chain – Part 3

Breaking Silos: Unifying DevOps and MLOps into a Cohesive Software Supply Chain – Part 3

The synergy between DevOps and MLOps is more crucial now than ever. However, merging these two paradigms into a coherent software supply chain poses a unique set of challenges that can leave teams feeling overwhelmed. From the complexities of managing model dependencies to adapting conventional CI/CD tools for advanced machine learning (ML) workflows, the path…
JFrog Cloud Native Innovation – Availability, Security Performance and Efficiency at Scale

JFrog Cloud Native Innovation – Availability, Security Performance and Efficiency at Scale

JFrog uses open source tools such as Kubernetes, Kubernetes Event-driven Autoscaling (KEDA), and Prometheus to develop its cloud development infrastructure and ensure tight integration with the three leading cloud providers AWS, GCP, and Azure. Let’s explore how JFrog cloud deployments leverage our cloud-native architecture to provide enhanced security and management capabilities for DevOps while ensuring…
Breaking Silos: Unifying DevOps and MLOps into a Cohesive Software Supply Chain – Part 2

Breaking Silos: Unifying DevOps and MLOps into a Cohesive Software Supply Chain – Part 2

In this blog series, we will explore the importance of merging DevOps best practices with MLOps to bridge this gap, enhance an enterprise's competitive edge, and improve decision-making through data-driven insights. Part one discussed the challenges of separate DevOps and MLOps pipelines and outlined a case for integration. In this second of three blogs, we’ll…
CVE-2024-6197 Curl and Libcurl: Use-after-Free on the Stack

CVE-2024-6197 Curl and Libcurl: Use-after-Free on the Stack

On July 24th 2024, Curl maintainers announced a new stack buffer Use After Free (UAF) vulnerability - CVE-2024-6197. This type of vulnerability is very uncommon since UAF issues usually occur on the heap and not on the stack. While the vulnerability can be easily exploited for causing denial of service, in this blog we will…
JFrog Cloud: Architected for Performance at Scale

JFrog Cloud: Architected for Performance at Scale

Petabytes of monthly data transfer. Thousands of concurrent requests per customer. Hundreds of thousands of requests per minute per customer. The JFrog Platform is a mission critical piece of software development and delivery infrastructure for companies that require performance at scale. When you’re supporting thousands of developers, even a minute of downtime or delay can…
Machine Learning Bug Bonanza – Exploiting ML Clients and “Safe” Model Formats

Machine Learning Bug Bonanza – Exploiting ML Clients and “Safe” Model Formats

In our previous blog post in this series we showed how the immaturity of the Machine Learning (ML) field allowed our team to discover and disclose 22 unique software vulnerabilities in ML-related projects, and we analyzed some of these vulnerabilities that allowed attackers to exploit various ML services. In this post, we will again dive…
Gain Clarity on Cloud Usage with Enhanced Monitoring from MyJFrog

Gain Clarity on Cloud Usage with Enhanced Monitoring from MyJFrog

We can all agree that visibility into resource usage is crucial for optimizing performance and managing costs to drive your business — especially in today’s cloud-driven world. MyJFrog is a comprehensive management portal for overseeing JFrog cloud platform instances and subscriptions. It provides a centralized control tower to manage and monitor subscriptions, resources, and usage.…
Feature Store Benefits: The Advantages of Feature Stores in Machine Learning Development

Feature Store Benefits: The Advantages of Feature Stores in Machine Learning Development

Feature stores are rapidly growing in popularity as organizations look to improve their machine learning productivity and operations (MLOps). With the advancements in MLOps, feature stores are becoming an essential component of the machine learning infrastructure, helping organizations to improve the performance and ability to explain their models, and accelerate the integration of new models…