Operations | Monitoring | ITSM | DevOps | Cloud

With over 50 built-in integrations, Cortex customers have an always-up-to-date, single interface for their engineering priorities, tools, and tasks. But large organizations have a lot of tools. And if you're running internally hosted tools, or for policy or security reasons would prefer to keep your access tokens private, that used to limit what was possible in your internal developer. Not anymore.

The internal DevOps team at JFrog needed to provision cloud resources, create environments, and manage infrastructure for our developers. Unfortunately, it involved wasting a significant amount of time on repetitive tasks, that was slowing down the pace of innovation and taking away our developers’ focus from building new features and industry leading products.

As artificial intelligence (AI) rapidly evolves from a research novelty to an enterprise essential, one often-overlooked component is under intense pressure: the network. AI’s hunger for data and real-time performance is forcing enterprises, cloud providers, and data center operators to rethink how they interconnect data centers. Enter Managed Optical Fiber Networks (MOFN) — a modern solution for modern DCI challenges.

Deploy full-stack environments for every PR in under 10 minutes If you’re using GitHub, GitLab, Bitbucket or Azure DevOps and want to streamline your development workflow, this post is for you. Imagine this: every time a developer opens a pull request, a full environment spins up automatically — frontend, backend, database, services — the whole stack. It’s deployed in your cloud, seeded with test data, and ready for QA, product, or design to review.

Especially when AI is writing more and more of your code Let’s be honest: developers don’t test enough. You see it every week — a feature is merged, staging breaks, and the bug was something obvious: a missing dependency, an incorrect flag, a minor logic error that could’ve been caught earlier. With AI tools like GitHub Copilot, Cursor, and Windsurf writing code faster than ever, this problem is only growing. The code output is higher — but the validation often isn’t.

And why ephemeral preview environments are your best defense AI-powered code assistants like GitHub Copilot, Cursor, and Windsurf are revolutionizing how we build software. Developers are moving faster than ever — scaffolding features, generating functions, and completing workflows in seconds. But here’s the catch: AI code looks right. Until it’s not. It compiles. It passes linting. It even makes it through some basic tests. But when merged?

For startups that need fast, flexible, and realistic environments If you're a startup moving off Heroku in 2025, you’re not alone. What once felt like magic — git push, instant deploy, no infrastructure to manage — now feels expensive, restrictive, and increasingly disconnected from how modern teams work.

…and why it matters even more in the age of AI-generated code Software development is changing fast. Thanks to tools like GitHub Copilot, Cursor, and Windsurf, developers can now generate large chunks of code in seconds. Product velocity is exploding. Startups are shipping faster than ever before. But there’s a catch: More code ≠ better code.