#devops

#devops

JFrog (NASDAQ: FROG) stunned investors with a blowout third quarter that sent shares soaring more than 24%. The DevOps platform provider not only delivered its eighth straight beat on both revenue and earnings but also showcased accelerating cloud adoption, record profitability, and a growing foothold in AI-driven software delivery. Here are three key takeaways from the results and management's commentary.

The query builder solves a large SQL bottleneck by transforming log analysis from a time-consuming task into a real-time, self-service capability that's fit for any DevOps or site reliability professional. This is an immense time-saver that can collapse typical investigation windows from hours to minutes,

We are a Berlin company with international employees working on decentral collaborative AI services in real estate. We change how people live and work, by making buildings think and act adaptive to occupant needs. It is not another App. We save highest possible energy and run AI in compliance with GDPR. We look for developers who know AI on edge as well as power of Edge&Cloud.

"Bringing DevOps Principles to Controls and Audits", not the most exciting title in the world, but I'm actually going to be talking about a revolution. What I'm talking about is an open-source project that me and my colleagues at Container Solutions are working on. My goal is that by the end of it, you'll be interested enough to check it out, perhaps give feedback, maybe even get involved.

With the new refactor feature, the company addresses a significant pain point: previously, any change to a resource's logical ID caused by renaming or moving a construct would force AWS CloudFormation to delete and then recreate the resource. This destructive process often led to data loss and downtime for stateful resources, such as databases, causing many developers to avoid refactoring altogether.

Designed to be integrated with continuous integration/continuous deployment (CI/CD) platforms such as Jenkins and others, the Zencoder AI agent can resolve issues, implement fixes, improve code quality, generate and run tests, and create documentation. As such, the goal is not just to write more code faster, but rather enable DevOps teams to take advantage of AI agents running in the background to re-engineer workflows in ways that result in more applications being deployed faster, said Filev.

For years,mainframes were synonymous with stability, but rarely with innovation. That image seems to be changing rapidly. New figures from BMC's annual mainframe survey show that confidence in the future of the platform has never been higher. No less than 97 percent of the professionals surveyed indicate that mainframes will remain part of their IT infrastructure. Increasingly, the system is even seen as a driver for new workloads.

System Initiative recently released its AI Native Infrastructure Automation platform, aiming to offer DevOps teams a new way to manage infrastructure through natural language. With this release, users can type simple prompts, such as "make load balancer health checks more aggressive", and the system's AI agent will discover relevant infrastructure, simulate proposed changes, and execute updates upon approval. System Initiative claims all of this will occur while maintaining full automation and safety within live environments.

Innovation simply can't wait. Not today, when rapid evolution and change are the baseline, the table stakes.

Vibe coding is AI-powered, collaborative code creation, where the "vibe" - the team's culture, coding style and collaborative preferences - is harnessed as an operational parameter. Imagine pairing human strengths with advanced generative AI, capturing not just code syntax and logic, but the subtle preferences, patterns and conventions that make YOUR team effective. This isn't about getting AI to write a few snippets. It's about the AI learning your team's DNA.

Fresh off raising $7.2 million in funding, SRE.ai CEO Raj Kadiyala said as the volume of code developed using low-code/no-code and, more recently, artificial intelligence (AI) tools increases, there needs to be a more automated approach to deploying that software based on best DevOps processes that also enables software development teams to monitor and observe those applications. At the core of that effort is a platform that will leverage artificial intelligence (AI) technologies to automate the deployment

The Org Intelligence module added to the Copado AI Platform leverages metadata exposed on the Salesforce platform to extrapolate relationships, promising an 80% reduction in discovery time.

A stack-based approach to IDPs emphasizes reusability, autonomy, and visibility, creating a standardized but flexible system where teams can define and deploy their own devops stack.

Blazor's rise aligns with transformative shifts in the DevOps landscape, particularly with AI and ML integration, which enhances DevOps processes and app performance.

Sustainable optimization starts when leaders reframe the conversation: From seeing costs as an external burden imposed by finance to recognizing them as an integral signal of engineering health.

"While the tech landscape has changed, the way we think about building automation has not," says Adam Jacob, CEO and co-founder at System Initiative. "It's had an incredible run, but we've taken that idea as far as it can go."