Code, deploy, repeat. As a developer, your days are a whirlwind of Git commits, pull requests, and CI/CD pipelines. In the rush to ship new features and hit those sprint goals, it's easy to overlook the less glamorous aspects of software maintenance. But one often-neglected practice could be the difference between a stable, secure system and a compromised system. Enter patch management, a key DevOps tool in your arsenal to safeguard your systems.

I was recently cruising LinkedIn and saw Abi Noda from GetDX reference a paper Meta wrote in 2022 on improving code review time. Meta’s focus on this metric was sparked by a developer survey, but what they did as a result is even more interesting (at least to me!). Meta developed a “NudgeBot” to alert reviewers to take action on stale diffs. And it worked; both time to review and time in review went down.

Measuring progress in software development is hard. Our industry is defined by complexity, entropy, shifting deadlines and priorities, and customer expectations that evolve almost as quickly as the technology that we use every day. The nature of this environment means that we need to apply continuous feedback loops, robust frameworks and structured approaches to do good work.

As a CIO or IT leader, the need for speed and efficiency is always in tension with governance and compliance requirements. Sounds all too familiar – the frustration of slow incident resolution, outdated ownership records and resistance from engineering teams. You’ve sunk significant time and effort into implementing your ITSM platforms (such as ServiceNow), yet you struggle with buy-in and adoption from engineering teams. They can’t afford to be throttled any further.

We all understand the significance of DevOps, defined here as the set of practices and processes that integrate software development and operations. By bridging the gap between traditionally siloed teams, DevOps accelerates software delivery processes, ensuring faster time-to-market for new features and updates. As you would expect at the intersection of software and operations, automation plays a central role.

‍ ‍ Most migration/modernization/transformation—whatever you want to call these initiatives—are a pain. "Have you done x yet?" isn't something anyone wants to have to say or hear, 10x a month. But there hasn't always been a great way to drive coordinated progress on these projects—against a real deadline. Stand-ups are a productivity killer, emails go straight into the ether, and project management software is manual and self-reported.

TLDR: We raised $60M in new funding, led by Scale Venture Partners, with participation from World Innovation Labs, Cross Creek, Alpha Square Group, Patrick and John Collison (Stripe) IVP, Sequoia, and Y Combinator. With this new infusion of capital, we’re looking to further grow developer awareness around IDPs and invest in our platform capabilities with enhanced workflows, engineering intelligence, user interface, and of course, AI.

Platform engineers have become a critical role in modern software development, creating and maintaining the foundational infrastructure that supports software development and deployment. Unsurprisingly, platform engineers face a wide range of challenges, from creating robust continuous integration and delivery (CI/CD) pipelines to keeping complex cloud infrastructure up and running. To effectively address these challenges, a platform engineer needs the right set of tools.

Release management is critical in software development, guiding how new features, updates, and bug fixes move from development teams through various stages of testing and deployment into production. In a DevOps framework, release management isn’t just about deploying code—it’s about ensuring reliable, timely, and stable software releases that meet business goals and satisfy end-users.

According to the 2024 State of Production Readiness report, 54% of engineering leaders said poor production readiness standards contributed to a decrease in developer productivity. But how? If software falls out of alignment with best practice—including those designed to maintain the health, observability, and security of software—developers wind up spending more time finding information and fixing issues than building new value.