News & Events

Syslog has been the backbone of infrastructure logging for decades. Network devices, operating systems, firewalls, and applications rely on it to send operational data.

Organizations deploying GPU infrastructure for AI training and inference are facing a new set of networking challenges. Unlike traditional enterprise applications, AI workloads generate unique traffic patterns, including large-scale data ingestion before training, high-bandwidth model checkpoint transfers to distributed storage, continuous inference requests from thousands of users, and ongoing management traffic that crosses cluster boundaries.

A recent incident involving a famous singer has left fans shocked and served as a powerful reminder to industry professionals about the vulnerability of sensitive data—even at the highest levels of production. Known for maintaining strict secrecy around upcoming releases, the artist now faces a serious risk of leaks after unreleased music was stolen.

Deploying hardware security keys like YubiKeys is one of the most effective ways to prevent phishing and credential-based attacks. Yet for many IT teams, the initial promise of stronger, phishing-resistant security is often offset by the operational burden that comes with managing these devices at scale.

Every data architect knows the struggle. Data modeling often begins with a blank canvas, vague requirements and countless hours spent translating business concepts into structured models for each new project. Meanwhile, your team is under constant pressure to deliver production-ready models faster than ever — yet manual processes continue to slow everything down.

Threat actors are leveraging fake meeting invitations for Zoom, Microsoft Teams, Google Meet, and other video conferencing platforms to trick users into installing remote monitoring and management (RMM) tools, according to researchers at Netskope.

As we move into 2026, I’ve been reflecting on where authentication and digital identity are heading. The past year brought meaningful progress: passkeys gained real traction, government-backed digital ID programs launched across multiple regions, and AI agents began reshaping how we think about machine-to-machine trust. In 2026, these trends won’t just continue — they’ll accelerate and fundamentally influence how we design authentication systems.

If you’ve been keeping an eye on the latest conversations coming out of Silicon Valley and the broader AI community, you’ve probably noticed a growing trend: developers are buying Mac Mini units to run local AI agents such as the project formerly known as Clawdbot—now rebranded as Moltbot.

As organizations grow, their IT infrastructures often become fragmented — especially when merging with other companies, onboarding new business units, or managing separate identity systems across departments. This fragmentation can make identity and access management (IAM) inefficient, risky, and difficult to administer. RCDevs introduces OneIAM, a flexible approach that simplifies and centralizes IAM across diverse systems without forcing a full migration into a single platform.