Operations | Monitoring | ITSM | DevOps | Cloud

Data centers are energy-intensive, and with the surge in AI-driven workloads, their global energy consumption is projected to more than double by 2030, potentially surpassing the current electricity consumption of Japan. For most data center operators, energy is one of their largest recurring expenses. As demand for data center capacity continues to grow and energy prices fluctuate, energy efficiency is no longer just a sustainability goal, it's a core business concern.

Earlier this year, I spent a few weeks in India, visiting universities, speaking at meetups, and catching up with founders. What stood out wasn’t just the excitement about AI, but the focus on what it can actually do today. The curiosity about GenAI and big-picture questions around AGI is there, but most conversations centered around real needs: learning faster, applying for jobs, and getting healthier.

One of the most critical gaps in traditional Large Language Models (LLMs) is that they rely on static knowledge already contained within them. Basically, they might be very good at understanding and responding to prompts, but they often fall short in providing current or highly specific information. This is where RAG comes in; RAG addresses these critical gaps in traditional LLMs by incorporating current and new information that serves as a reliable source of truth for these models.

If you've ever received a call that looked like it was from your bank or, worse, a family member, but turned out to be a scam, you're not alone. These spoofed calls continue to be a huge headache, not just for everyday people but for businesses, phone carriers, and regulators too. The good news? The FCC is stepping up again. Last week, the Federal Communications Commission released a new Notice of Proposed Rulemaking (NPRM) to close a serious gap in our defense against robocalls: non-IP networks.

As Software as a Service (SaaS) solutions evolve, organizations face increasing pressure to ensure uninterrupted service delivery. One of the most significant threats to SaaS Service delivery and operational continuity is the presence of known and unknown Single Points of Failure (SPOFs). As a SaaS organization, the team at JFrog deeply understands the risks of SPOFs and works hard to avoid them.

As organizations increasingly deploy AI solutions, I am seeing more and more that the strategic placement of data—particularly at the edge—is becoming paramount to unlocking AI’s full potential. This is a viewed shared by our partners at Riverbed, as highlighted in a recent white paper, Accelerating AI and Data Movement at the Edge. Edge computing enables businesses to perform complex operations at production sites by positioning compute resources nearer to users and operations.

With more enterprises adopting SD-WAN technology, SD-WAN vendor support can be a key to success. We break down the licensing of eight major SD-WAN vendors. Whichever SD-WAN vendor you use, the way you deploy is essential to success.