Making LLMs Observable : AI, OpenTelemetry and Rise of MCP
Making LLMs Observable : AI, OpenTelemetry and Rise of MCP.
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Coralogix becomes first observability vendor to earn ISO/IEC 42001:2023 certification for responsible AI
We’re proud to announce that Coralogix is now officially ISO/IEC 42001:2023 certified, becoming the first observability vendor to achieve this globally recognized standard for responsible AI management. ISO/IEC 42001:2023 is the world’s first international standard for Artificial Intelligence Management Systems (AIMS). It provides a comprehensive framework for how organizations should govern AI, focusing on transparency, ethical use, accountability, and regulatory compliance.
AI in IT: Great! Now What the Hell Do You Do with It?
The demand for organizations to minimize downtime, swiftly address issues, and proactively manage the infrastructure has never been greater. But how can teams be expected to meet that challenge with legacy tools and approaches? Enter Zero Ticket IT, a transformative approach where AI-driven automation eliminates traditional ticket bottlenecks, empowering IT teams to focus on innovation and strategy. But how do you know if your team is truly ready for this transformative leap?
Leaning into AI, ML, and observability to manage your ever-growing infrastructure
The complexity and scale of modern infrastructure requires an equally intelligent set of observability tools to effectively monitor it. Remember when scaling meant ordering new servers and racking them in a data center? Remember when cloud providers first offered access to seemingly infinite virtual machines at the click of a button? Remember when Kubernetes made it trivial for infrastructure to automatically scale itself based on demand?
We built an MCP server so Claude can access your incidents
"Show me all critical incidents from the last week." "Create an incident for the payment API being down." "What was the root cause of that database incident last Tuesday?" If you've ever wished you could just ask Claude (or any MCP client) to handle incident management tasks instead of context-switching between chat and your incident management dashboard, you're going to like what we built.
The Role of AI in Next-Gen Fleet Telematics Systems
Artificial intelligence (AI) is really making fleet telematics way smarter. Right now, telematics uses things like GPS and other sensors to keep tabs on vehicles. But AI takes all that information and actually thinks like a human brain, just way faster. It's awesome at finding patterns, guessing when problems might pop up, and even suggesting how to fix them. For businesses with vehicles, this means they can make better choices without just guessing. AI is completely changing how managers handle their trucks or vans, which saves both time and money.
Vibe Coded Software Cybersecurity Risks and How To Respond
Generative AI has enabled anyone in any company to become a software creator, thereby creating a new generation of vibe-coded cybersecurity risks. The rise of "vibe coding" (building applications on the fly by describing what's needed in natural language) has introduced an entirely new class of security blind spots when these tools plug into your systems or are installed in your environment. Here's what vibe coding cybersecurity risks look like in your environment and what you need to do to stop them.
AI Agent Is Hitting Your APIs - Are You Ready?
It’s no longer theoretical – artificial intelligence has left research labs and entered production systems, generating a new breed of consumers – autonomous and intelligent agents. These autonomous AI agents are increasingly interacting with real-world APIs (application programming interfaces), which are sets of protocols and tools for building and integrating software applications.
Building your AI infra, our tips
Modular architecture: Decouple compute from storage so each can scale independently. This makes it easier to adapt to growing or shifting workloads over time. Future-ready hardware: Select GPUs and CPUs not just for current workloads but with an eye on scalability, including support for newer accelerator types. Scalable design: Ensure the system allows seamless addition of compute nodes or storage without a full redesign.
Running AI without blowing up your storage
Storage is often underestimated: In infrastructure discussions, compute and networking get most of the attention, while storage is treated as secondary. For AI workloads, that can be a costly oversight. Data throughput for specialized hardware: AI infrastructure powered by GPUs can process massive volumes of data at unprecedented speeds. This puts immense pressure on the storage system to keep up. Scale-out performance: An on-prem, scale-out, software-defined storage setup allows you to meet high performance demands, grow capacity as needed, and stay in control of infrastructure costs.