Karios AI-native hyperconverged infrastructure for datacenters

Ever wondered why message brokers are the backbone of scalable, fault-tolerant Industrial IoT architectures? Message brokers enable seamless asynchronous communication by decoupling systems—allowing data to flow reliably across distributed environments without bottlenecks. Here’s how they elevate your operations: ✨ System Decoupling — Senders don’t need to know who consumes their messages, simplifying integration. ✨ Parallel Processing — Multiple consumers process data simultaneously to maximize throughput. ✨ Load Balancing — Prevent downstream services from being overwhelmed during traffic spikes. ✨ Reliability & Recovery — Brokers ensure no messages are lost, maintaining delivery even through failures. At IoT83, we leverage message-driven architecture to streamline large-scale data orchestration—helping enterprises build systems that are fast, resilient, and truly scalable from edge to cloud. 🔗 Discover how we enable smarter Industrial IoT: https://lnkd.in/geMTACEN #IoT83 #Flex83 #AIoT #DataOrchestration #MessageBrokers #EventDrivenArchitecture #DigitalTransformation #ScalableSystems #EdgeToCloud

Disaggregated storage architectures. Evolving data sovereignty requirements. Explosive growth of data from AI, video, IoT and research workloads. These data demands of tomorrow require systems designed for scalable growth. And Seagate continues to meet that opportunity. Today, Seagate unveiled a next-generation, enterprise storage system engineered for tomorrow’s data center challenges. This flagship petabyte-scale storage system empowers enterprises to consolidate data, boost efficiency, and scale to meet evolving infrastructure demands. Learn more about the most complete high-density single enclosure on the market here: https://lnkd.in/e4zgvMqF

IoT → Private 5G → Edge AI → Data Centers. We’re watching a classic “systems flywheel” play out: Instrument everything: IoT hit ~18.8B devices in 2024, data volume and velocity keep rising. Localize decisions: Enterprises deploy private LTE/5G + edge AI for real-time ops (vision, robotics, safety), then sync to cloud for fleet-wide learning + storage. Scale the core: Cloud infrastructure spend reached ~$99B in Q2’25 (+~25% YoY); capacity under construction across NA primary markets remains>5 GW. Power is the constraint: IEA projects DC electricity use could ~double to ~945 TWh by 2030, placing a premium on grid access, efficiency, and clean power. Bottom line: IoT and private networks don’t just digitize operations—they shift where compute happens. Edge handles the instant decisions; core data centers handle the learning loops, archives, and scale. This is why power, land, and interconnects are the new strategic battlegrounds. #IoT #Private5G #EdgeAI #EdgeComputing #DataCenters #AIInfrastructure #Cloud #IndustrialIoT #WirelessInfrastructure #DigitalTransformation

Edge computing brings processing closer to where data is generated, starting from devices at the edge and moving through gateways and local datacenters before reaching the cloud, reducing latency and enabling faster, context-aware responses. This architectural vision reflects how enterprises can manage the growing pressure of real-time applications. Data generated at the edge continues to expand rapidly, with billions of IoT devices producing information that needs to be processed efficiently. Placing computing capacity near the source ensures immediate insights, greater reliability, and less dependence on centralized infrastructure. Such a design is not only technical but also strategic. It transforms how organizations think about data flows, security, and resilience. Local processing reduces vulnerabilities and helps achieve compliance with regional regulations. At the same time, integration with the cloud preserves scalability and advanced analytics. In my view, edge computing will become a foundation for sectors that demand instant reaction, from healthcare monitoring to autonomous systems and industrial automation. The real challenge is to create a balance where edge and cloud complement each other with efficiency and coherence. #EdgeComputing #CloudComputing #IoT #DigitalTransformation

Excited to share that AiRISTA is partnering with Cisco for an upcoming webinar on how Real-Time Location Systems (RTLS) are transforming operations across industries. We’ll explore how organizations are using RTLS to improve efficiency, safety, and visibility — and how integrating with Cisco networking makes these solutions even more scalable and secure. If you’re curious about how RTLS can create smarter, more connected environments in healthcare, manufacturing, or logistics — this is one you won’t want to miss! See original post below to register.

Smart Data Routing = Smarter Businesses Cavli Hubble™ ensures your large-scale IoT ecosystem runs faster, safer, and smarter. With the Hubble Messaging Service, data doesn’t just move; it flows intelligently across cloud platforms and hyperscalers while providing real-time insights. ⚡Multi-Endpoint Delivery  Transmit data to custom destinations. All at once, for instant analytics and visibility. 🛡️ Zero Data-Loss Guarantee  Built-in persistence and fail-safe delivery ensure every byte reaches its destination, no drops, no downtime.  ⚙️ Dynamic Configuration  Add or modify endpoints on the fly, with no device redeployment and no interruption.  🔒 Secure, Scoped Access  Every device is verified for identity and compliance before communication, keeping your data trusted and safe. 🌐 Explore Cavli Hubble: https://lnkd.in/g-PhRK9N #IoT #CavliHubble #DataFlow #SeamlessIntegration #DataSecurity #DataManagement #CloudSolutions #Cavli

Cloud & Edge: The Hybrid Backbone of Tomorrow’s Tech We’re entering the age where hybrid computing isn’t optional—it’s essential. Cloud services gave us scalability, global reach, and cost-efficiency. Edge computing brings data processing closer to the device: low latency, real-time decisions, and smarter workflows. Imagine a system where: Your company’s data backbone is in the cloud—powerful servers, big data analysis, global access. At the same time, your on-site sensors, IoT devices and remote offices do real-time processing at the edge. The two systems talk seamlessly, enabling both agility and scalability. This fusion means faster insights, better resilience (even during connectivity issues), and more efficient bandwidth use. If you’re still thinking “cloud or edge,” it’s time to shift thinking to “cloud and edge.” 🔍 Question for you: How is your org leveraging or planning to leverage this hybrid model? Drop your approach, challenge or vision in the comments! #CloudComputing #EdgeComputing #TechTrends #DigitalTransformation #HybridCloud #IoT #FutureOfWork

Edge data centres promise low-latency compute close to users. Yet many organizations still struggle with hardware that survives wide temperature swings, guarantees 24/7 uptime and secures every boot at remote sites. Are your micro-DC servers built for true industrial lifecycles and hassle-free firmware updates? What about TPM-based security and IPMI remote management—features often overlooked until downtime strikes? With evolving AI/ML inference loads and ever-changing IoT protocols, trial-and-error edge deployments waste time and budget. Before your next roll-out, pause and ask: does your edge strategy include long-term board availability, ECC memory reliability and flexible COM modules tailored to carrier-grade performance? If you’re second-guessing your answers, it may be time to consult an expert. Sigma Data Centres designs resilient, secure edge infrastructures that tick every reliability box—freeing your team to focus on core innovation, not hardware headaches. Reach out today to explore how custom edge data-centre design can safeguard your remote compute investments. #DataCenters #DataCentres #Cloudcomputing #ICT #AI #ArtificialIntelligence #ML #MachineLearning #Edge #EdgeComputing #Engineering #Construction

 The Power of AI in Networking: Smarter Troubleshooting for a Connected World As networks grow more complex — from cloud infrastructures to IoT ecosystems — traditional troubleshooting methods are no longer enough. That’s where AI steps in. Artificial Intelligence is transforming network management by enabling systems to predict, detect, and resolve issues faster than ever before. Imagine identifying a performance drop before users even notice it — or having an AI assistant pinpoint the exact switch, port, or misconfiguration causing downtime. AI-driven tools can analyze logs, monitor traffic patterns, and learn from previous incidents — turning hours of manual diagnostics into seconds of intelligent insight. For IT professionals, this means less firefighting and more strategic focus on optimizing network performance and security. The future of networking isn’t just connected — it’s intelligent ⚡ ⚡ . #Networking #ArtificialIntelligence #ITSupport #AIOps #NetworkManagement #TechInnovation #DigitalTransformation #SmartNetworks

Edge is moving from buzzword to backbone. The colocation edge data center market is projected to grow from $14.9B in 2026 to $64.2B by 2035, at a 20% CAGR. This shift reflects a deeper trend where compute is decentralizing. As AI, IoT, and latency-sensitive workloads push demand closer to the user, edge colocation is becoming an important factor for balancing proximity, power, and performance. Traditional hyperscale hubs will still lead, but the edge is where agility meets scale: smaller footprints, faster deployment, and smarter power use. The next decade won’t just be about bigger data centers. It’ll be about closer ones. If you’re identifying powered land or evaluating grid-aligned sites for next-gen edge or AI builds, let’s connect.