Seagate Unveils Next-Gen Enterprise Storage System for Scalable Growth

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

https://lnkd.in/gcXFt7MU Artificial Intelligence workloads are transforming datacenter infrastructure demands like never before. At Karios, we've pioneered an AI-native hyperconverged infrastructure platform uniquely designed to meet these challenges. Our revolutionary platform integrates intelligent hardware provisioning, Kubernetes orchestration, power & thermal management, IoT integration, and built-in security ushering in a new era of AI-ready datacentre operations. With features like automatic resource optimization, real-time asset discovery, hyper-scale support, remote out-of-band management, and sustainability-focused hardware innovations such as Karios PowerLink and the portable Karios Cube micro-datacenter, we empower enterprises to: • Seamlessly scale AI workloads • Enhance energy efficiency and sustainability • Secure infrastructure at every layer • Extend AI compute power to remote and edge environments Explore how AI-native hyperconvergence is not just the next step in HCI evolution but the foundation for the future datacentre era. #AINativeInfrastructure #HyperconvergedInfrastructure #Kubernetes #EdgeComputing #PowerManagement #IoTIntegration #ZeroTrustSecurity #Sustainability #AIWorkloads #DatacenterInnovation #Karios

Top 5 Largest Data Center in The World 2025 As our digital world continues to grow, so does the demand for massive data storage and lightning-fast processing capabilities. From social media and cloud computing to AI and IoT, everything we do online relies on powerful infrastructure hidden inside colossal data centers. In this 2025 edition, we explore the top 5 largest data centers in the world based on size, power capacity, and global impact.   Let's explore with gbc engineers how the largest data center in the world is shaping the future through innovative engineering solutions. - China Telecom-Inner Mongolia Information Park (Hohhot, China) - The Citadel – Switch (Tahoe Reno, Nevada, USA - Yotta NM1 (Panvel, India)  - Utah Data Center (Bluffdale, Utah, USA) - Lakeside Technology Center (Chicago, Illinois, USA) Much more photos and texts on full article : https://lnkd.in/e_ns-F5i

What if you could cut unplanned downtime by 70%, lower maintenance costs by 30%, and predict failures with over 90% accuracy? In our latest blog, we share how one discrete manufacturer achieved exactly that with PROLIM + Microsoft Azure — connecting machines, MES, and IoT data into a single predictive maintenance platform. You’ll learn how they: • Moved from calendar-based to condition-based maintenance • Unified siloed systems across global sites • Leveraged Azure IoT, Synapse, ML, and Power BI for real-time insights 👉 Read the full story: https://lnkd.in/gXzZTebm #Manufacturing #PredictiveMaintenance #Industry40 #IoT #Azure #DigitalTransformation #SmartManufacturing

Powering the Digital World: Expansion of the Data Center Services Market The global data center services market size is predicted to reach USD 260.47 billion by 2033 from USD 94.69 billion in 2024, registering a CAGR of 11.9% during the forecast period from 2025 to 2033. Rising cloud adoption, AI workloads, and IoT data growth are driving global demand for advanced data center services. Providers are focusing on green infrastructure, edge computing, and energy-efficient cooling to meet modern digital infrastructure needs. List of Top Data Center Services Companies Arrow Electronics (U.S.) Sims Recycling (U.S.) IBM (U.S.) HPE (U.S.) Atlantix Global Systems (U.K.) Get Sample Copy of this Report - https://lnkd.in/gmnD_RZE #DataCenterServices #CloudComputing #EdgeComputing #DigitalInfrastructure #AI #GreenDataCenters

IoT Streams feature released with ThingWorx 10.0 June 2025 has been an instant hit! TBH- It’s exceeded my expectations to see the creative ways it adds value to the ThingWorx ecosystem. So, working with early adopters, our services team has authored a best practice guide along with sample code to help you start with IoT Streams. The GitHub artifact located at https://lnkd.in/dPh7u92C provides practical guidance for leveraging ThingWorx IoT Streams to: ·      Export data from ThingWorx to external systems ·      Implement durable queues for reliability ·      Design scalable streaming architectures ·      Integrate with Kafka and Azure Event Hubs So, check it out, try IoT Streams in your projects, and share how you’re using it in the ThingWorx community here: https://lnkd.in/dT7ScvVe Cheers Ayush

Exciting innovation from the ThingWorx team! The IoT Streams feature, released with ThingWorx 10.0 (June 2025), is already creating real value for our customers. It’s great to see how it enables more reliable, scalable, and flexible data streaming within the ThingWorx ecosystem, helping customers connect systems, manage data efficiently, and build resilient IoT architectures. As a CSM, I’m especially excited about how this supports our customers’ digital transformation journeys, from improving data flow across environments to integrating seamlessly with Kafka or Azure Event Hubs. A new best practice guide is available, with practical examples and code to help you get started: 👉 https://lnkd.in/dPh7u92C Kudos to Ayush Tiwari and the team for driving this forward! 👏 Let’s continue sharing how IoT Streams is being used across projects: 👉 https://lnkd.in/dT7ScvVe

The Rise of Edge Computing in Modern IT In today’s fast-paced digital world, low-latency data processing is no longer a luxury—it's a necessity. Edge computing is revolutionizing how organizations handle data by moving processing closer to the source rather than relying solely on centralized cloud servers. This approach drastically reduces latency, improves response times, and enables real-time analytics. Industries like autonomous vehicles, smart manufacturing, and healthcare are already leveraging edge computing to enhance operational efficiency and user experience. Moreover, edge computing complements cloud infrastructure by offloading heavy workloads locally, reducing bandwidth usage, and increasing system resilience. As IoT devices proliferate and data volumes explode, edge computing will become a cornerstone of modern IT architectures, offering faster, smarter, and more secure solutions for businesses and consumers alike. https://lnkd.in/gr92_3Yh

The growing complexity of the IoT edge—facing thousands of distributed devices, continuous updates, and security demands—requires a unified management approach. The traditional way is no longer efficient, CTHINGS.CO explains. #EdgeAI #IoTManagement https://lnkd.in/eq_xvYq2 The economic case for AI at the edge: - Scalability: Seamlessly manage growing fleets of devices across diverse environments. - Autonomy: Enable local intelligence for faster decisions, critical for time-sensitive use cases. - Efficiency: Spot anomalies and predict failures instantly, reducing downtime and maintenance costs. With the edge computing market projected to grow rapidly, AI is emerging as the necessary game-changer to move from insight to coordinated action.