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Delska is a data center and network operator that provides tailor-made IT and network services for businesses. With 5 data centers (one under construction, launching in 2025) in Latvia and Lithuania, and points of presence in Germany, Netherlands, and Sweden, we offer a comprehensive regional data center and network ecosystem. By 2030, we aim to achieve net-zero CO2 emissions, setting standard for sustainable IT infrastructure in the Baltic region. In addition to cloud computing, colocation, data security, network, and other services, we have launched the self-service cloud platform myDelska for swift virtual machine deployment, IT resources management, and soon-to-come bare metal services. Key features: • Unlimited traffic and predictable monthly costs • API integration • Flexible firewall configurations • Backup solutions • Real-time network topology • Latency measurement map • Alpine Linux, Ubuntu, Debian, Windows OS, openSUSE and other operating systems Since June 2024, Delska has merged 2 companies—DEAC European Data Center and Data Logistics Center (DLC). Both operate under their respective legal entities, which are owned by Quaero European Infrastructure Fund II.

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RunPod provides a cloud infrastructure that enables seamless deployment and scaling of AI workloads with GPU-powered pods. By offering access to a wide array of NVIDIA GPUs, such as the A100 and H100, RunPod supports training and deploying machine learning models with minimal latency and high performance. The platform emphasizes ease of use, allowing users to spin up pods in seconds and scale them dynamically to meet demand. With features like autoscaling, real-time analytics, and serverless scaling, RunPod is an ideal solution for startups, academic institutions, and enterprises seeking a flexible, powerful, and affordable platform for AI development and inference.

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Compute Engine (IaaS), a platform from Google that allows organizations to create and manage cloud-based virtual machines, is an infrastructure as a services (IaaS). Computing infrastructure in predefined sizes or custom machine shapes to accelerate cloud transformation. General purpose machines (E2, N1,N2,N2D) offer a good compromise between price and performance. Compute optimized machines (C2) offer high-end performance vCPUs for compute-intensive workloads. Memory optimized (M2) systems offer the highest amount of memory and are ideal for in-memory database applications. Accelerator optimized machines (A2) are based on A100 GPUs, and are designed for high-demanding applications. Integrate Compute services with other Google Cloud Services, such as AI/ML or data analytics. Reservations can help you ensure that your applications will have the capacity needed as they scale. You can save money by running Compute using the sustained-use discount, and you can even save more when you use the committed-use discount.

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