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Coreweave logoCoreweave · Feature trail

Customer Cloud Solutions

15 posts · May 2026 – Sep 2026

What this trail covers

CoreWeave enhances its cloud solutions to cater to specific customer needs, focusing on scalability, security, and high-performance compute for demanding workloads. This involves providing tailored infrastructure, direct connections, dedicated storage, and upgrade options to enable customers to design, execute, and scale proprietary models efficiently. The goal is to deliver timely access to cutting-edge technologies in a fully managed fashion, leading to rapid deployment, increased compute, and improved collaboration for virtual production and other real-time rendering applications. The integration of WebRTC-based streaming allows for high-fidelity experiences to be rendered in the cloud and streamed directly to users, solving challenges of remote collaboration and on-set visualization.

All Coreweave trails
  1. An AI Cloud Platform Is More Than Rented Hardware | CoreWeaveThis post articulates the strategic differentiation of CoreWeave's AI cloud platform beyond mere GPU capacity. It emphasizes the value proposition of integrated orchestration, observability, security, and development tools, which transform raw hardware into a functional environment for building and running AI products. The post highlights how this platform approach broadens the addressable market to diverse enterprises and provides durability by enabling customers to build and grow production systems over the long term, citing customer examples like Jane Street, Zonos, and Mercado Libre as evidence of platform depth and customer breadth.
  2. Introducing Automated User Provisioning and SUNK User Provisioning | CoreWeave BlogIntroduced Automated User Provisioning (AUP) and SUNK User Provisioning (SUP) to automate user provisioning for Slurm clusters. AUP integrates with enterprise identity providers (e.g., Okta, Microsoft Entra) via SCIM to synchronize users and groups with CoreWeave IAM. SUP extends this automation to Slurm-on-Kubernetes (SUNK) clusters, automatically creating POSIX users, groups, SSH keys, and Slurm users/accounts. This leverages NSSCache for resilient, local caching of identity data, improving performance and reliability compared to traditional daemon-based solutions like SSSD.
  3. Kueue: Kubernetes-Native AI Workload Scheduling with CoreWeaveThis post introduces Kueue as a Kubernetes-native system for AI training workloads on Coreweave Kubernetes Service (CKS). It explains the challenges of traditional Kubernetes for GPU-intensive AI jobs (inelastic GPU nodes, 'all-or-nothing' requirements) and how Kueue addresses these with 'all or nothing' scheduling, ResourceFlavors for fine-grained resource management, and ClusterQueues/LocalQueues for multi-tenant resource sharing, including quota borrowing and preemption. Coreweave provides a Helm chart for Kueue installation and integrates its metrics into Grafana.
  4. SkyPilot for Multi-Cloud Orchestration | CoreWeave BlogThis post introduces official support for SkyPilot, an open-source framework for multi-cloud AI orchestration, on CoreWeave's GPU infrastructure. Key technical contributions include: one-line InfiniBand enablement via a `<network_tier: best>` directive in SkyPilot resources, native integration with CoreWeave AI Object Storage using a `cw://` scheme for high-throughput data access (up to 7 GB/s per GPU), and autoscaling support for CoreWeave clusters. The post also details how SkyPilot abstracts cluster management, auto-selects resources, and handles job submission, with specific examples for training, development, and serving workloads, and highlights the benefits of combining SkyPilot's orchestration with CoreWeave's bare-metal Kubernetes architecture for price/performance optimization and reduced time-to-market.
  5. Tarteel Migrates to CoreWeave with Support from ZeetThis post details Tarteel's migration of its AI-powered Quran app infrastructure from AWS to CoreWeave, facilitated by Zeet. The migration resulted in a 22% improvement in latency and approximately a 56% cost reduction. Key technical aspects include the use of NVIDIA Riva and NeMo toolkits for ASR and TTS models, Triton for inference, and the benefits of CoreWeave's GPU selection, observability (Grafana/Prometheus), and native S3 solution. Zeet's role in simplifying the deployment and autoscaling process is also highlighted.
  7. Unlocking cross-cloud AI | CoreWeave BlogIntroduces CoreWeave Interconnect, a private high-performance fiber-based network interconnect directly connecting CoreWeave Cloud to Google Cloud, leveraging Google Cloud's Partner Cross-Cloud Interconnect. Details SUNK Anywhere, extending the SUNK (Slurm on Kubernetes) system to support GPU environments across clouds or on-premises, enabling consistent cross-cloud AI training. Mentions LOTA Cross-Cloud for storage integration.
  8. Why general-purpose cloud platforms throttle AI innovation | CoreWeave BlogThis post details the architectural mismatch between general-purpose cloud platforms and AI workloads, explaining how limitations in provisioning, infrastructure rigidity, and cost control inherent in legacy clouds throttle AI innovation. It advocates for purpose-built AI clouds that offer on-demand GPU access, high-throughput networking, flexible resource orchestration, and deep observability to accelerate AI development and deployment.