Scaling Across Clusters: JD Cloud’s Large‑Scale Application Management Practices
At KubeCon + CloudNativeCon 2024 in Hong Kong, JD Cloud presented its cross‑cluster, large‑scale application management practice, detailing a federated Serverless model that oversees over 10,000 nodes, improves resource utilization, simplifies multi‑cluster scheduling, and offers efficient elastic scaling solutions.
Alongside the digital wave, AI is transforming cloud computing, making it safer and more efficient for industries worldwide.
The KubeCon + CloudNativeCon + Open Source Summit + AI_dev China 2024, co‑hosted by CNCF and the Linux Foundation, opened in Hong Kong on August 21, 2024, attracting over 1,000 participants from more than 30 countries.
JD Cloud’s on‑site technical sharing topic: “Cross‑Cluster Large‑Scale Application Management Practice”.
In JD Cloud, the federated Serverless service is built on a federated management model and a Serverless application model, providing JDOS application container control for federated app container deployment, elastic scaling, and fault migration.
The service manages multiple clusters with over 10,000 nodes, unifying management of sub‑clusters to improve overall resource utilization and reduce the complexity of multi‑cluster management, scheduling, and distribution.
Users can interact with the platform using the native Kubernetes API, while the team addresses several technical challenges:
Multi‑cluster management and distribution practices
Efficient cross‑cluster elastic scaling solutions
Issues encountered in production and sharing
The elastic scaling technology has broad application prospects, and JD Cloud is conducting extensive production practice and verification internally.
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