The Alibaba Cloud Big Data AI Platform builds on Alibaba’s leading cloud infrastructure, big‑data and AI engineering capabilities, scenario algorithms, and extensive industry experience to offer enterprises and developers a one‑stop, cloud‑native big‑data and AI capability suite. It boosts AI development efficiency, enables large‑scale AI deployment across industries, and drives business value.
This article explores Kubernetes Custom Resource Definitions (CRDs) and Operators, explaining their origins, how they enable custom resources, the operator concept, practical examples like a smart‑home light controller, and guidance on building operators with frameworks such as KubeBuilder and Operator‑SDK.
Helm, the Kubernetes package manager, streamlines the creation, packaging, configuration, and deployment of complex applications by bundling multiple YAML resources into reusable charts, offering lifecycle management, command‑line convenience, ecosystem plugins, secret handling, debugging tools, and addressing both its advantages and limitations within SREWorks.
This article introduces Kustomize, explains its base‑and‑overlay approach for managing native Kubernetes YAML, provides practical file‑structure examples and commands, compares it with Helm, and shares a real‑world SREWorks component implementation for flexible, template‑free deployments.
This tutorial explains how to use Milvus 2.5's new full‑text, BM25 keyword matching, and hybrid search capabilities—including step‑by‑step setup, schema design, code examples, and RAG integration—to achieve high recall and precision in large‑scale AI vector retrieval scenarios.
SREWorks v1.2 introduces an extensible operations marketplace, supports private intra‑network source builds with configurable resources, enhances metric collection and data consumption via Logstash and Kafka, adds various optimizations, and provides upgrade instructions for seamless migration to the new version.
This article walks through the complete structure of a Kubernetes Pod—covering its Resource, Object, Spec, and Status sections, the corresponding REST API paths, metadata fields, lifecycle phases, scheduling strategies, and status reporting—providing a clear, step‑by‑step guide for both beginners and experienced users.
This article explains how SREWorks evolved its continuous delivery pipeline from traditional machine‑based builds to fully cloud‑native, elastic image construction using on‑demand Pods, Docker‑in‑Docker techniques, and the Kaniko builder to achieve secure, serverless, and fast deployments.
This article explores the evolution of low‑code front‑end development, detailing the sw‑frontend architecture, visual designer, component system, dynamic routing, form factories, data handling, and future roadmap for building efficient, serverless, cloud‑native operations interfaces.
Alibaba Cloud’s Serverless Elasticsearch service, combined with the SREWorks data‑driven operations platform, offers a cloud‑native, real‑time search and analytics engine that integrates metric and log collection, cost management, and health monitoring to enhance scalability, performance, and operational efficiency for enterprise applications.
SREWorks v1.1 introduces a lightweight base edition, plug‑in support for ElasticSearch, MySQL and MinIO, a low‑code page template center, default OpenEBS‑based StorageClass, numerous bug fixes, and a straightforward upgrade path, all aimed at simplifying cloud‑native operations platforms.
