Alibaba ACA Cloud Computing case studies
Alibaba ACA Cloud Computing · Put your knowledge to work in context.
The Alibaba ACA Cloud Computing credential is an associate-level certification for practitioners who want to demonstrate foundational competence with Alibaba Cloud's platform. It suits cloud engineers, solution architects, developers, and operations staff early in their Alibaba Cloud journey, as well as professionals preparing for more advanced Alibaba Cloud certifications. The exam tests breadth rather than deep specialization: core cloud computing concepts and how Alibaba Cloud positions its portfolio, compute with Elastic Compute Service, storage and delivery through Object Storage Service and CDN, networking with Virtual Private Cloud, Server Load Balancer, and Cloud Enterprise Network, plus security, identity and access management. Recent revisions of Alibaba Cloud's own materials also emphasize AI and cloud solutions, including Qwen models, Model Studio, and Platform for AI (PAI), so expect questions that connect classic infrastructure to AI workloads. The Alibaba ACA Cloud Computing case studies are 5 cases and about 2,425 words.
1Right-sizing an order-processing fleet under bursty load
A retail team runs its order API on 12 ECS instances behind an SLB. Each instance is a general-purpose type with 4 vCPU and 16 GiB.
503 words, about 3 min2Static assets served slowly to overseas users
A media company stores 4 TB of images and short videos in an OSS bucket in the China (Hangzhou) region. Users are split roughly 70% mainland China and 30% Southeast Asia.
483 words, about 2 min3Two VPCs, overlapping CIDRs, and a latency-sensitive database
A company acquires a partner and must connect two environments. VPC A (10.0.0.0/16) runs the core app in Hangzhou.
450 words, about 2 min4A shared account, a leaked key, and least privilege
A 40-person startup runs everything in one Alibaba Cloud account. All engineers use a shared RAM user whose AccessKey is stored in a wiki page and baked into CI scripts.
500 words, about 3 min5Choosing between a hosted model API and a trained model for document review
A legal-tech team wants to extract clauses and risk flags from 200,000 contracts per month. Documents average 30 pages and are confidential.
489 words, about 2 min