  Cloud-native architecture is becoming increasingly crucial for today's cloud
computing environments due to the need for speed and flexibility in developing
applications. It utilizes microservice technology to break down traditional
monolithic applications into light-weight and self-contained microservice
components. However, as microservices grow in scale and have dynamic
inter-dependencies, they also pose new challenges in resource provisioning that
cannot be fully addressed by traditional resource scheduling approaches. The
various microservices with different resource needs and latency requirements
can create complex calling chains, making it difficult to provide fine-grained
and accurate resource allocation to each component while maintaining the
overall quality of service in the chain. In this work, we aim to address the
research problem on how to efficiently provision resources for the growing
scale of microservice platform and ensure the performance of latency-critical
microservices. To address the problem, we present in-depth analyses of
Alibaba's microservice cluster and propose optimized resource provisioning
algorithms to enhance resource utilization while ensuring the latency
requirement. First, we analyze the distinct features of microservices in
Alibaba's cluster compared to traditional applications. Then we present
Alibaba's resource capacity provisioning workflow and framework to address
challenges in resource provisioning for large-scale and latency-critical
microservice clusters. Finally, we propose enhanced resource provisioning
algorithms over Alibaba's current practice by making both proactive and
reactive scheduling decisions based on different workloads patterns, which can
improve resource usage by 10-15% in Alibaba's clusters, while maintaining the
necessary latency for microservices.
