ARM processors, with their low power consumption and heat dissipation, have been highly successful in embedded systems. In the recent past, there have been attempts to adopt these energy-efficient processors for servers in data centers. However, a fundamental question remains open with ARM-based systems on server side is whether they are capable of handling compute-intensive workloads at scale. This paper gives our answer to this question with an empirical approach. We study the performance characteristics of the Amazon Graviton Processor-an ARM64 processor with the Cortex-A72 micro-architecture-using the A1 (Graviton) product family on AWS EC2, with comparisons to the I3 and M5 product families based on Intel Xeon processors. We use a combination of micro benchmark and performance counters to identify the lack of L3 cache and the slower memory access speed limit Graviton's capability in achieving higher performance. We confirm Graviton's capability in handling various large-scale horizontally scalable compute-intensive workloads, including multi-tier web service, video transcoding and terabyte scale sorting. In our large-scale evaluations, the test worker fleet has up to 1600 vCPU cores, which is by far the largest ARM64 cluster that has been reported. We observe that the A1 product family achieves the same price-performance in multi-tier web service, up to 37% cost saving in video transcoding, and up to 65% cost saving in terabyte scale sorting, as compared with the I3 and M5 product families.