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In Amazon's spot instance (SI) market, the volatility of the two important parameters, namely spot price (SP) and inter-price time (IPT), affects not only the market's profit, but also its service reliability. Thus, it is important for the cloud service provider to understand how SP and IPT impact the profit-reliability trade-off in the SI market. To the best of our knowledge, such a trade-off has not been studied in existing liter-ature. In this paper, we model Amazon's SI market as a modified repeated single-price auction and study the profit maximization problem using a graph model. We prove the NP-Completeness of the corresponding offline decision problem. Moreover, we propose an order-statistics based online pricing (OSOP) algorithm that can effectively evaluate and tune the profit-reliability trade-off by on-the-fly adapting SP and IPT. In our approach, SP and IPT are determined in real time based on the order statistics of the latest historical bids and the profit-reliability trade-off desired by the service providers. Our experiments show that the proposed OSOP mechanism (on average) achieves as high as ≈19% profit gain as compared to the current algorithm, with negligible reliability loss. Moreover, the mechanism also achieves a favorable trade-off between profit and service reliability, at which point our mechanism (on average) achieves ≈ 12% profit gain and ≈ 8% reduction in unexpected service interruption penalty as compared to the current algorithm.