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Amazon Web Services reserved instances are virtual machine instances purchased for an upfront fee and an hourly...
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rate that's lower than the rate for on-demand instances. The reduced rate might seem like a selling point, but reserved instances aren't a fit for every company.
Reserved instances from Amazon Web Services (AWS) are billed according to the length of the contract term -- one or three years -- and the level of their utilization (light, medium or heavy). "Light" utilization means an instance is used less than 39% of the time during the contract period; "medium" utilization, less than 75% of the time; and "heavy" utilization, more than 75% of the time. To save on hourly charges, you can shut down your light- or medium-utilization AWS reserved instances, but heavy-utilization instances are billed at the hourly rate regardless of the state of the instance. The break-even point for a one-year light-utilization Linux server is 28% utilization; for a one-year medium-utilization Linux server, 41%; and for a one-year heavy-utilization Linux server, 56%.
You can purchase AWS reserved instances from the company itself or from AWS customers who sell their reserved instances on the Amazon Reserved Instance Marketplace. Third-party listings are shown in the management console with Amazon's listing. The length of contract term and price can vary with third-party sellers. You might be able to find short-term contracts from third parties, but the supply will fluctuate.
If you are primarily concerned with keeping your cost per instance down but you want to avoid long-term contracts, consider using "spot" instances instead, which are suitable for jobs that can be disrupted and restarted. Spot instances should not be used for applications that require consistent availability, such as websites, or continuous availability, such as transaction processing systems.
About the author
Dan Sullivan, M.Sc., is an author, systems architect and consultant with more than 20 years of IT experience. He has had engagements in advanced analytics, systems architecture, database design, enterprise security and business intelligence. He has worked in a broad range of industries, including financial services, manufacturing, pharmaceuticals, software development, government, retail and education. Dan has written extensively about topics from data warehousing, cloud computing and advanced analytics to security management, collaboration and text mining.
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