In Figure 1, you can see our example application logical architecture looks like this: Let’s assume for now that the workload is entirely static, and autoscaling isn’t being used (oh don’t worry, we’ll add that and more back in later). The Cassandra cluster will need five instances with a higher memory footprint.

The application layer will need four instances for image processing and storage control.The marketing front end shouldn’t need more than two instances for redundancy.Therefore we should only need four regular instances for this layer. We expect about 350 requests per second given this number of users. The API frontend instances can respond to roughly 80 requests per second.And on the back end, a Cassandra cluster to store operational metadata.įor capacity planning, we have scoped as follows:.An application layer that will process and store images as they come in or are accessed.This portion will consume the majority of the compute cycles. An API frontend that mobile devices will contact for requests and actions.Our example application has 4 components: Let’s go through what instance types this application will need to meet that user-driven workload and then price out what that will cost in an average month on Google Cloud Platform and compare against Amazon Web Services. This application shares pictures in some way, and has about 5 million active monthly users. For this example, let's look at a fairly common scenario, a mobile application with its backend in the cloud. To help you work this through, we’ve created an example for you. How do you figure out what each costs and make a choice? Some bill in different time increments, and many offer a variety of payment structures, each with differing economic ramifications. In addition, no two clouds are the same! Some bundle components while others offer more granular purchasing. Cloud infrastructure systems create a whole new range of variables in these complex equations. Costs come from a variety of sources, and every approach to delivering infrastructure has its own tradeoffs and complexities. When designing infrastructure systems, whether creating new applications or deploying existing software, it’s crucial to manage cost.

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