Ceramic Nodes in Production: Example Costs + Scenarios
Running a Ceramic node involves several key services. Learn about what production costs to expect across example hypothetical scenarios.
Running a Ceramic node in a production environment involves several key components. This article aims to provide an overview of the necessary resources and cost estimates for deploying a Ceramic node in the cloud. While we only showcased two specific providers for the services required (DigitalOcean and QuickNode), we hope these cost examples given the hypothetical scenarios we walk through will help give you a general idea of cost.
There are several sub-services to consider when running a Ceramic node in production, each serving different functions. As such, you will need:
Given the services you’ll need above, the Ceramic team has tested and organized a set of “baseline” configuration settings we recommend when setting up your node. However, seeing as these are baseline, or average, you may need to increase resourcing accordingly based on your actual usage:
Given the services you’ll need above, the Ceramic team has tested and organized a set of “High Traffic” configuration settings we recommend when setting up your node. However, seeing as these are baseline, or average, you may need to increase resourcing accordingly based on your actual usage:
For high availability, an additional node can be configured to sync data and handle dynamic read/write tasks, thus doubling the cost of a single-node setup.
We’ve also chosen QuickNode to provide several RPC cost examples :
Let’s walk through three hypothetical need scenarios and use these to help estimate our cost structure:
Additional cloud costs must be considered for networking - these costs will vary based on traffic patterns. Most cloud providers offer free traffic ingress to the nodes but will charge for egress, or data leaving the nodes.
Running a Ceramic node in production involves various components and resources, each contributing to the overall cost. By understanding the necessary configurations and associated costs, developers can make informed decisions tailored to their application's needs and user base. High availability setups and resource over-provisioning can significantly impact costs, especially for mid-sized applications with high traffic and write volumes.