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When it comes to carbon emissions and the internet, we very often come back to data centers and streaming applications. But what is the situation and how can we improve it?
Being interested in Green IT and the CO2 emissions of our data centers, I've had the opportunity to read several very interesting articles that I'd like to share with you and give you my thoughts.
One of the challenges faced by distributed systems is how to keep the replicas consistent with each other. Maintaining consistency requires balancing availability and partitioning. Fortunately, Apache Cassandra lets us tune this balancing according to our needs. In this blog, we are going to see how we can tune consistency levels during reads and writes to achieve faster reads and writes.
Before digging more about consistency, let me first discuss CAP Theorem. CAP Theorem describes the tradeoffs in distributed systems; it states that any networked shared-data system can have at most two of three desirable properties: