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Previously we detailed what memory statistics you can view in a Kubernetes, along with the importance of each metric. Of particular note is the (file) cache, using “available” memory to optimize IO. To demonstrate these container memory metric interactions, lets take a look at a Kafka broker...
Previously we looked at memory usage by the system as a whole, focusing on the buffers and cache usage that can grow and shrink as needed to optimize file IO. But how much cache do we really need? And how can we tell who is using it? For this deeper dive we’re going to focus on the usage...