Apache Kafka is a common choice for inter-service communication. Kafka facilitates the parallel processing of messages and is a good choice for log aggregation. Kafka claims to be low latency, high throughput . However, is Kafka fast enough for many microservices applications in the cloud? When I wrote Chronicle Queue Open Source my aim was to develop a messaging framework with microsecond latencies, and banks around the world have adopted it for use in their latency-sensitive trading systems. In this article, I will describe how Kafka does not scale in terms of throughput as easily as Chronicle Queue for microservices applications. As a teaser, I will show you this chart showing that Chronicle Queue is around 750 times faster even for lower throughput. Visualising delay as a distance In order to illustrate the difference, let me start with an analogy. Light travels through optic fibre and copper at about two thirds the speed of light in a vacuum, so to appreciate very short de
It depends on the context and what your customer expects. I will differentiate between 3 type of editions:
ReplyDelete1. the ones that can be solved by the customer, like a NumberFormatException from a customer data.
2. The ones that customer cannot do anything like a NullPointerException.
3. Others we can retry, like the dependency is not available.
So for 3 I will not show them to customer unless they are persistent, in which case they become exceptions of type 2.
For type 1 you need to show to the customer and I will not log anything, obviously you need to catch it.
For type 2 you should show to customer as well and potentially with a way to report the error.
ReplyDeleteI saw lot of information On Other Site But this blog helped me alot to learn Java Thanks for sharing.........
Is this blog dead? no posts since Mar.2017
ReplyDeletePlease follow the links to my new blog, though the last post was the end of May, I have more posts planned.
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