34 lines
1.6 KiB
Markdown
34 lines
1.6 KiB
Markdown
> *Latency plays a key role in determining the overall performance of the
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distributed service/application, where calls are made between hosts to
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serve the users.*
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RTT is a measure of time, it takes for a packet to reach B from A, and
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return to A. It is measured in milliseconds. This measure plays a role
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in determining the performance of the services. Its impact is seen in
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calls made between different servers/services, to serve the user, as
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well as the TCP throughput that can be achieved.
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It is fairly common that service makes multiple calls to servers within
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its cluster or to different services like authentication, logging,
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database, etc, to respond to each user/client request. These servers can
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be spread across different cabinets, at times even between different
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data centres in the same region. Such cases are quite possible in cloud
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solutions, where the deployment spreads across different sites within a
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region. As the RTT increases, the response time for each of the calls
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gets longer and thereby has a cascading effect on the end response being
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sent to the user.
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### Relation of RTT and throughput
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RTT is inversely proportional to the TCP throughput. As RTT increases,
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it reduces the TCP throughput, just like packet loss. Below is a formula
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to estimate the TCP throughput, based on TCP mss, RTT and packet loss.
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As within a data centre, these calculations are also, important for
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communication over the internet, where a client can connect to the DC
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hosted services, over different telco networks and the RTT is not very
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stable, due to the unpredictability of the Internet routing policies.
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