Networking metrics - Deepstash

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Networking metrics

Networking metrics

  • Bandwidth - Maximum amount of data that can be transferred in a unit of time. Usually expressed in bits per second.
  • Throughput - Amount of data that is actually transferred in a unit of time.
  • Latency - How long it takes data to go from one end to the other.

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Asynchronous processing

Asynchronous processing

Slow operations should be done asynchronously to avoid making users wait for long periods of time until their requests are processed.

Sometimes this can be done in advance, by pre-processing data that you know users will need. For example, a forum might per...

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Caching

Caching

Caching systems are usually in-memory key-value databases that provide very fast access to data. They sit between your application and the database.

Depending on your use case, you can either cache only the results of the database queries, or cache the entire response objec...

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Scaling

Scaling

Systems can be scaled:

  • Vertically - by increasing the resources of a specific node (more CPU, memory, disk etc.). This is easier to do, but it's limited. You can only add so many CPU cores and memory.
  • Horizontally - by adding more nodes of the ...

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Database sharding

Database sharding

Sharding means splitting your data across multiple nodes. This can be done in different ways:

1. Vertical sharding

  • Store tables on different nodes.
  • Drawback: If one of these tables gets very large, then you need to re-shard that datab...

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Database denormalization

Database denormalization

Joins in relational databases get very slow as the system grows bigger. You should denormalize your data to avoid joins and speed up your queries.

Normalized databases are designed to minimize redundancy, while denormalized databases are designed to optimize read ti...

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Performance and scale

Performance and scale

  • Each Frontend node handles 100k persistent connections. It handles only this many connections because the server is doing a lot of work processing multiple types of data (likes, comments, instant messaging etc.).
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