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Cake day: June 12th, 2023

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  • I work for a company that handles this In a few ways. We set up read replicas to handle large read queries. To offload the reads from the primary server. Data is replicated to the read replicas so reporting can be run from that server. And not add load to the primary server.

    The second approach is sharding. Sharding breaks a large table into smaller, more manageable chunks, distributing them across systems. This reduces the burden on any one server, improves performance, and enables scaling out as data or traffic increases.






  • Can’t remember the full details of the deal, but I seem to recall a story about how Apple approached Intel to manufacture a low-powered processor for mobile (for the first iPhone). At the time, Intel didn’t see money in mobile processors and passed on the deal. Additionally, for years, Apple asked for more powerful chips for the MacBooks. At the time, the iPads were surpassing MacBooks in speed on some tasks. Finally, Apple decided that since they were already designing their own silicon for iPhones and iPads, they might as well just do the same for the MacBooks as well since Intel couldn’t keep up.

    Again, this is largely from memory. I can’t remember the source, so take it with a grain of salt.