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    <title>Scaling the API: How Far Request-Response Actually Goes</title>
    <link>https://www.rambling-me.com/blog/posts/technology/scaling/api-backend/1-how-far-request-response-goes</link>
    <description>The honest defense of synchronous request-response. Before reaching for a broker, most systems have a long runway left in boring, well-understood techniques: stateless services, connection pooling, caching in front of the database, and read replicas. Services scale for free. The database is the ceiling. Knowing how far sync goes tells you when you actually need something else.</description>
    <pubDate>Mon, 27 Jul 2026 00:00:00 GMT</pubDate>
    <author>me@rambling-me.com (Dopeking)</author>
    <category>technology</category><category>scaling</category><category>api-backend</category><category>system-design</category><category>request-response</category><category>caching</category><category>database</category><category>practitioner</category>
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    <title>Scaling: What Breaks, and When</title>
    <link>https://www.rambling-me.com/blog/posts/technology/scaling/orders-of-magnitude/2-what-breaks-and-when</link>
    <description>A walk up the orders of magnitude with one system. At hundreds of requests per second a single box is fine. At thousands, caching and replicas earn their keep. At tens of thousands the sync path cracks and state becomes the enemy. At millions, physics starts dictating the architecture. What breaks first at each rung, and the cheapest thing that fixes it.</description>
    <pubDate>Mon, 20 Jul 2026 00:00:00 GMT</pubDate>
    <author>me@rambling-me.com (Dopeking)</author>
    <category>technology</category><category>scaling</category><category>orders-of-magnitude</category><category>system-design</category><category>bottlenecks</category><category>database</category><category>sharding</category><category>practitioner</category>
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