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      <h1 class="brand"><a href="https://rafaelcapucho.github.io">rafaelcapucho.com</a></h1>
      <p class="lead">
       be welcome 
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        <li><a href="https://rafaelcapucho.github.io/blog">Posts</a></li>
        
            <li><a href="/about/">About me </a></li>
        
    
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        <li><small>My main open source project:</small></li>
        <li><a href="http://github.com/rafaelcapucho/scrapy-eagle" target="_blank"><i class="fa fa-github-square"></i>&nbsp;Scrapy-Eagle</a></li>


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    &copy; 2017 Rafael Capucho.<br>All rights reserved.</p>

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    <h1 class="post-title">
      <a href="https://rafaelcapucho.github.io/2016/10/enhance-the-quality-of-your-api-calls-with-client-side-throttling/">
        Enhance the quality of your API calls with Client-Side Throttling
      </a>
    </h1>

    <span class="post-date">Oct 2, 2016</span>

    
        If you are a backend engineer and work with high load environment you should be familiarized with the old Server-Side Rate Limit, mainly for security concerns. Didn&rsquo;t you ever heard about Server-Side Rate Limit? It is a technique to limit the amount of requests that the server or API can handle in a defined period of time, and that limit can be set per user or not. Throttling is often used to limiting traffic on the server, mainly as a way to protect against DOS Attack.
        <a href="/2016/10/enhance-the-quality-of-your-api-calls-with-client-side-throttling/">Read More…</a>
    

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      <a href="https://rafaelcapucho.github.io/2016/09/speeding-up-your-mongodb-queries-up-to-30-times-with-tornado/">
        Speeding up your MongoDB queries up to 30 times with Tornado
      </a>
    </h1>

    <span class="post-date">Sep 5, 2016</span>

    
        Sometime ago, I was facing a problem using MongoDB to perform heavy operations like Aggregations over a considerable amount of documents. Fortunately, most of them were repeating, like when your projects are fetching contents from database to make the same menu structure, it doesn&rsquo;t change every second. We already know how is the recipe to solve that: Cache it. I was using Tornado and it&rsquo;s common to use Motor to perform async database operations over MongoDB.
        <a href="/2016/09/speeding-up-your-mongodb-queries-up-to-30-times-with-tornado/">Read More…</a>
    

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