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  • Open service 108.138.7.97:443 · www.firstprincipleresilience.com

    2026-01-09 12:18

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    			How to Simulate How Cloud Networks Fail
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    		<p class="list__lead post__lead">Cloud networks, and most massively scaled networks, are subject to partial failures that will impact some of your application connections but not others. Congestion will lead to intermittent packet loss and is another flavor of partial impact that occurs in multi-tenant environments. How do you know if your monitoring, health checks and failure mitigations, like host removal and retry, will mitigate these kinds of failures? You test! This article will show you how you can use Linux IPTables, routing policies and network control to simulate cloud network failures.</p>
    		
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  • Open service 108.138.7.9:443 · firstprincipleresilience.com

    2026-01-09 12:18

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    			<a href="/articles/howtosimulatehowcloudnetworksfail/" rel="bookmark">
    			How to Simulate How Cloud Networks Fail
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    		</h2>
    		<p class="list__lead post__lead">Cloud networks, and most massively scaled networks, are subject to partial failures that will impact some of your application connections but not others. Congestion will lead to intermittent packet loss and is another flavor of partial impact that occurs in multi-tenant environments. How do you know if your monitoring, health checks and failure mitigations, like host removal and retry, will mitigate these kinds of failures? You test! This article will show you how you can use Linux IPTables, routing policies and network control to simulate cloud network failures.</p>
    		
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    		Linux has come a long way with tooling for simulating network failures. The traffic control (tc) tool has a wonderful bag of tricks for simulating total packet loss, intermittent packet loss and delays. Tc even provides random distributions of packet loss for additional realism in testing. However, tc doesn&rsquo;t support random % of network flow impacts. As a reminder, network flows are defined as a 5-tuple of ip address, ports and protocol.
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    	<figure class="list__thumbnail thumbnail">
    		<a class="thumbnail__link" href="/articles/howcloudnetworksfail/">
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    Found 2026-01-09 by HttpPlugin
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  • Open service 108.138.7.9:443 · firstprincipleresilience.com

    2026-01-02 15:37

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    		<p class="list__lead post__lead">Cloud networks, and most massively scaled networks, are subject to partial failures that will impact some of your application connections but not others. Congestion will lead to intermittent packet loss and is another flavor of partial impact that occurs in multi-tenant environments. How do you know if your monitoring, health checks and failure mitigations, like host removal and retry, will mitigate these kinds of failures? You test! This article will show you how you can use Linux IPTables, routing policies and network control to simulate cloud network failures.</p>
    		
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    		Linux has come a long way with tooling for simulating network failures. The traffic control (tc) tool has a wonderful bag of tricks for simulating total packet loss, intermittent packet loss and delays. Tc even provides random distributions of packet loss for additional realism in testing. However, tc doesn&rsquo;t support random % of network flow impacts. As a reminder, network flows are defined as a 5-tuple of ip address, ports and protocol.
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    	<figure class="list__thumbnail thumbnail">
    		<a class="thumbnail__link" href="/articles/howcloudnetworksfail/">
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    Found 2026-01-02 by HttpPlugin
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  • Open service 108.138.7.97:443 · www.firstprincipleresilience.com

    2026-01-02 15:37

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    	</figure>
    	<header class="list__header">
    		<h2 class="list__title post__title">
    			<a href="/articles/howtosimulatehowcloudnetworksfail/" rel="bookmark">
    			How to Simulate How Cloud Networks Fail
    			</a>
    		</h2>
    		<p class="list__lead post__lead">Cloud networks, and most massively scaled networks, are subject to partial failures that will impact some of your application connections but not others. Congestion will lead to intermittent packet loss and is another flavor of partial impact that occurs in multi-tenant environments. How do you know if your monitoring, health checks and failure mitigations, like host removal and retry, will mitigate these kinds of failures? You test! This article will show you how you can use Linux IPTables, routing policies and network control to simulate cloud network failures.</p>
    		
    	</header>
    	<div class="content list__excerpt post__content clearfix">
    		Linux has come a long way with tooling for simulating network failures. The traffic control (tc) tool has a wonderful bag of tricks for simulating total packet loss, intermittent packet loss and delays. Tc even provides random distributions of packet loss for additional realism in testing. However, tc doesn&rsquo;t support random % of network flow impacts. As a reminder, network flows are defined as a 5-tuple of ip address, ports and protocol.
    	</div>
    </article><article class="list__item post">
    	
    	<figure class="list__thumbnail thumbnail">
    		<a class="thumbnail__link" href="/articles/howcloudnetworksfail/">
    		<img class="thumbnail__image" src="/img/diagrams/CloudNetwor
    Found 2026-01-02 by HttpPlugin
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  • Open service 108.138.7.9:443 · firstprincipleresilience.com

    2025-12-23 01:12

    HTTP/1.1 200 OK
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  • Open service 108.138.7.97:443 · www.firstprincipleresilience.com

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  • Open service 108.138.7.9:443 · firstprincipleresilience.com

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    		<p class="list__lead post__lead">Cloud networks, and most massively scaled networks, are subject to partial failures that will impact some of your application connections but not others. Congestion will lead to intermittent packet loss and is another flavor of partial impact that occurs in multi-tenant environments. How do you know if your monitoring, health checks and failure mitigations, like host removal and retry, will mitigate these kinds of failures? You test! This article will show you how you can use Linux IPTables, routing policies and network control to simulate cloud network failures.</p>
    		
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  • Open service 108.138.7.82:80 · firstprincipleresilience.com

    2025-12-19 02:17

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  • Open service 108.138.7.81:80 · firstprincipleresilience.com

    2025-12-19 02:17

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  • Open service 108.138.7.81:443 · www.firstprincipleresilience.com

    2025-12-19 02:17

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  • Open service 108.138.7.81:80 · www.firstprincipleresilience.com

    2025-12-19 02:17

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  • Open service 108.138.7.82:80 · www.firstprincipleresilience.com

    2025-12-19 02:17

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  • Open service 108.138.7.9:80 · firstprincipleresilience.com

    2025-12-19 02:17

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  • Open service 108.138.7.82:443 · firstprincipleresilience.com

    2025-12-19 02:17

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    			How to Simulate How Cloud Networks Fail
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  • Open service 108.138.7.97:443 · www.firstprincipleresilience.com

    2025-12-19 02:17

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    		<a class="thumbnail__link" href="/articles/howcloudnetworksfail/">
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    Found 2025-12-19 by HttpPlugin
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  • Open service 108.138.7.9:443 · www.firstprincipleresilience.com

    2025-12-19 02:17

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    		<p class="list__lead post__lead">Cloud networks, and most massively scaled networks, are subject to partial failures that will impact some of your application connections but not others. Congestion will lead to intermittent packet loss and is another flavor of partial impact that occurs in multi-tenant environments. How do you know if your monitoring, health checks and failure mitigations, like host removal and retry, will mitigate these kinds of failures? You test! This article will show you how you can use Linux IPTables, routing policies and network control to simulate cloud network failures.</p>
    		
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    		Linux has come a long way with tooling for simulating network failures. The traffic control (tc) tool has a wonderful bag of tricks for simulating total packet loss, intermittent packet loss and delays. Tc even provides random distributions of packet loss for additional realism in testing. However, tc doesn&rsquo;t support random % of network flow impacts. As a reminder, network flows are defined as a 5-tuple of ip address, ports and protocol.
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