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pull-1/sitemap.xml

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<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
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<loc>https://redhat-solution-patterns.github.io/solution-patterns/solution-pattern-event-mesh-for-microservices/01-pattern.html</loc>
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</url>
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<loc>https://redhat-solution-patterns.github.io/solution-patterns/solution-pattern-event-mesh-for-microservices/02-architecture.html</loc>
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</url>
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<loc>https://redhat-solution-patterns.github.io/solution-patterns/solution-pattern-event-mesh-for-microservices/03-demo.html</loc>
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</url>
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<loc>https://redhat-solution-patterns.github.io/solution-patterns/solution-pattern-event-mesh-for-microservices/developer-resources.html</loc>
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<loc>https://redhat-solution-patterns.github.io/solution-patterns/solution-pattern-event-mesh-for-microservices/index.html</loc>
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pull-1/solution-pattern-event-mesh-for-microservices/02-architecture.html

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@@ -177,7 +177,7 @@ <h2 id="tech_stack"><a class="anchor" href="#tech_stack"></a><a class="link" hre
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<li>
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<p><a href="https://www.redhat.com/en/technologies/cloud-computing/openshift">Red Hat OpenShift</a>
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&mdash; Orchestrate containerized applications.
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Based on <a href="https://kubernetes.io/">Kuberentes</a>.</p>
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Based on <a href="https://kubernetes.io/">Kubernetes</a>.</p>
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</li>
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<p><a href="https://www.redhat.com/en/technologies/cloud-computing/openshift/serverless">Red Hat OpenShift Serverless</a>
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This results in better alignment with business requirements, as it supports scenarios where multiple services collaborate and synchronize their operations, making the whole state eventually consistent, without the constraint of strict, synchronous consistency.</p>
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</li>
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<p><strong>Avoidance of systemic issues</strong>:
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<p><strong>Improved Resilience</strong>:
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The <em>Event Mesh</em>'s error-handling mechanism, through retries and event persistence, aids in minimizing the impact of failures on the end user.
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This is crucial as it prevents bugs and outages from becoming visible to the user, thereby preserving the system&#8217;s perceived responsiveness.</p>
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<div class="olist arabic">
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<p>An end-user application sends a request, which forms a <em>Command</em> type event, which is transferred to the <em>Event Mesh</em>.</p>
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<p>An end-user application sends an <em>HTTP</em> request to the <em>Event Mesh</em>. Such message can be understood as a <em>Command</em> type event.</p>
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<p>The <em>Event Mesh</em> (Broker) persists the event in a queue (e.g. Kafka).
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After successful persistence <em>Event Mesh</em> returns the success information.
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After <em>Event Mesh</em> persists safely the data, it returns a successful <em>HTTP</em> response with the <code>202 Accepted</code> return code.
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At this point, the operation could already be considered successful, from the end-user point of view.
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It will eventually settle correctly in all downstream systems.</p>
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<p>The dispatch loop continues until the event queue is empty and all the events are processed successfully.
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The failures are being automatically retried by the <em>Event Mesh</em> using exponential backoff algorithm by default.</p>
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The failures are automatically retried by the <em>Event Mesh</em>, with an increasing pauses between retries to avoid overloading the system.</p>
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<h3 id="_work_ledger_analogy"><a class="anchor" href="#_work_ledger_analogy"></a><a class="link" href="#_work_ledger_analogy">2.4. <em>Work Ledger</em> analogy</a></h3>
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<div class="paragraph">
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<p>A good way of thinking about the <em>Event Mesh</em> and its persistent queue backend is the <em>Work Ledger</em> analogy.
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Like in olden days, the clerk was keeping his to-do work in the <em>Work Ledger</em> (e.g. a tray for paper forms).
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Like in the olden days, the clerk kept his to-do work in the <em>Work Ledger</em> (e.g. a tray for paper forms).
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Then he was picking the next form, and processing it, making changes within the physical file cabinets.
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In case of rare and unexpected issues (e.g. Invoicing dept being unavailable), the clerk would just put the data back onto the <em>Work Ledger</em> to be processed later.</p>
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In case of rare and unexpected issues (e.g. invoicing dept being unavailable), the clerk would just put the data back onto the <em>Work Ledger</em> to be processed later.</p>
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<div class="paragraph">
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<p>The <em>Event Mesh</em> is processing the data in very similar fashion.

pull-1/solution-pattern-event-mesh-for-microservices/03-demo.html

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We also need to accept new events coming from the <em>Event Mesh</em>, as the calculated fee will be transmitted as such.</p>
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<div class="paragraph">
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<p>Here&#8217;s the refactored <code>completeTransit</code> method:</p>
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<p>Here&#8217;s the refactored code:</p>
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</div>
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pull-1/solution-pattern-event-mesh-for-microservices/developer-resources.html

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<ul>
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<li>
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<p><a href="https://github.com/cardil/cabs-usvc">cardil / cabs-usvc</a> <em>(The example code used in this solution)</em></p>
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<p><a href="https://github.com/cardil/cabs-usvc">Demo Source</a> <em>(The example code used in this solution)</em></p>
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<p><a href="https://youtu.be/Rc5IO6S6ZOk">youtu.be / Rc5IO6S6ZOk</a> <em>(The talk that served a base for this solution)</em></p>

pull-1/solution-pattern-event-mesh-for-microservices/index.html

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<p>This solution pattern is written to make it obvious and to show simple, yet
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elegant, correct, and comprehensive way of building software, either in
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greenfield or even in legacy projects. This solution leverages the
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<a href="https://www.redhat.com/en/technologies/cloud-computing/openshift/serverless">Red Hat Serverless</a>
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<a href="https://www.redhat.com/en/technologies/cloud-computing/openshift/serverless">Red Hat OpenShift Serverless</a>
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Eventing component, which implements the <a href="https://www.redhat.com/en/topics/integration/what-is-an-event-mesh">Event Mesh</a> pattern.</p>
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<div class="paragraph">

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