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add a couple of aws lambda and web app performance resources
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content/pages/05-deployment/39-aws-lambda.markdown

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how the circuit breaker pattern should be applied to your Lambdas
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and ultimately why low time outs are likely the best way to go to
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prevent your application from becoming entirely unresponsive.
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* [X-rays for Flask and Django Serverless Applications](https://aws.amazon.com/blogs/developer/introducing-aws-x-ray-support-for-python-web-frameworks-used-in-serverless-applications/)
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is an instrumentation, monitoring and debugging service built into AWS
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Lambda specifically for Python [web frameworks](/web-frameworks.html)
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running on the service.
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* [Cutting Through the Layers: AWS Lambda Layers Explained](https://read.iopipe.com/cutting-through-the-layers-aws-lamba-layers-explained-28e8a8d7bda8)
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explains how AWS Lambda now offer a "Bring Your Own Runtime" by exposing
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the layers that were previously controlled exclusively by Amazon. There
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is an overview of the layers and why they matter for customizing your
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functions.

content/pages/06-devops/02-prometheus.markdown

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* This primer on [Prometheus](https://www.kartar.net/2017/10/prometheus/)
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walks through installation, configuration and metrics collection.
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* [Monitoring synchronous Python web apps with Prometheus](https://blog.codeship.com/monitoring-your-synchronous-python-web-applications-using-prometheus/)
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and its
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[asynchronous monitoring](https://blog.codeship.com/monitoring-your-asynchronous-python-web-applications-using-prometheus/)
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counterpart are two tutorials that show how to add middleware
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to your web apps that allows Prometheus metrics collection.
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* [Monitoring with Prometheus](https://kjanshair.github.io/2018/02/20/prometheus-monitoring/)
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provides an overview of the tool and explains how to combine it
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with [Grafana](https://grafana.com/) to visualize the metrics
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that are collected.
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* [Monitor your applications with Prometheus](https://blog.alexellis.io/prometheus-monitoring/)
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is a getting started guide with a walkthrough of how to instrument
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a simple Golang application.

content/pages/06-devops/06-web-app-performance.markdown

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ensure their applications work properly under heavy usage.
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### Web app performance resources
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* [A Primer in Web Performance](https://kiboit.com/performance) is a quick,
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straightforward one pager on why the topic matters and what causes bad
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[task queues](/task-queues.html), [database](/databases.html) optimization
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and [caching](/caching.html).
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* The [Performance Testing Guidance for Web Applications](https://docs.microsoft.com/en-us/previous-versions/msp-n-p/bb924375(v%3dpandp.10)
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book from Microsoft is a gem. There are chapters on foundations of
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performance testing, modeling application usage and many other topics
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that are critical to working on web app performance.
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* [awesome-scalability](https://github.com/binhnguyennus/awesome-scalability)
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provides a list with a crazy number of scaling and performance optimization
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resources and tools by category.
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* [The Infrastructure Behind Twitter: Scale](https://blog.twitter.com/engineering/en_us/topics/infrastructure/2017/the-infrastructure-behind-twitter-scale.html)
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examines the evolution from having to buy your own hardware from vendors
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to run a service to the current days of being able to rely on cloud
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providers for some or all workloads regardless of scale.

theme/templates/table-of-contents.html

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<div class="tc"><a href="/rollbar.html">Rollbar</a></div>
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<div class="tc sn">Sentry</div>
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<div class="tc sn">Scout</div>
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<h4>6.2 <span class="sn">Web App Performance</span></h4>
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<h4>6.2 <a href="/web-app-performance.html">Web App Performance</a></h4>
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<div class="tc"><a href="/logging.html">Logging</a></div>
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<div class="tc"><a href="/caching.html">Caching</a></div>
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<div class="tc"><a href="/web-analytics.html">Web Analytics</a></div>

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