Simple Kubernetes real-time dashboard and management.
Then the next step can be using Docker and Kubernetes. Your application will be running inside the Docker container and Kubernetes will be managing all the resources. So Kubernetes can do already some scaling and allocate more resources to your application when needed. As well you can use Skooner (https://github.com/skooner-k8s/skooner) , a dashboard for Kubernetes. From there you can see if your Kubernetes configuration is optimal or it needs some tweaking (more CPU, more RAM, perhaps bigger disk...).
Scalable user load testing tool written in Python
There are a bunch of load testing tools available that let you throw a bunch of requests at a server and see how it copes, my personal preference is locust.io
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
API Performance Testing Tools: JMeter, Taurus, and BlazeMeter
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How does one benchmark performance for async functions?
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Why am I getting a 403 error when running Locust?
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I’ve learn django and have built projects but what do i need to learn after in order to handle millions of users on my app?
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AWS Compute Optimizer provides Amazon EC2 instance recommendations
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