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Finally, let's compare the response time of the requests. For that, we will use Locust , an open source load testing tool. The tests will run for 5 minutes, and will increase 4 requests per second every second until they reach 1000 requests per second. - Source: dev.to / about 2 months ago
Locust: Another open-source tool, Locust is particularly flexible due to its support for Python scripts. It can conduct load tests across multiple machines, making it possible to simulate millions of users simultaneously. An exceptional feature of Locust is its web-based UI, which allows real-time tracking of performance metrics during test execution. - Source: dev.to / about 2 months ago
Locust is a perfect tool to use on such occasion:. - Source: dev.to / 2 months ago
So, in theory, we can handle 300 requests per minute on a single server which was the assumption we started with. After this, I decided to play with this configuration and see what we could achieve. But, to go ahead I need a system to measure the metrics of our load testing. So I quickly set up Locust on my system. Locust is an open-source easy to setup load-testing framework. - Source: dev.to / 2 months ago
The OpenTelemetry Demo is composed of microservices written in different programming languages that talk to each other over gRPC and HTTP; and a load generator which uses Locust to fake user traffic. - Source: dev.to / 6 months ago
Tip: You can use tools like DataDog, perf (Linux), New Relic etc. To monitor cache performance. - Source: dev.to / 19 days ago
Using APM tools like NewRelic, Sentry, Datadog, etc to monitor the performance of your application and while you're on it, they can help you identify N+1 queries. - Source: dev.to / 29 days ago
These tools track server and underlying infrastructure and backend performance. They monitor several metrics, like disk I/O, CPU and memory usage, network traffic, and more. Some examples of these tools include New Relic, Datadog, and AppDynamics. Web administrators can use them to see what's causing slow SRT, like high CPU usage or network traffic. Server-side monitoring tools also provide real-time alerts to... - Source: dev.to / 2 months ago
11 Application performance: Before we even perform a deployment, we should configure monitoring tools like Retrace, DataDog, New Relic, or AppDynamics to look for performance problems, hidden errors, and other issues. During and after the deployment, we should also look for any changes in overall application performance and establish some benchmarks to know when things deviate from the norm. - Source: dev.to / 2 months ago
Recently, we have been experiencing some Latency issues. The reason being the increase in our userbase as more companies are adopting our platform to do their procurement efficiently. Our core product is a monolith rails application served on AWS servers. We use AWS ELB's Application load balancer to swiftly balance the load on multiple servers and increase them when needed. So, these sudden latency issues caused... - Source: dev.to / 2 months ago
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