Datadog is a monitoring and analytics platform for cloud-scale application infrastructure. Combining metrics from servers, databases, and applications, Datadog delivers sophisticated, actionable alerts, and provides real-time visibility of your entire infrastructure. Datadog includes 100+ vendor-supported, prebuilt integrations and monitors hundreds of thousands of hosts.
Based on our record, locust seems to be a lot more popular than Datadog. While we know about 55 links to locust, we've tracked only 5 mentions of Datadog. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Ideally, if we had access to the underlying infrastructure, we could probably install the Datadog Agent and configure it to send our logs directly to Datadog, or even use AWS Lambda functions or Azure Event Hub + Azure Functions in case we were facing some specific cloud scenarios. - Source: dev.to / 7 months ago
Currently supported : Datadog, Jenkins, DNS, HTTP. Source: over 1 year ago
Datadog is a powerful monitoring and security platform that gives you visibility into end-to-end traces, application metrics, logs, and infrastructure. While Datadog has great documentation on their Kubernetes integration, we've observed that there's some missed nuance that leads to common pitfalls. - Source: dev.to / almost 3 years ago
.. Is to see you email address being silently distributed to every single company that I've watched a talk from. And now suddenly get several promotional spam emails per day from some 4-5 different domains like instana.com, datadoghq.com, snyk.io, cockroachlabs.com (some of them send even multiple emails per day!). Source: almost 3 years ago
We're commonly doing this with logging, using services such as Loggly or DataDog. We're using managed databases, be it on AWS, Heroku or database-vendor-specific solutions. We're storing binaries on S3. Externalising user authentication and authorization might be a good candidate as well. - Source: dev.to / about 3 years ago
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
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