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, NumPy seems to be a lot more popular than Datadog. While we know about 107 links to NumPy, 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 / 8 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
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / 2 months ago
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / 3 months ago
Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 7 months ago
A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
Zabbix - Track, record, alert and visualize performance and availability of IT resources
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Dynatrace - Cloud-based quality testing, performance monitoring and analytics for mobile apps and websites. Get started with Keynote today!
OpenCV - OpenCV is the world's biggest computer vision library
NewRelic - New Relic is a Software Analytics company that makes sense of billions of metrics across millions of apps. We help the people who build modern software understand the stories their data is trying to tell them.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.