One tool for all your Python performance tracking needs We're building this neat service in Python to ingest data in Elasticsearch from various sources (MySQL, Network Drive, AWS, etc.) for Enterprise Search. Sucking data from a third-party service to Elasticsearch is usually an I/O-bound activity. Your code sits on opened sockets and passes data from one end to the other. That's a great use case for an asynchronous application in Python, but it needs to be carefully crafted.

If you’re new to InfluxDB you might wonder, “Why does InfluxDB have its own query and scripting language (aka Flux)?” You might also be thinking, “InfluxDB has client libraries. Why and when should I use the Python client library and when should I use Flux?” In this post we’ll discuss when developers should use Flux and when they should use Python for developing their IoT applications.

As two of the most popular and practical languages out there, should you choose Java or Python for your next project? Is one of these languages a clear-cut better option? The answer is a long one. According to GitHub’s annual Octoverse report, Python has now climbed to the second most popular language in usage, pushing Java down to third place.

At Lumigo, we keep improving the coverage and quality of our distributed tracing instrumentation to give you, through Lumigo’s transactions, the most accurate and intuitive representation of how your distributed system behaves. In this blog, we cover a recent development for the Amazon SQS instrumentation in Lumigo’s OpenTelemetry distro for Python, providing a seamless experience for a scenario that otherwise would result in confusing, broken transactions and lost insights.

Python has staked its claim as the most popular programming language among developers worldwide. Accessible via Windows, Linux, and Mac, it’s intuitive and easy to read, and its use of maths lends itself perfectly to Python for finance and data analysis.

Profiling is an important tool in every developer’s toolkit because it provides a granular view into the execution of your program from your production environment. This is an important concept, as performance bottlenecks can often be very hard or even impossible to reproduce locally due to external constraints or loads only seen in a production environment. Python is one of the most popular programming languages available, and it is one of the core technologies we use at Sentry.

Not in a reading mood? You also can watch the talk I gave at DjangoCon 2022. One of Sentries core company values is “for every developer”. We want to support every developer out there with our tools. But not every developer uses the newest or widely adopted tech stack, so we also try to support older versions of libraries and frameworks.

Python is one of the most used languages among developers. There are many reasons why python is very famous among developers, which we will discuss in this blog. Due to the fame of python, it is used in many business applications, hence monitoring a python application is crucial. New Relic is one of the oldest monitoring tools for python monitoring. But New Relic competitors are growing rapidly; hence, if you do not like the New Relic user interface, many New Relic alternatives exist.

We eat lots of our own dog food at MetricFire, monitoring our services with a dedicated cluster running the same software. This has worked out really well for us over the years: as our own customer, we quickly spot issues in our various ingestion, storage, and rendering services. It also drives the service status transparency our customers love. Our customers include large multinational coffee brewers, game companies, and other data science/SaaS companies.