The complexity of applications is continually increasing the need for good logs. This need is not just for debugging purposes but also for gathering insight about the performance and possible issues with an application. The Python standard library is an extensive range of facilities and modules that provide most of the basic logging features. Python programmers are given access to system functionalities they would not otherwise be able to employ.

Thanks to its user-friendliness and popularity in the field of data science, Python is one of the best programming languages for ETL. Still, coding an ETL pipeline from scratch isn’t for the faint of heart — you’ll need to handle concerns such as database connections, parallelism, job scheduling, and logging yourself. The good news is that Python makes it easier to deal with these issues by offering dozens of ETL tools and packages.

Data has gone from scarce, expensive, and hard to find and collect to rich and cheap, hard to process and understand with the digital age. In data science solutions, traditional software was used to capture, store, understand and analyze, but not all verticals of data science are essential for individuals and businesses. So Data visualization comes into play to make your tasks easy.

After building Lightrun for the JVM – an easier way to get a better grasp on production applications written in Java, Scala, and Kotlin – we’re pleased to announce the release of Lightrun’s developer-native observability platform for Python!

We are happy to announce support for Python runtime for Thundra Sidekick. Now, with Thundra's latest release, developers can remotely debug their Python applications using Sidekick’s web applications or the IntelliJ IDEA plugin.

AWS Simple Storage Service (S3) is by far the most popular service on AWS. The simplicity and scalability of S3 made it a go-to platform not only for storing objects, but also to host them as static websites, serve ML models, provide backup functionality, and so much more. It became the simplest solution for event-driven processing of images, video, and audio files, and even matured to a de-facto replacement of Hadoop for big data processing.

Software package repositories are becoming a popular target for supply chain attacks. Recently, there has been news about malware attacks on popular repositories like npm, PyPI, and RubyGems. Developers are blindly trusting repositories and installing packages from these sources, assuming they are secure.

Traditionally an APM tool, Scout has expanded its service offerings to now include error monitoring of Python web applications for more cohesive and actionable observability insights within a single platform. This new feature supports an overall better user experience by eliminating the need for multiple web-application monitoring services; Scout APM with Scout Error Monitoring offers performance and error insight and alerting within a single, integrated dashboard.

We just announced the creation of a new RemoteWrite SDK to support custom metrics from applications using several different languages. This tutorial will give a quick rundown of how to use the Python SDK. Using these integrations, Prometheus users can send metrics directly to Logz.io using the RemoteWrite protocol without sending them to Prometheus first. Each SDK, while for a separate language, is each capable of working with frameworks like Thanos, Cortex, and of course M3DB.