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Getting Started with Telegraf

Telegraf is a plugin-driven agent for collecting, processing, aggregating and writing metrics and events. Telegraf ships as a single binary with no external dependencies that runs with a minimal footprint and a plugin system that supports many popular services. Telegraf is used to collect metrics from the system it runs on, applications, remote IoT devices and many other inputs. Telegraf can also capture data from event-driven operations.

Making developers' lives better with Aiven

What is the story behind Aiven? Oskari Saarenmaa (Co-Founder & CEO) and Soumya Bijjal (Director of Product Management), talk about the journey of Aiven and the bright future that lies ahead in the open source industry. You will also hear how Aiven takes the pain away from running cloud data infrastructure and enables customers to drive business results from open source. With Aiven, developers can focus on what they love best: creating applications. No more maintenance headaches!

When Big Data Goes Wrong: 3 Common Issues and Possible Solutions

Our shared future has always been profoundly enigmatic. Hoary seers from days of yore would never have predicted everyday life as it is now. It would have been impossible to guess most of what has already happened in the 21st century. Peering into crystal balls would have proved equally futile. Even an attempt to make well-educated guesses about possible issues with big data would likely have been way off the mark.

Energy Regulators Driving Cloud-First Strategies in Race to Net Zero Carbon

Every government in the world is evaluating the steps necessary to radically reduce carbon emissions. The UK Government has been especially proactive, not just assessing these steps, but rolling out aggressive carbon-control strategies and legislation. Originally, the UK Government’s Climate Change Act 2008 set a goal of an 80 percent reduction in the country’s carbon emissions by 2050.

What Is CI/CD and How to Build ETL Processes

In today’s world of heterogeneous data ecosystems, managing and consuming data can be cumbersome. Organizations often have multiple systems of truth in corresponding to the applications managing the data. While data engineers dream of software that would make it easy to consume and digest different data streams from disparate systems, that scenario rarely comes to fruition.