Meltwater is excited to sponsor Brewing Agile in Gothenburg on October 12-13, 2018. This is the 4th year in a row that Meltwater is supporting Brewing Agile, so you can tell that we are honestly excited about this event.
This is the only conference about Agile in Gothenburg, and there are still tickets available, so don’t wait and sign up quickly.
Benthos is a dull and resilient stream processor that solves mundane streaming tasks. Its development is driven by our desire to defer these tasks to a common tool wherever sensible, allowing us to focus on solving more interesting business problems within our stream pipelines. This post explains why we chose to build it.
Love it or hate it, CSV is a format many developers have to deal with at some stage. It’s lightweight and it’s understood by many platforms and humans. However, if you’re using non-ASCII characters (like an umlaut on the word über or accent in José) and you have users viewing your CSV files in Microsoft Excel, things get a bit more complicated.
Most Excel users open CSV files simply by double-clicking the file and waiting for Excel to import it automatically. But if Excel doesn’t decode the CSV file correctly, your data will end up as a garbled mess.
How do we avoid this when generating CSV files in Elixir?
Are you working with an ocean of microservices connected together by a message broker like RabbitMQ? Then there is a chance you have experienced queues filling up and messages not reaching their destination, most likely due to stability issues in your architecture of services.
If you want to know how our engineers investigate such issues, and why they built a tool called RabbitIO that helps them with this, then this post is for you.
Haven’t we all been a bit nervous at times about pressing that “Deploy” button, even with amazing test coverage? Especially in the scary world of microservices (aka distributed systems) where the exact constellation of services and their versions is hard to predict.
In this post I will introduce the Synthetic Monitoring concept, which can make you feel more confident about your production system because you find errors quicker. It focuses on improving your Mean Time to Recovery (MTTR), and gathering valuable metrics on how your whole system behaves.