A few members of the Scout team had the chance to head to Monitorama in Portland, Oregon this week. For those who do not know what Monitorama is, it is a 3-day, open-source monitoring conference with a single track. There is plenty of time during the breaks to chat with attendees, ask the speakers questions or just catch up on some email.
Today, I’m excited to announce a partnership between Logz.io and Microsoft Azure. With this partnership, Logz.io is now offering Azure customers a fully managed, scalable machine data analytics platform built on ELK and Grafana. What does that mean? Azure customers can now easily deploy, run, and scale ELK without the hassle and pain of maintaining and managing the stack themselves.
What is the most important feature your Node.js application can have? Do you think it’s having fancy fuzzy logic for your full-text search, or maybe using sockets for real-time chats? You tell me. What’s the fanciest, most amazing and sexy feature you can add to your Node.js application?
The growing threat of attacks and data breaches on IT systems has made security monitoring more crucial now than ever before. Organizations of all sizes face risks to their data, and without the proper tools in place, a single attack could pose a severe threat to your operations.
In Parts One and Two of this blog, we looked back at the ongoing open source licensing wars, focusing on the evolving situation between Elastic N.V. and AWS. In this final installment, we’ll offer some opinions on the situation, as well as share our own views on how we’re reacting at Grafana Labs.
Open source software adoption continues to grow within enterprises (even for legacy applications), beyond just startups and born-in-the-cloud software. In this second part of our Kafka monitoring series (see the first part discussing Kafka metrics to monitor), we’ll take a look at some open source tools available to monitor Kafka clusters. We’ll explore what it takes to install, configure, and actually use each tool in a meaningful way.
Where we left off: AWS had taken the Elasticsearch software and launched their own cloud offering in 2015, and Elastic N.V. had doubled down on an “open core strategy.” Once AWS decides to offer a project like Elasticsearch, it immediately becomes a truly formidable competitor to anyone trying to do the same, even the company behind the software itself. AWS has huge scale, operational expertise, and various network effects that really compound.
The emergence of a new breed of commercial open source company, challenging the dominance of public cloud, has set off a licensing war that calls into question the very meaning of open source. We debated this topic at last month’s GrafanaCon Los Angeles, where I participated in a spirited panel. Since then, the battle lines have been redrawn. Last week, Amazon announced its Open Distribution for Elasticsearch. And MongoDB Inc. abandoned OSI approval of its new SSPL license.
In the following example-driven tutorial we will learn how to use Prometheus metrics / OpenMetrics to instrument your code whether you are using Golang, Java, Python or Javascript. We will cover the different metric types and provide readily executable code snippets. Prometheus is an open source time series database for monitoring that was originally developed at SoundCloud before being released as an open source project.
Rapitt built their partner store app on top of Mattermost to create a platform that facilitates local commerce. Rapitt digitally connects local business owners with customers to enable specific use cases and transactions—like storing items for a period of time (e.g., a suitcase) and serving as a key-handling solution (e.g., Airbnb hosts can use Rapitt to provide keys to guests).
