Vertica is a platform that uses machine learning capabilities to help you analyze large amounts of data. Vertica provides high availability and parallel processing by replicating data onto multiple nodes in a cluster, and uses a column-based data store for efficient querying. You can deploy Vertica in the cloud, on premise, or as a hybrid of the two.

Earlier this month, Ivana Huckova, one of Grafana’s junior developers, wrote an article about how to contribute to Grafana as a junior dev. As an open-source project supported by engineers around the world, Grafana strongly encourages anyone to contribute. And ICYMI, there are many opportunities to help: Testing the UI and reporting issues, finding and fixing bugs, and improving the documentation are just a few.

Sharp growth driven by proven, industry-only solution for reducing end-user experience issues that impact the clinician’s virtual workspace and access to EHR applications and improves patient care.

Instrumenting the performance of custom code (the code you write, not the libraries you require) in web apps has been a thorn in my side for years. Yes, we have a custom instrumentation API, but raise your hand if you enjoy sprinkling your code with this? Anyone? Having a custom code instrumentation blackhole doesn't matter if your app spends almost all of its time in common libraries that Scout instruments by default (ex: ActiveRecord, Redis, View Rendering, and HTTP calls).

Here at Lumigo, we are big fans of serverless. And a big part of working with AWS Lambda involves using many other AWS services. For example, services such as SNS and SQS are often used to chain Lambda functions together. They are essential ingredients of an event-driven architecture, where systems are loosely coupled through events. However, they also pose a challenge to how we test our systems and how to get fast feedback on what’s happening in the system.

In the beginning, there was a developer using Graphite, and he found its user interface lacking. Then he discovered the Kibana project, liked its UI, and forked it. Grafana was born in 2013. “I started Grafana to do something similar as Kibana, but focused on time series metrics. My goal was to make time series data accessible for a wider audience, to make it easier to build dashboards, to make graphs and dashboards more interactive,” says Torkel Ödegaard.