Kong

I've used more and more of New Relic Insights here in my work at Kong. New Relic Insights is a "time series event database as a service" with a super-easy API for inserting custom events, and a flexible query language for building visualization widgets and dashboards.

I'm a big fan of New Relic Insights when I have data I know I need to analyze, but perhaps I'm not exactly sure how I want to analyze it in the future. For example, at Kong we recently wanted to get some understanding of our open source community's activity on our GitHub repos. I was able to quickly configure GitHub to send webhooks to Zapier , which in turn posted the JSON to New Relic Insights.

Insights is schema-less and configuration-less - just start posting JSON key value pairs, then start querying your data.

Within minutes, data was flowing from GitHub to Insights, and I was building widgets on my Insights dashboard to help my colleagues visualize the activity of our open source community.

#GitHubAnalytics #OpenSourceCommunityAnalytics #CommunityAnalytics #RepoAnalytics

On the marketing team at Kong, we use Trello for tracking our tasks. Other teams use JIRA but we don't need to do any storypoint estimation and don't really operate in sprints, so we find it to be a bit of overkill. Trello has easy-to-configure integrations with most of the tools we use, and a great mobile app which makes it easy to add things to to-do lists even when we aren't in front of our computers. If there's one thing I would add to Trello it would be some kind of time tracking to help us stay focused and to be able to look back on tasks and see how long each one took. It would also be nice if there were an epic equivalent so that we could group cards into projects, but this can sort of be hacked around using lables. Over all we're pretty happy with Trello! Would recommend!

At Kong while building an internal tool, we struggled to route metrics to Prometheus and logs to Logstash without incurring too much latency in our metrics collection.

We replaced nginx with OpenResty on the edge of our tool which allowed us to use the lua-nginx-module to run Lua code that captures metrics and records telemetry data during every request’s log phase. Our code then pushes the metrics to a local aggregator process (written in Go) which in turn exposes them in Prometheus Exposition Format for consumption by Prometheus. This solution reduced the number of components we needed to maintain and is fast thanks to NGINX and LuaJIT.