Grafana vs. Nagios vs. StatsD

Grafana is our monitoring system, with system and applicative dashboards

Create and view dashboard on Prometheus metrics and Logstash logs.

Grafana takes the data from InfluxDB and presents it in a nice flexible format. Bonus points for built-in alerts and playlists (cycles through different dashboards automatically)

Grafana is used in combination with Prometheus to display the gathered stats and to monitor our physical servers aswell as their virtual applications. We also use Grafana to get notifications about irregularities.

Grafana is used in combination with Prometheus to display the gathered stats and to monitor our physical servers aswell as their virtual applications.

Dynamic GRAPHS!

We use Grafana to view live stats relating to our servers such as memory and CPU usage. We also use Grafana to monitor our gaming servers for data such as latency and player counts. This allows us to generate effective analytics and see when problems arise.

Everyone likes graphs, right?! This isn't a tool we actively use right now, but paired with Prometheus we want to use it to have visual monitors on things like API cluster health, status, queue stats, DB/redis query and cache stats etc.

Each piece of our infrastructure is monitored using Nagios, alerting us immediately if anything goes wrong (hopefully before anyone else notices), and with a level of granularity that really helps in resolving things quickly when things are on fire.

We use Nagios to monitor customer instances of Bridge and proactively alert us about issues like queue sizes, downed services, errors in logs, etc.

Internal IT monitoring.

System, apps, monitoring.

Monitor web servers, databases, utility servers

We use nagios based OpsView to monitor our server farm and keep everything running smoothly.

For the monitoring full stack of the platform.

For system up times

Monitors everything!

We use Nagios to monitor our stack and alert us when problems arise. Nagios allows us to monitor every aspect of each of our servers such as running processes, CPU usage, disk usage, and more. This means that as soon as problems arise, we can detect them and call out an engineer to resolve the issues as soon as possible.

Business and system counters go through StatsD and are pushed to InfluxDB

Arm yourself with sensor all over your application

StatsD is used to track the number of messages we're publishing and the type of realtime subscribers. So it shows the number of longpoll connections, the number of websocket connections etc. It also tracks how Redis is performing.