Dumping ongoing results of the spike on top of various logging solutions.

1. 1. 1. 1. Prometheus

1. 1. 1. 1. 1. Pros

• Shared service with backend metrics
• Requires an additional service for long-term metrics storage

1. 1. 1. 1. 1. Cons

• Data model is time-series exclusive
• Pull-based data gathering

1. 1. 1. 1. ElasticSearch

1. 1. 1. 1. 1. Pros

• High advertised performance
• Highest variety of data types and modelling (supports time series data and non-time series data)
• Rich querying possibilities

1. 1. 1. 1. 1. Cons

• High minimum resource requirements (over evaluation-sized clusters)

1. 1. 1. 1. MongoDB

1. 1. 1. 1. 1. Pros

• Supports time series data and non-time series data

1. 1. 1. 1. 1. Cons

• Support for time series data is not native thus needs modeling work
• Grafana/Kibana cannot talk to MongoDB without ugly workarounds
• We can't go with the approach Prometheus storing data in MongoDB since it is not supported

1. 1. 1. 1. InfluxDB

1. 1. 1. 1. 1. Pros

• Long-term storage adapter for Prometheus
• HTTP-based API for push-based metrics gathering
• Flexible querying with direct comparison to SQL

1. 1. 1. 1. 1. Cons

• Focused on time-series data
• No clustering support in OSS offering
• Medium-sized minimum resource requirements