Data Architecture

Time Series, events, logging

• Docker-based

  • NLog + Graylog + Docker: https://sachabarbs.wordpress.com/2020/08/24/setting-up-graylog-for-use-with-nlog/

• Influxdata - TICK Stack: https://www.influxdata.com/time-series-platform/

  • Telegraf
    • RabbitMQ Input Plugin: https://github.com/influxdata/telegraf/tree/master/plugins/inputs/rabbitmq
    • MQTT Consumer Input Plugin: https://github.com/influxdata/telegraf/tree/master/plugins/inputs/mqtt_consumer
      • https://github.com/influxdata/telegraf/issues/4580
    • NB: runs on Windows: https://github.com/influxdata/telegraf/blob/master/docs/WINDOWS_SERVICE.md
  • InfluxDB
  • Chronograf
    • Grafana vs Chronograf: https://community.influxdata.com/t/grafana-and-chronograf-concurrents-what-is-the-difference/8282/2
    • Use cases:
      • Chronograf is better at data exploration and understanding schemas for InfluxDB data.
      • Typically we tell people to use Chronograf to explore and play around with their data. Once they find something they want to be able to check/monitor then you create a Grafana dashboard and/or alert based on that data. If you have to find new data inside Grafana, well it can be painful
  • Kapacitor

• InfluxDB + Grafana + Chronograf: https://medium.com/@xaviergeerinck/how-to-visualize-metrics-with-grafana-and-chronograf-by-using-influxdb-450a6b796710

• TIG Stack (Telegraf/InfluxDB/Grafana) - MQTT -> Telegraf -> InfluxDB:

  • https://xebia.com/blog/use-the-tig-stack-to-create-your-iot-home-automation-dashboards/
  • https://www.andymelichar.com/2017/02/26/iot-data-management-with-the-tig-stack/

• Telegraf + MQTT issues; how to map MQTT topics to InfluxDB tags and measurements?

  • There is a proposal; howvever it is not implemented... As of now, the hack is to consume one's MQTT topics and re-publish them into a new 'unpacked' topic for consumption by Telegraf: My current ugly workaround for this is that I write a small program that extracts fields from the topic and posts them on a new "unpacked" topic with the payload as json. I can then use the datatype json and the "tag_keys" to add specific json fields as tags in influxdb. See https://github.com/influxdata/telegraf/issues/648.

• Grafana vs Kibana: https://logz.io/blog/grafana-vs-kibana/

  • Logs vs. metrics: Grafana is designed for analyzing and visualizing metrics (...). Kibana, on the other hand, runs on top of Elasticsearch and is used primarily for analyzing log messages.

• InfluxDB Articles

  • Processing Time Series Data in Real-Time with InfluxDB and Structured Streaming: https://towardsdatascience.com/processing-time-series-data-in-real-time-with-influxdb-and-structured-streaming-d1864154cf8b
  • InfluxDB Data Retention: https://towardsdatascience.com/influxdb-data-retention-f026496d708f

Big Data, Streaming

Apache Kafka

• Kafka can be used for activity monitoring. The activity could belong to a website or physical sensors and devices. Producers can publish raw data from data sources that later can be used to find trends and pattern. From https://towardsdatascience.com/getting-started-with-apache-kafka-in-python-604b3250aa05
• Getting Started with Kafka & python: https://towardsdatascience.com/getting-started-with-apache-kafka-in-python-604b3250aa05
• Confluent's blog
  • Overview: https://www.confluent.io/blog/stream-data-platform-1/ and https://www.confluent.io/blog/stream-data-platform-2/
  • Kafka for Data Scientists: https://www.confluent.io/blog/putting-power-apache-kafka-hands-data-scientists/

QuasarDB

• https://quasardb.net/
  • .NET Client: https://github.com/bureau14/qdb-api-dotnet
  • Windows Administration: https://github.com/quasar/QuasarRAT
  • QuasarDB + Kafka:
    • https://doc.quasardb.net/master/api/kafka.html
    • https://github.com/bureau14/kafka-connect-qdb
    • https://jujucharms.com/u/bigdata-dev/kafka-quasardb/

Juju (Hadoop platform)

Juju: The reference implementation of the Anssr Data Platform, developed by Juju experts at Spicule.

• https://jujucharms.com/
  • https://jujucharms.com/big-data
  • https://jujucharms.com/how-it-works

Machining Data

• MTConnect vs OPC-UA: https://www.mmsonline.com/columns/the-difference-between-mtconnect-and-opc-ua

MTConnect

OPC-UA

MQTT

MongoDB

• Time-series and MongoDB:

  • https://www.mongodb.com/blog/post/time-series-data-and-mongodb-part-1-introduction. This is the intro article; nothing really useful here...
  • https://www.mongodb.com/blog/post/time-series-data-and-mongodb-part-2-schema-design-best-practices. Interesting concepts:
    • Use WiredTiger engine, not MMAPV1
    • data bucketting,
    • TTL indexes (https://docs.mongodb.com/manual/core/index-ttl/)
    • Collection per block of time
  • https://www.mongodb.com/blog/post/time-series-data-and-mongodb-part-3--querying-analyzing-and-presenting-timeseries-data. Querying:
    • Aggregation Framework
    • Read Only Views (materialized at run-time)

• Articles at red-gate:

  • MongoDB: https://www.red-gate.com/simple-talk/dotnet/net-development/how-to-program-with-mongodb-using-the-net-driver/
  • CQRS (using ASP.NET Core, RabbitMQ and MongoDB): https://www.red-gate.com/simple-talk/dotnet/c-programming/getting-started-with-cqrs-part-1/