I want to know what is happening in my processes !
So here they are: my multi-millions of data records, now what?
My impatience is hard to handle: the data is eager to get analysed.
What is next to do ?
… to discuss the possibilities or just a quick chat …
Grafana is most commonly used for visualizing time series data for Internet infrastructure, as server monitoring software, Graphite tools and Graphite dashboard and application analytics but many use it in other domains including industrial sensors, home automation, weather, and process control. Grafana.net consolidates your traditionally disparate data into a single platform. Visualize your local data alongside a hosted and scalable metric store. Share dashboards, panels and apps with the Grafana community – hundreds of thousands strong and create your own integrations for the world to use. Monitor the health your Grafana instances no matter where they live, and get support directly from the core Grafana team.
- Fully-interactive, editable graphs. Multiple Y-axes, Logarithmic scales & options.
- Draw your graphs how you want. Mix lines, points and bars. Mix stacked w/ isolated series.
- Ships with two themes. If you don’t like the default dark theme, switch to a light theme.
- Create variables that are automatically filled with values from your DB.
Generic & Reusable
- You can use variables in your metric queries and panel titles.
- Automatically repeat rows or panels for each selected variable value.
InfluxDB is an open source database written in Go specifically to handle time series data with high availability and high performance requirements. InfluxDB installs in minutes without external dependencies, yet is flexible and scalable enough for complex deployments. InfluxDB is a time series database built from the ground up to handle high write and query loads. It is the second piece of the TICK stack. InfluxDB is meant to be used as a backing store for any use case involving large amounts of timestamped data, including DevOps monitoring, application metrics, IoT sensor data, and real-time analytics.
Key Features Here are some of the features that InfluxDB currently supports that make it a great choice for working with time series data.
- Custom high performance datastore written specifically for time series data. The TSM engine allows for high ingest speed and data compression.
- Written entirely in Go. It compiles into a single binary with no external dependencies.
Simple, high performing write and query HTTP(S) APIs.
- Plugins support for other data ingestion protocols such as Graphite, collectd, and OpenTSDB.
- High availability setup available with Relay.
- Expressive SQL-like query language tailored to easily query aggregated data.
- Tags allow series to be indexed for fast and efficient queries.
- Retention policies efficiently auto-expire stale data.
- Continuous queries automatically compute aggregate data to make frequent queries more efficient.
- Built in web admin interface.
Node-RED is a tool for wiring together hardware devices, APIs and online services in new and interesting ways. Node-RED provides a browser-based flow editor that makes it easy to wire together flows using the wide range nodes in the palette. Flows can be then deployed to the runtime in a single-click.
Browser-based flow editing
Built on Node.js
The light-weight runtime is built on Node.js, taking full advantage of its event-driven, non-blocking model. This makes it ideal to run at the edge of the network on low-cost hardware such as the Raspberry Pi as well as in the cloud. With over 225,000 modules in Node’s package repository, it is easy to extend the range of palette nodes to add new capabilities.
The flows created in Node-RED are stored using JSON which can be easily imported and exported for sharing with others. An online flow library allows you to share your best flows with the world.