![]() Sidekiq is a background processing framework for Ruby. We will show you how to set up each of them starting from nginx. In commercial projects development, we use Monit to monitor and/or control services like Sidekiq, ElasticSearch, Redis server, Rpush, Nginx, PostgreSQL, and some others. Set mailserver some_mail_server Monit configuration and setup If the first one fails, Monit will move to the second one and so on. Further, you can specify several mail servers that will be used to deliver alerts. To enable this option you need to change few lines in the main configuration file.īy default, Monit uses local host for sending emails. If you want to always have the latest updates on the monitored processes - just enable alerts and Monit will start sending emails to a specified address should any errors occur. The port address can also be changed to a custom one if security is a top priority. refining the GUI behaviour especially when data graph become highly populated.After the web interface has been configured it can be accessed by this link.putting URIs on timeseries (or subset of) which is a topic of its own,.deploying the JSON-LD layer on top of the identified silos, applying the ELFIE patterns,.In order to move this demo to production, several aspects need to be covered, such as, ![]() It is also a wonderful discussion material with domain colleagues to demonstrate the usefulness of linked data on their information silos. Here, given that each information element is properly linked to the others through their URIs, data content is properly contextualized and accessible ‘in a click’. Domain experts don’t have to go through various discovery layers (CSW, WFS, SOS/SensorThingAPI). ![]() It provides a really fast way to discover and interact with groundwater monitoring data. Setting up the demo proved that actually trying to consume the JSON-LD files helped design and populate them. JSON-LD content just need to be pasted in the dedicated area. Interaction with the json-ld content can be experienced using BRGM experimental Linked Data Viewer (BLiV) which code is available on ELFIE github repository here. The Borehole is linked to two features, a piezometer, and a geology log. The primary entry point to the data is the Borehole that can be seen in The data index can be seen in github here. The ground water monitoring demo is a mashup involving a graph library (viz.js), a map viewer (leaflet), json-ld library (jsonld.js) and timeseries representation using plot.ly. Given that content is highly typed it was tried to see to what extent content driven widgets could be fed by a data graph (adding features to a map, viewing a timeseries graph). The demonstration makes use of BRGM experimental Linked Data Viewer (BLiV) that was developped as a support to ELFIE activities. It was decided that the observation will be served here following an OGC:SensorThings approach. In this demonstration, SOSA terminology is used to link the piezometer (O&M Sampling feature) to the domain features it monitors (the Aquifer) but also to the observations generated. This use case is meant to demonstrate the combination of the use of W3C:SOSA, tentative OGC:GroundWaterML2 and OGC:ELFIE json-ld contexts to access and navigate though data representing the groundwater monitoring environnement of a given aquifer in France. GroundWater level (OGC SensorThings response to a request for observations).User Storyįrom a given groundwater well, a user needs to access to the sampling strategy and associated observations of a given aquifer monitored in France. The linked data approach it serves as a demonstration artifact on how typed informationĬan trigger type-specific data viewer (here map and time series). (domain expert, machine) can then traverse to the monitoring strategy deployedĪnd then access to the ground water level time series. ![]() This use case is meant to demonstrate how from a given Well URI, any user ELFIE Ground water monitoring Demo Use Case Descrition
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