We report the implemented architecture for monitoring the health and the quality of the Son Of X-Shooter (SOXS) spectrograph for the New Technology Telescope in La Silla at the European Southern Observatory. Briefly, we report on the innovative no-SQL database approach used for storing time-series data that best suits for automatically triggering alarm, and report high-quality graphs on the dashboard to be used by the operation support team. The system is designed to constantly and actively monitor the Key Performance Indicators (KPI) metrics, as much automatically as possible, reducing the overhead on the support and operation teams. Moreover, we will also detail about the interface designed to inject quality checks metrics from the automated SOXS Pipeline (Young et al. 2022).
We present development progress of the scheduler for the Son Of X-Shooter (SOXS) instrument at the ESO-NTT 3.58-m telescope. SOXS will be a single object spectroscopic facility, consisting of a two-arms high-efficiency spectrograph covering the spectral range 350-2000 nm with a mean resolving power R≈4500. SOXS will be uniquely dedicated to the UV-visible and near infrared follow up of astrophysical transients, with a very wide pool of targets available from the streaming services of wide-field telescopes, current and future. This instrument will serve a variety of scientific scopes in the astrophysical community, with each scope eliciting its specific requirements for observation planning, that the observing scheduler has to meet. Due to directions from the European Southern Observatory (ESO), the instrument will be operated only by La Silla staff, with no astronomer present on the mountain. This implies a new challenge for the scheduling process, requiring a fully automated algorithm that should be able to present the operator not only with and ordered list of optimal targets, but also with optimal back-ups, should anything in the observing conditions change. This imposes a fast-response capability to the scheduler, without compromising the optimization process, that ensures good quality of the observations. In this paper we present the current state of the scheduler, that is now almost complete, and of its web interface.
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