ICALEPCS2023 - List of Authors (Juerges, T.)

Paper	Title	Page
TH1BCO03	The Tango Controls Collaboration Status in 2023	1100
	T. Juerges SKAO, Macclesfield, United Kingdom G. Abeillé SOLEIL, Gif-sur-Yvette, France R.J. Auger-Williams OSL, St Ives, Cambridgeshire, United Kingdom B. Bertrand, V. Hardion, A.F. Joubert MAX IV Laboratory, Lund University, Lund, Sweden R. Bourtembourg, A. Götz, D. Lacoste, N. Leclercq ESRF, Grenoble, France T. Braun byte physics, Annaburg, Germany G. Cuní, C. Pascual-Izarra, S. Rubio-Manrique ALBA-CELLS, Cerdanyola del Vallès, Spain Yu. Matveev DESY, Hamburg, Germany M. Nabywaniec, T.R. Noga, Ł. Żytniak S2Innovation, Kraków, Poland L. Pivetta Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy
	Since 2021 the Tango Controls collaboration has improved and optimised its efforts in many areas. Not only have Special Interest Group meetings (SIGs) been introduced to speed up the adoption of new technologies or improvements, the kernel has switched to a fixed six-month release cycle for quicker adoption of stable kernel versions by the community. CI/CD provides now early feedback on test failures and compatibility issues. Major code refactoring allowed for a much more efficient use of developer resources. Relevant bug fixes, improvements and new features are now adopted at a much higher rate than ever before. The community participation has also noticeably improved. The kernel switched to C++14 and the logging system is undergoing a major refactoring. Among many new features and tools is jupyTango, Jupyter Notebooks on Tango Controls steroids. PyTango is now easy to install via binary wheels, old Python versions are no longer supported, the build-system is switching to CMake, and releases are now made much closer to stable cppTango releases.
	Slides TH1BCO03 [1.357 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TH1BCO03
About •	Received ※ 05 October 2023 — Revised ※ 24 October 2023 — Accepted ※ 21 November 2023 — Issued ※ 13 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THMBCMO01	New Developements on HDB++, the High-performance Data Archiving for Tango Controls	1190
	D. Lacoste, R. Bourtembourg ESRF, Grenoble, France J. Forsberg MAX IV Laboratory, Lund University, Lund, Sweden T. Juerges SKAO, Macclesfield, United Kingdom J.J.D. Mol ASTRON, Dwingeloo, The Netherlands L. Pivetta, G. Scalamera Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy S. Rubio-Manrique ALBA-CELLS, Cerdanyola del Vallès, Spain
	The Tango HDB++ project is a high performance event-driven archiving system which stores data with micro-second resolution timestamps. HDB++ supports many different backends, including MySQL/MariaDB, TimeScaleDB (a time-series PostgreSQL extension), and soon SQLite. Building on its flexible design, latest developments made supporting new backends even easier. HDB++ keeps improving with new features such as batch insertion and by becoming easier to install or setup in a testing environment, using ready to use docker images and striving to simplify all the steps of deployment. The HDB++ project is not only a data storage installation, but a full ecosystem to manage data, query it, and get the information needed. In this effort a lot of tools were developed to put a powerful backend to its proper use and be able to get the best out of the stored data. In this paper we will present as well the latest developments in data extraction, from low level libraries to web viewer integration such as grafana. Pointing out strategies in use in terms of data decimation, compression and others to help deliver data as fast as possible.
	Slides THMBCMO01 [0.926 MB]
	Poster THMBCMO01 [0.726 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THMBCMO01
About •	Received ※ 05 October 2023 — Revised ※ 24 October 2023 — Accepted ※ 08 December 2023 — Issued ※ 16 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THMBCMO14	Development of the SKA Control System, Progress, and Challenges	1221
	S. Vrcic, T. Juerges SKAO, Macclesfield, United Kingdom
	The SKA Project is a science mega-project whose mission is to build an astronomical observatory that comprises two large radio-telescopes: the SKA-Low Telescope, located in the Inyarrimanha Ilgari Bundara, the CSIRO Murchison Radio-astronomy Observatory in Western Australia, with the observing range 50 to 350 MHz, and the SKA Mid Telescope, located in the Karoo Region, South Africa, with the observing range 350 MHz to 15 GHz. The SKA Global Headquarters is in the Jodrell Bank Observatory, near Manchester, UK. When completed, the SKA Telescopes will surpass existing radio-astronomical facilities not only in the scientific criteria such as sensitivity, angular resolution, and survey speed, but also in the number of receptors and the range of the observing and processing modes. The Observatory, and each of the Telescopes, will be delivered in stages, thus supporting incremental development of the collecting area, signal and data processing capacity, and the observing and processing modes. Unlike scientific capability, which, in some cases, may be delivered in the late releases, the control system is required from the very beginning to support integration and verification. Development of the control system to support the first delivery of the Telescopes (Array Assembly 0.5) is well under way. This paper describes the SKA approach to the development of the Telescope Control System, and discusses opportunities and challenges resulting from the distributed development and staged approach to the Telescope construction.
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THMBCMO14
About •	Received ※ 06 October 2023 — Revised ※ 12 October 2023 — Accepted ※ 12 December 2023 — Issued ※ 22 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THSDSC05	The SKAO Engineering Data Archive: From Basic Design to Prototype Deployments in Kubernetes	1590
	T. Juerges SKAO, Macclesfield, United Kingdom A. Dange Tata Consultancy Services, Pune, India
	During its construction and production life cycles, the Square Kilometre Array Observatory (SKAO) will generate non-scientific, i.e. engineering, data. The sources of the engineering data are either hardware devices or software programs that generate this data. Thanks to the Tango Controls software framework, the engineering data can be automatically stored in a relational database, which SKAP refers to as the Engineering Data Archive (EDA). Making the data in the EDA accessible and available to engineers and users in the observatory is as important as storing the data itself. Possible use cases for the data are verification of systems under test, performance evaluation of systems under test, predictive maintenance and general performance monitoring over time. Therefore we tried to build on the knowledge that other research facilities in the Tango Controls collaboration already gained, when they designed, implemented, deployed and ran their engineering data archives. SKAO implemented a prototype for its EDA, that leverages several open-source software packages, with Tango Controls’ HDB++, the Timescaledb time series database and Kubernetes at its core. In this overview we will answer the immediate question "But why do we not just do, what others are doing?" and explain the reasoning behind our choices in the design and in the implementation.
	Poster THSDSC05 [3.062 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THSDSC05
About •	Received ※ 05 October 2023 — Revised ※ 27 October 2023 — Accepted ※ 05 December 2023 — Issued ※ 11 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

The Tango Controls Collaboration Status in 2023

1100

T. Juerges
SKAO, Macclesfield, United Kingdom
G. Abeillé
SOLEIL, Gif-sur-Yvette, France
R.J. Auger-Williams
OSL, St Ives, Cambridgeshire, United Kingdom
B. Bertrand, V. Hardion, A.F. Joubert
MAX IV Laboratory, Lund University, Lund, Sweden
R. Bourtembourg, A. Götz, D. Lacoste, N. Leclercq
ESRF, Grenoble, France
T. Braun
byte physics, Annaburg, Germany
G. Cuní, C. Pascual-Izarra, S. Rubio-Manrique
ALBA-CELLS, Cerdanyola del Vallès, Spain
Yu. Matveev
DESY, Hamburg, Germany
M. Nabywaniec, T.R. Noga, Ł. Żytniak
S2Innovation, Kraków, Poland
L. Pivetta
Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy

Since 2021 the Tango Controls collaboration has improved and optimised its efforts in many areas. Not only have Special Interest Group meetings (SIGs) been introduced to speed up the adoption of new technologies or improvements, the kernel has switched to a fixed six-month release cycle for quicker adoption of stable kernel versions by the community. CI/CD provides now early feedback on test failures and compatibility issues. Major code refactoring allowed for a much more efficient use of developer resources. Relevant bug fixes, improvements and new features are now adopted at a much higher rate than ever before. The community participation has also noticeably improved. The kernel switched to C++14 and the logging system is undergoing a major refactoring. Among many new features and tools is jupyTango, Jupyter Notebooks on Tango Controls steroids. PyTango is now easy to install via binary wheels, old Python versions are no longer supported, the build-system is switching to CMake, and releases are now made much closer to stable cppTango releases.

Slides TH1BCO03 [1.357 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TH1BCO03

About •

Received ※ 05 October 2023 — Revised ※ 24 October 2023 — Accepted ※ 21 November 2023 — Issued ※ 13 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THMBCMO01

New Developements on HDB++, the High-performance Data Archiving for Tango Controls

1190

D. Lacoste, R. Bourtembourg
ESRF, Grenoble, France
J. Forsberg
MAX IV Laboratory, Lund University, Lund, Sweden
T. Juerges
SKAO, Macclesfield, United Kingdom
J.J.D. Mol
ASTRON, Dwingeloo, The Netherlands
L. Pivetta, G. Scalamera
Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy
S. Rubio-Manrique
ALBA-CELLS, Cerdanyola del Vallès, Spain

The Tango HDB++ project is a high performance event-driven archiving system which stores data with micro-second resolution timestamps. HDB++ supports many different backends, including MySQL/MariaDB, TimeScaleDB (a time-series PostgreSQL extension), and soon SQLite. Building on its flexible design, latest developments made supporting new backends even easier. HDB++ keeps improving with new features such as batch insertion and by becoming easier to install or setup in a testing environment, using ready to use docker images and striving to simplify all the steps of deployment. The HDB++ project is not only a data storage installation, but a full ecosystem to manage data, query it, and get the information needed. In this effort a lot of tools were developed to put a powerful backend to its proper use and be able to get the best out of the stored data. In this paper we will present as well the latest developments in data extraction, from low level libraries to web viewer integration such as grafana. Pointing out strategies in use in terms of data decimation, compression and others to help deliver data as fast as possible.

Slides THMBCMO01 [0.926 MB]

Poster THMBCMO01 [0.726 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THMBCMO01

About •

Received ※ 05 October 2023 — Revised ※ 24 October 2023 — Accepted ※ 08 December 2023 — Issued ※ 16 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THMBCMO14

Development of the SKA Control System, Progress, and Challenges

1221

S. Vrcic, T. Juerges
SKAO, Macclesfield, United Kingdom

The SKA Project is a science mega-project whose mission is to build an astronomical observatory that comprises two large radio-telescopes: the SKA-Low Telescope, located in the Inyarrimanha Ilgari Bundara, the CSIRO Murchison Radio-astronomy Observatory in Western Australia, with the observing range 50 to 350 MHz, and the SKA Mid Telescope, located in the Karoo Region, South Africa, with the observing range 350 MHz to 15 GHz. The SKA Global Headquarters is in the Jodrell Bank Observatory, near Manchester, UK. When completed, the SKA Telescopes will surpass existing radio-astronomical facilities not only in the scientific criteria such as sensitivity, angular resolution, and survey speed, but also in the number of receptors and the range of the observing and processing modes. The Observatory, and each of the Telescopes, will be delivered in stages, thus supporting incremental development of the collecting area, signal and data processing capacity, and the observing and processing modes. Unlike scientific capability, which, in some cases, may be delivered in the late releases, the control system is required from the very beginning to support integration and verification. Development of the control system to support the first delivery of the Telescopes (Array Assembly 0.5) is well under way. This paper describes the SKA approach to the development of the Telescope Control System, and discusses opportunities and challenges resulting from the distributed development and staged approach to the Telescope construction.

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THMBCMO14

About •

Received ※ 06 October 2023 — Revised ※ 12 October 2023 — Accepted ※ 12 December 2023 — Issued ※ 22 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THSDSC05

The SKAO Engineering Data Archive: From Basic Design to Prototype Deployments in Kubernetes

1590

T. Juerges
SKAO, Macclesfield, United Kingdom
A. Dange
Tata Consultancy Services, Pune, India

During its construction and production life cycles, the Square Kilometre Array Observatory (SKAO) will generate non-scientific, i.e. engineering, data. The sources of the engineering data are either hardware devices or software programs that generate this data. Thanks to the Tango Controls software framework, the engineering data can be automatically stored in a relational database, which SKAP refers to as the Engineering Data Archive (EDA). Making the data in the EDA accessible and available to engineers and users in the observatory is as important as storing the data itself. Possible use cases for the data are verification of systems under test, performance evaluation of systems under test, predictive maintenance and general performance monitoring over time. Therefore we tried to build on the knowledge that other research facilities in the Tango Controls collaboration already gained, when they designed, implemented, deployed and ran their engineering data archives. SKAO implemented a prototype for its EDA, that leverages several open-source software packages, with Tango Controls’ HDB++, the Timescaledb time series database and Kubernetes at its core. In this overview we will answer the immediate question "But why do we not just do, what others are doing?" and explain the reasoning behind our choices in the design and in the implementation.

Poster THSDSC05 [3.062 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THSDSC05

About •

Received ※ 05 October 2023 — Revised ※ 27 October 2023 — Accepted ※ 05 December 2023 — Issued ※ 11 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)