No measurement no improvement how to define metrics for cicd optimizationShuquan Huang
CI/CD is a software engineering approach where software is made available to end users as soon as it’s implemented and tested. There is no doubt that CI/CD is the key to implement successful DevOps. However, it’s not easy to establish a CI/CD pipeline and even much harder to optimize it. To continuously optimize CI/CD, we should find ways to measure its performance.
In this session, I’ll share how to define metrics for optimizing CI/CD through a case study consisted of Zuul, Jenkins, OpenStack, etc. The goal is to identify and measure the essential parameters that affect the whole process and finally help teams understand what happened during CI/CD, make team members focus on specific improvements. I’ll present a variety of metrics based on my own experience and show you how to create your own.
• How to determine the type of data you need to collect
• Metrics for individual and teams
• Metrics for the response of your features and products
• How to make better product based on your metrics
Frontiers of data-driven property prediction: molecular machine learningIchigaku Takigawa
Innovation Camp 2018 for Computational Materials Science(ICCMS2018)
January 23rd(Tue.)-25th(Thu.), 2018
The Jozankei View Hotel, Sapporo, Hokkaido, Japan.
http://ccms.issp.u-tokyo.ac.jp/events/eventsfolder/ICCMS2018
In materials science, data-centric science is becoming one of the major approaches along with theoretical, experimental, and computational sciences. The main purpose of this camp is that we learn the basics of the machine learning as data-centric science and use it to solve problems in our researches through group works. We will also have lectures on advanced researches in computational and data-centric sciences and discuss future perspectives. Furthermore, we learn innovation minds by inviting lecturers who are at the forefront beyond the industry-government-academia framework.
計算物質科学イノベーションキャンプ2018
物質科学の課題を解決する際、理論科学、実験科学、計算科学に加え、データ科学の活用が盛んになっている。本キャンプでは、そのデータ科学として機械学習の手法を学び、チームでの実習を通し手法を身に着け、各自の研究やプロジェクトの課題解決に役立てることを主目的とする。また、講師を招いて計算科学やデータ科学の最先端の研究成果に関する講義と今後の発展の可能性などについて議論する。さらに、産官学や学問領域を超えて活躍する方々のレクチャーと意見交換などでイノベーションマインドを学ぶ。
How to improve spoken English, by learning online with a native English speaker. Go to www. learnenglishfromenglish.org to learn from CELTA trained native English teachers.
Improve your fluency and confidence with lessons created for your needs, for travelling, business, sport, fashion, and popular culture.
No measurement no improvement how to define metrics for cicd optimizationShuquan Huang
CI/CD is a software engineering approach where software is made available to end users as soon as it’s implemented and tested. There is no doubt that CI/CD is the key to implement successful DevOps. However, it’s not easy to establish a CI/CD pipeline and even much harder to optimize it. To continuously optimize CI/CD, we should find ways to measure its performance.
In this session, I’ll share how to define metrics for optimizing CI/CD through a case study consisted of Zuul, Jenkins, OpenStack, etc. The goal is to identify and measure the essential parameters that affect the whole process and finally help teams understand what happened during CI/CD, make team members focus on specific improvements. I’ll present a variety of metrics based on my own experience and show you how to create your own.
• How to determine the type of data you need to collect
• Metrics for individual and teams
• Metrics for the response of your features and products
• How to make better product based on your metrics
Frontiers of data-driven property prediction: molecular machine learningIchigaku Takigawa
Innovation Camp 2018 for Computational Materials Science(ICCMS2018)
January 23rd(Tue.)-25th(Thu.), 2018
The Jozankei View Hotel, Sapporo, Hokkaido, Japan.
http://ccms.issp.u-tokyo.ac.jp/events/eventsfolder/ICCMS2018
In materials science, data-centric science is becoming one of the major approaches along with theoretical, experimental, and computational sciences. The main purpose of this camp is that we learn the basics of the machine learning as data-centric science and use it to solve problems in our researches through group works. We will also have lectures on advanced researches in computational and data-centric sciences and discuss future perspectives. Furthermore, we learn innovation minds by inviting lecturers who are at the forefront beyond the industry-government-academia framework.
計算物質科学イノベーションキャンプ2018
物質科学の課題を解決する際、理論科学、実験科学、計算科学に加え、データ科学の活用が盛んになっている。本キャンプでは、そのデータ科学として機械学習の手法を学び、チームでの実習を通し手法を身に着け、各自の研究やプロジェクトの課題解決に役立てることを主目的とする。また、講師を招いて計算科学やデータ科学の最先端の研究成果に関する講義と今後の発展の可能性などについて議論する。さらに、産官学や学問領域を超えて活躍する方々のレクチャーと意見交換などでイノベーションマインドを学ぶ。
How to improve spoken English, by learning online with a native English speaker. Go to www. learnenglishfromenglish.org to learn from CELTA trained native English teachers.
Improve your fluency and confidence with lessons created for your needs, for travelling, business, sport, fashion, and popular culture.
Masanori Misono, Kaito Yoshida, Juho Hwang, Takahiro Shinagawa.
Distributed Denial of Service Attack Prevention at Source Machines.
In Proceedings of the 16th IEEE International Conference on Dependable, Autonomic and Secure Computing (DASC 2018), Aug 2018.
http://dx.doi.org/10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00096