TY - CHAP
T1 - Dynamic Patterns for Cloud Application Life-Cycle Management
AU - Horn, Geir
AU - Arrieta, Leire Orue Echevarria
AU - Di Martino, Beniamino
AU - Skrzypek, Paweł
AU - Kyriazis, Dimosthenis
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2020.
PY - 2020
Y1 - 2020
N2 - Cloud applications are by nature dynamic and must react to variations in use, and evolve to adopt new Cloud services, and exploit new capabilities offered by Edge and Fog devices, or within data centers offering Graphics Processing Units (GPUs) or dedicated processors for Artificial Intelligence (AI). Our proposal is to alleviate this complexity by using patterns at all stages of the Cloud application life-cycle: Deployment, automatic service discovery, monitoring, and adaptive application evolution. The main idea of this paper is that it is possible to reduce the complexity of composing, deploying, and evolving Cross-Cloud applications using dynamic patterns.
AB - Cloud applications are by nature dynamic and must react to variations in use, and evolve to adopt new Cloud services, and exploit new capabilities offered by Edge and Fog devices, or within data centers offering Graphics Processing Units (GPUs) or dedicated processors for Artificial Intelligence (AI). Our proposal is to alleviate this complexity by using patterns at all stages of the Cloud application life-cycle: Deployment, automatic service discovery, monitoring, and adaptive application evolution. The main idea of this paper is that it is possible to reduce the complexity of composing, deploying, and evolving Cross-Cloud applications using dynamic patterns.
UR - https://www.scopus.com/pages/publications/85074720862
U2 - 10.1007/978-3-030-33509-0_59
DO - 10.1007/978-3-030-33509-0_59
M3 - Chapter
AN - SCOPUS:85074720862
T3 - Lecture Notes in Networks and Systems
SP - 626
EP - 637
BT - Lecture Notes in Networks and Systems
PB - Springer
ER -