TY - GEN
T1 - From DevOps to NoOps
T2 - 10th International Conference on Cloud Computing and Services Science, CLOSER 2020
AU - Jindal, Anshul
AU - Gerndt, Michael
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - With the rise of the adoption of microservice architecture due to its agility, scalability, and resiliency for building the cloud-based applications and their deployment using containerization, DevOps were in demand for handling the development and operations together. However, nowadays serverless computing offers a new way of developing and deploying cloud-native applications. Serverless computing also called NoOps, offloads management and server configuration (operations work) from the user to the cloud provider and lets the user focus only on the product developments. Hence, there are debates regarding which deployment strategy to use. This research provides a performance comparison of a cloud-native web application along with three different function benchmarks in terms of scalability, reliability, and latency when deployed using DevOps and NoOps deployment strategy. NoOps deployment in this work is achieved using Google Cloud Function and OpenWhisk, while DevOps is achieved using the Kubernetes engine. This research shows that neither of the deployment strategies fits all the scenarios. The experimental results demonstrate that each type of deployment strategy has its advantages under different scenarios. The DevOps deployment strategy has a huge performance advantage (almost 72% lesser 90 percentile response time) for simple web-based requests and requests accessing databases while compute-intensive applications perform better with NoOps deployment. Additionally, NoOps deployment provides better scaling-agility as compared to DevOps.
AB - With the rise of the adoption of microservice architecture due to its agility, scalability, and resiliency for building the cloud-based applications and their deployment using containerization, DevOps were in demand for handling the development and operations together. However, nowadays serverless computing offers a new way of developing and deploying cloud-native applications. Serverless computing also called NoOps, offloads management and server configuration (operations work) from the user to the cloud provider and lets the user focus only on the product developments. Hence, there are debates regarding which deployment strategy to use. This research provides a performance comparison of a cloud-native web application along with three different function benchmarks in terms of scalability, reliability, and latency when deployed using DevOps and NoOps deployment strategy. NoOps deployment in this work is achieved using Google Cloud Function and OpenWhisk, while DevOps is achieved using the Kubernetes engine. This research shows that neither of the deployment strategies fits all the scenarios. The experimental results demonstrate that each type of deployment strategy has its advantages under different scenarios. The DevOps deployment strategy has a huge performance advantage (almost 72% lesser 90 percentile response time) for simple web-based requests and requests accessing databases while compute-intensive applications perform better with NoOps deployment. Additionally, NoOps deployment provides better scaling-agility as compared to DevOps.
KW - Cloud computing
KW - Cloud-native applications
KW - DevOps
KW - Microservices
KW - NoOps
KW - Serverless
UR - http://www.scopus.com/inward/record.url?scp=85104736630&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-72369-9_8
DO - 10.1007/978-3-030-72369-9_8
M3 - Conference contribution
AN - SCOPUS:85104736630
SN - 9783030723682
T3 - Communications in Computer and Information Science
SP - 178
EP - 202
BT - Cloud Computing and Services Science - 10th International Conference, CLOSER 2020, Revised Selected Papers
A2 - Ferguson, Donald
A2 - Pahl, Claus
A2 - Helfert, Markus
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 7 May 2020 through 9 May 2020
ER -