Serverless computing for container-based architectures

Alfonso Pérez, Germán Moltó, Miguel Caballer, and Amanda Calatrava. Serverless computing for container-based architectures. Future Generation Computer Systems, 83:50–59, 6 2018.

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Abstract

New architectural patterns (e.g. microservices), the massive adoption of Linux containers (e.g. Docker containers), and improvements in key features of Cloud computing such as auto-scaling, have helped developers to decouple complex and monolithic systems into smaller stateless services. In turn, Cloud providers have introduced serverless computing, where applications can be defined as a workflow of event-triggered functions. However, serverless services, such as AWS Lambda, impose serious restrictions for these applications (e.g. using a predefined set of programming languages or difficulting the installation and deployment of external libraries). This paper addresses such issues by introducing a framework and a methodology to create Serverless Container-awarwe ARchitectures (SCAR). The SCAR framework can be used to create highly-parallel event-driven serverless applications that run on customized runtime environments defined as Docker images on top of AWS Lambda. This paper describes the architecture of SCAR together with the cache-based optimizations applied to minimize cost, exemplified on a massive image processing use case. The results show that, by means of SCAR, AWS Lambda becomes a convenient platform for High Throughput Computing, specially for highly-parallel bursty workloads of short stateless jobs.

BibTeX Entry

@article{Perez2018scc,
   abstract = {New architectural patterns (e.g. microservices), the massive adoption of Linux containers (e.g. Docker containers), and improvements in key features of Cloud computing such as auto-scaling, have helped developers to decouple complex and monolithic systems into smaller stateless services. In turn, Cloud providers have introduced serverless computing, where applications can be defined as a workflow of event-triggered functions. However, serverless services, such as AWS Lambda, impose serious restrictions for these applications (e.g. using a predefined set of programming languages or difficulting the installation and deployment of external libraries). This paper addresses such issues by introducing a framework and a methodology to create Serverless Container-awarwe ARchitectures (SCAR). The SCAR framework can be used to create highly-parallel event-driven serverless applications that run on customized runtime environments defined as Docker images on top of AWS Lambda. This paper describes the architecture of SCAR together with the cache-based optimizations applied to minimize cost, exemplified on a massive image processing use case. The results show that, by means of SCAR, AWS Lambda becomes a convenient platform for High Throughput Computing, specially for highly-parallel bursty workloads of short stateless jobs.},
   author = {Alfonso Pérez and Germán Moltó and Miguel Caballer and Amanda Calatrava},
   doi = {10.1016/j.future.2018.01.022},
   issn = {0167739X},
   journal = {Future Generation Computer Systems},
   month = {6},
   pages = {50-59},
   title = {Serverless computing for container-based architectures},
   volume = {83},
   url = {https://linkinghub.elsevier.com/retrieve/pii/S0167739X17316485},
   year = {2018}
}