AWS Public Sector Blog
Author: Gabriela Karina Paulus, PhD
Gabriela is a solutions architect at AWS, working within the NPO Sector and focusing on Research customers. She holds a PhD in Molecular Biology and Bioinformatics, a MSc. in Pharmacology, and a BSc. in Biotechnology. Based in the NYC Metropolitan Area, Gabriela is not only a solutions architect, but is also recognized as a genomics expert within AWS. She combines her scientific background with cloud computing expertise to drive innovation and to help scientists and research institutes perform their best work. Gabriela's expertise in cloud technology is complemented by her extensive experience in research, with her previous peer-reviewed publication contributing valuable insights.
Maximizing EC2 Spot Instance reliability for Nextflow on AWS Batch with Memory Machine Batch
AWS partners with providers of innovative solutions such as MemVerge, an AWS Partner Network (APN) Advanced Technology Partner, whose Memory Machine Batch (MMBatch) technology complements AWS Batch by providing advanced checkpointing capabilities for EC2 Spot Instances. In this post, we look at how MemVerge’s technology can overcome the challenges of interrupted pipelines by enabling pipelines that were interrupted mid task to start from where they left off, regardless of Spot Instance reclaims. We’ll also show how MemVerge’s Batch Viewer and proven best practices empower researchers to visualize their workloads, identify bottlenecks, and apply smart strategies that make their pipelines more efficient, resilient, and cloud-optimized.