AWS Compute Blog

Tag: Amazon EC2 Spot Instances

Spark Deployment on Kubernetes Cluster

Running cost optimized Spark workloads on Kubernetes using EC2 Spot Instances

This post is written by Kinnar Sen, Senior Solutions Architect, EC2 Spot  Apache Spark is an open-source, distributed processing system used for big data workloads. It provides API operations to perform multiple tasks such as streaming, extract transform load (ETL), query, machine learning (ML), and graph processing. Spark supports four different types of cluster managers (Spark standalone, Apache […]

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Introducing Spot Blueprints, a template generator for frameworks like Kubernetes and Apache Spark

This post is authored by Deepthi Chelupati, Senior Product Manager for Amazon EC2 Spot Instances, and Chad Schmutzer, Principal Developer Advocate for Amazon EC2 Customers have been using EC2 Spot Instances to save money and scale workloads to new levels for over a decade. Launched in late 2009, Spot Instances are spare Amazon EC2 compute […]

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Proactively manage the Spot Instance lifecycle using the new Capacity Rebalancing feature for EC2 Auto Scaling

By Deepthi Chelupati and Chad Schmutzer AWS now offers Capacity Rebalancing for Amazon EC2 Auto Scaling, a new feature for proactively managing the Amazon EC2 Spot Instance lifecycle in an Auto Scaling group. Capacity Rebalancing complements the capacity optimized allocation strategy (designed to help find the most optimal spare capacity) and the mixed instances policy […]

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Folding@home infectious disease research with Spot Instances

This post was contributed by Jarman Hauser, Jessie Xie, and Kinnar Kumar Sen. Folding@home (FAH) is a distributed computing project that uses computational modeling to simulate protein structure, stability, and shape (how it folds). These simulations help to advance drug discoveries and cures for diseases linked to protein dynamics within human cells. The FAH software crowdsources its distributed […]

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TensorFlow Serving on Kubernetes with Amazon EC2 Spot Instances

This post is contributed by Kinnar Sen – Sr. Specialist Solutions Architect, EC2 Spot TensorFlow (TF) is a popular choice for machine learning research and application development. It’s a machine learning (ML) platform, which is used to build (train) and deploy (serve) machine learning models. TF Serving is a part of TF framework and is […]

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Best practices for handling EC2 Spot Instance interruptions

This post is contributed by Scott Horsfield – Sr. Specialist Solutions Architect, EC2 Spot Amazon EC2 Spot Instances are spare compute capacity in the AWS Cloud available to you at steep discounts compared to On-Demand Instance prices. The only difference between an On-Demand Instance and a Spot Instance is that a Spot Instance can be […]

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Building for Cost optimization and Resilience for EKS with Spot Instances

This post is contributed by Chris Foote, Sr. EC2 Spot Specialist Solutions Architect Running your Kubernetes and containerized workloads on Amazon EC2 Spot Instances is a great way to save costs. Kubernetes is a popular open-source container management system that allows you to deploy and manage containerized applications at scale. AWS makes it easy to run […]

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Cost Optimize your Jenkins CI/CD pipelines using EC2 Spot Instances

Author: Rajesh Kesaraju, Sr. Specialist Solution Architect, EC2 Spot Instances In this blog post, I go over using Amazon EC2 Spot Instances on continuous integration and continuous deployment (CI/CD) workloads, via the popular open-source automation server Jenkins. I also break down the steps required to adopt Spot Instances into your CI/CD pipelines for cost optimization purposes. In this blog, I explain […]

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10 things you can do today to reduce AWS costs

This post is contributed by Shankar Ramachandran, SA Specialist, Cost Optimization Introduction AWS’s breadth of services and pricing options offer the flexibility to effectively manage your costs, and still keep the performance and capacity per your business requirement. While the fundamental process of cost optimization on AWS remains the same – monitor your AWS costs and usage, […]

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Figure 5: Resource Automation using Serverless Scheduler - A deeper look A deeper dive in to Part 2, resource allcoation.

Decoupled Serverless Scheduler To Run HPC Applications At Scale on EC2

This post is written by Ludvig Nordstrom and Mark Duffield | on November 27, 2019 In this blog post, we dive in to a cloud native approach for running HPC applications at scale on EC2 Spot Instances, using a decoupled serverless scheduler. This architecture is ideal for many workloads in the HPC and EDA industries, and […]

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