AWS Fargate Reviews

Amazon EMR Reviews

AWS Fargate mentions (46)

• A Brief History Of Serverless

  This model was so successful that we started to see others create competitors such as AWS Fargate and Azure Container Instances. - Source: dev.to / about 1 month ago

• Event-Driven Architecture on AWS

  Event Producers: Generate streams of events, which can be implemented using straightforward microservices with AWS Lambda (for serverless computing), Amazon DynamoDB Streams (to captures changes to DynamoDB tables in real-time), Amazon S3 Event Notifications (Notify when certain events occur in S3 buckets) or AWS Fargate (a serverless compute engine for containers). - Source: dev.to / about 1 month ago

• Lambda on hard mode: serverless HTTP in Rust

  I never had a case where cold starts mattered because either 1) it was the kind of service where cold starts intrinsically didnt matter, or 2) we generally had > 1 req/15mins meaning we always had something warm. 3) Also you can pay for provisioned capacity[1] if the cold start thing makes it worth the money, though also just look into fargate[2] if that's the case. [1]:... - Source: Hacker News / 3 months ago

• Serverless Data Processor using AWS Lambda, Step Functions and Fargate on ECS (with Rust 🦀🦀)

  One great option in the serverless world for something like this is to run containers using AWS Fargate (https://aws.amazon.com/fargate/). Fargate is a service from AWS where you don't need to spin up or manage EC2 VMs to get access to compute. Also you don't need to pay for a container orchestration layer. You just provide a docker image and the specs of what you need to run it (cpu, ram, disk, etc) and AWS spins... - Source: dev.to / 5 months ago

• Best Practices for Seamless EKS Cluster Upgrades with Fargate: A Hands-On Guide

  As cloud-native architectures evolve, managing Kubernetes clusters becomes pivotal for maintaining optimal performance and security. Amazon EKS, combined with Fargate for serverless pod execution, offers a powerful solution. In this guide, we'll delve into best practices for EKS cluster upgrades with Fargate, providing a hands-on approach to ensure a seamless transition. Let's embark on the journey of mastering... - Source: dev.to / 6 months ago

Amazon EMR mentions (10)

• 5 Best Practices For Data Integration To Boost ROI And Efficiency

  There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: over 1 year ago

• What compute service i should use? Advice for a duck-tape kind of guy

  I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago

• Processing a large text file containing millions of records.

  This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: about 2 years ago

• How to use Spark and Pandas to prepare big data

  Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago

• Beginner building a Hadoop cluster

  Check out https://aws.amazon.com/emr/. Source: about 2 years ago