AWS re:Invent 2020: Deep dive on AWS Lambda consumers for Amazon Kinesis
AWS released mechanisms for scaling the consumption of Amazon Kinesis Data Streams last year. In this session, dive deep on two different scaling mechanisms. First, learn how Enhanced Fan-Out allows you to scale multiple, independent application AWS Lambda consumers per shard. Second, see how Parallelization Factor allows you to scale an application as multiple concurrent Lambda consumers per shard. This gives users more flexibility as they look to consume from Kinesis Data Streams.
Learn more about re:Invent 2020 at http://bit.ly/3c4NSdY
Subscribe:
More AWS videos http://bit.ly/2O3zS75
More AWS events videos http://bit.ly/316g9t4
#AWS #AWSEvents
Видео AWS re:Invent 2020: Deep dive on AWS Lambda consumers for Amazon Kinesis канала AWS Events
Learn more about re:Invent 2020 at http://bit.ly/3c4NSdY
Subscribe:
More AWS videos http://bit.ly/2O3zS75
More AWS events videos http://bit.ly/316g9t4
#AWS #AWSEvents
Видео AWS re:Invent 2020: Deep dive on AWS Lambda consumers for Amazon Kinesis канала AWS Events
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
AWS re:Invent 2020: AWS Lambda – Part 1: Optimizing your serverless applicationsBuild a Real Time Data Streaming System with AWS Kinesis, Lambda Functions and a S3 BucketHigh Performance Data Streaming with Amazon Kinesis: Best Practices and Common PitfallsAWS re:Invent 2020: How Amazon Aurora helps you protect your data from mistakesAWS re:Invent 2020: Top 5 best practices for data streaming with Amazon KinesisKinesis Data Streams to AWS Lambda Example | Kinesis Lambda Consumer | AWS Lambda with Java RuntimeAmazon EMR Deep Dive and Best Practices - AWS Online Tech TalksAWS re:Invent 2020: Observability, logging, and more with AWS Lambda extensionsAmazon Kinesis Consumers ExplainedAWS re:Invent 2020: Applying the principles of the AWS Well-Architected security pillarAWS re:Invent 2020: Scalable serverless event-driven architectures with SNS, SQS & LambdaAWS re:Invent 2020: Testing resiliency using chaos engineeringAWS re:Invent 2019: Supercharge your real-time apps with Amazon ElastiCache (DAT208)AWS re:Invent 2020: AWS Outposts: An in-depth look at hybrid cloud use casesAWS IAM Core Concepts You NEED to KnowAWS re:Invent 2020: Scaling containers on AWSAWS re:Invent 2020: Introducing container image support for AWS LambdaRun and debug Java AWS Lambda locally using SAM CLI commands and Docker in IntelliJ IdeaAWS re:Invent 2020: Application integration patterns for microservices