Deep Dive Amazon Kinesis - d0.awsstatic.com

Deep Dive Amazon KinesisIan Meyers, Principal Solution Architect- Amazon Web ServicesAnalyticsAmazon KinesisManaged Service for Real Time Big Data ProcessingCreate Streams to Produce & Consume DataElastically Add and Remove Shards for PerformanceUse Kinesis Worker Library, AWS Lambda, Apache Spark and Apache Storm to Process DataIntegration with S3, Redshift and Dynamo DBComputeStorageAWS Global InfrastructureDatabaseApp ServicesDeployment & AdministrationNetworkingAnalyticsData [Machine Learning]AWS [Aggregate & De-Duplicate]Data SourcesData SourcesData [Metric Extraction] [Sliding Window Analysis]Data SourcesShard 1 Shard 2 Shard NAvailability ZoneAvailability ZoneAmazon Kinesis DataflowAvailability ZoneBilling AuditorsIncremental Bill ComputationMetering ArchiveBilling ManagementServiceExample Architecture -MeteringStreamsNamed Event Streams of DataShardsYou scale Kinesis streams by adding or removing ShardsEach Shard ingests up to 1MB/sec of data and up to 1000 TPSAll data is stored for 24 hoursPartition KeyIdentifier used for Ordered Delivery & Partitioning of Data across ShardsSequenceNumber of an event as assigned by KinesisAmazon Kinesis ComponentsGetting Data InProducers use a PUT cal

Amazon Kinesis Managed Service for Real Time Big Data Processing Create Streams to Produce & Consume Data Elastically Add and Remove Shards for Performance Use Kinesis Worker Library, AWS Lambda, Apache Spark and Apache Storm to Process Data …

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