Tag: Amazon Kinesis

Amazon Kinesis Data Firehose now provides an easy-to-configure and straightforward process for streaming data to a third-party service for analysis, including logs from AWS services. Due to the varying formats and high volume of this data, it’s a complex challenge to identify and correlate key event details and data points to fix issues and improve […]

The value of data is time sensitive. Streaming data services can help you move data quickly from data sources to new destinations for downstream processing. For example, Amazon Kinesis Data Firehose can reliably load streaming data into data stores like Amazon Simple Storage Service (Amazon S3), Amazon Redshift, Amazon Elasticsearch Service (Amazon ES), and Splunk. […]

Building a modern data platform on AWS enables you to collect data of all types, store it in a central, secure repository, and analyze it with purpose-built tools. Yet you may be unsure of how to get started and the impact of certain design decisions. To address the need to provide advice tailored to specific technology and application domains, AWS added the concept of well-architected lenses 2017. AWS now is happy to announce the Analytics Lens for the AWS Well-Architected Framework. This post provides an introduction of its purpose, topics covered, common scenarios, and services included.

Most businesses generate data continuously in real time and at ever-increasing volumes. Data is generated as users play mobile games, load balancers log requests, customers shop on your website, and temperature changes on IoT sensors. You can capitalize on time-sensitive events, improve customer experiences, increase efficiency, and drive innovation by analyzing this data quickly. The […]

Real-time delivery of data and insights enables businesses to pivot quickly in response to changes in demand, user engagement, and infrastructure events, among many others. Amazon Kinesis offers a managed service that lets you focus on building your applications, rather than managing infrastructure. Scalability is provided out-of-the-box, allowing you to ingest and process gigabytes of […]

In February 2019, Amazon Web Services (AWS) announced a new feature in Amazon Kinesis Data Firehose called Custom Prefixes for Amazon S3 Objects. It lets customers specify a custom expression for the Amazon S3 prefix where data records are delivered. Previously, Kinesis Data Firehose allowed only specifying a literal prefix. This prefix was then combined with a static date-formatted prefix to create the […]

In this post, we discuss how you can use Apache Flink and Amazon Kinesis Data Analytics for Java Applications to address these challenges. We explore how to build a reliable, scalable, and highly available streaming architecture based on managed services that substantially reduce the operational overhead compared to a self-managed environment.

This blog post discusses an efficient architecture to stream, analyze, and store Microsoft Exchange Server logs. For frequent queries and operational analytics, we use Amazon Elasticsearch Service (Amazon ES) and Kibana for real-time visualization.

Recently, AWS launched a new feature of AWS Application Auto Scaling that let you define scaling policies that automatically add and remove shards to an Amazon Kinesis Data Stream. For more detailed information about this feature, see the Application Auto Scaling GitHub repository. As your streaming information increases, you require a scaling solution to accommodate […]

AWS re:Invent 2018 is almost here! This post includes a list of Amazon Kinesis sessions, chalk talks, and workshops at AWS re:Invent 2018. You can choose the link next to each session description for the session schedule. Use the information to help schedule your conference week in Las Vegas to learn more about Amazon Kinesis. Sessions ANT208 – […]