Tag: Amazon Kinesis

July 2024: This post was reviewed and updated for accuracy. In February 2019, Amazon Web Services (AWS) announced a new feature in Amazon 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, Firehose allowed only specifying a […]

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 […]

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. 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 […]

Whether you’ve just signed up for your first AWS account or you’ve been with us for some time, there’s always something new to learn as our services evolve to meet the ever-changing needs of our customers. To help ensure you’re set up for success as you build with AWS, we put together this quick reference guide for Big Data training and resources available here on the AWS site.

Over the years, I have developed and created a number of data warehouses from scratch. Recently, I built a data warehouse for the iGaming industry single-handedly. To do it, I used the power and flexibility of Amazon Redshift and the wider AWS data management ecosystem. In this post, I explain how I was able to build a robust and scalable data warehouse without the large team of experts typically needed.

You can now provision and manage resources for Amazon Kinesis Analytics applications using AWS CloudFormation. Kinesis Analytics is the easiest way to process streaming data in real time with standard SQL, without having to learn new programming languages or processing frameworks.

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Nowadays, streaming data is seen and used everywhere—from social networks, to mobile and web applications, IoT devices, instrumentation in data centers, and many other sources. As the […]

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Monitoring your AWS environment is important for security, performance, and cost control purposes. For example, by monitoring […]