AWS Big Data Blog

Turn Windows DHCP Server logs into actionable metrics using Amazon Kinesis Agent for Windows

Understanding Windows system and service health on a global scale is challenging. You capture server log data, and then analyze and manipulate the data in real time to create actionable telemetry insights. Amazon Kinesis Agent for Microsoft Windows makes it efficient to ingest Windows server log data into your AWS ecosystem for analysis. This blog […]

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Connecting to and running ETL jobs across multiple VPCs using a dedicated AWS Glue VPC

In this blog post, we’ll go through the steps needed to build an ETL pipeline that consumes from one source in one VPC and outputs it to another source in a different VPC. We’ll set up in multiple VPCs to reproduce a situation where your database instances are in multiple VPCs for isolation related to security, audit, or other purposes.

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Collect, parse, transform, and stream Windows events, logs, and metrics using Amazon Kinesis Agent for Microsoft Windows

A complete data pipeline that includes Amazon Kinesis Agent for Microsoft Windows (KA4W) can help you analyze and monitor the performance, security, and availability of Windows-based services. You can build near-real-time dashboards and alarms for your Windows services. You can also use visualization and business intelligence tools such as Amazon Athena, Kibana, Amazon QuickSight, and […]

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Chasing earthquakes: How to prepare an unstructured dataset for visualization via ETL processing with Amazon Redshift

As organizations expand analytics practices and hire data scientists and other specialized roles, big data pipelines are growing increasingly complex. Sophisticated models are being built using the troves of data being collected every second. The bottleneck today is often not the know-how of analytical techniques. Rather, it’s the difficulty of building and maintaining ETL (extract, transform, and load) jobs using tools that might be unsuitable for the cloud. In this post, I demonstrate a solution to this challenge.

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Performance matters: Amazon Redshift is now up to 3.5x faster for real-world workloads

Since we launched Amazon Redshift, thousands of customers have trusted us to get uncompromising speed for their most complex analytical workloads. Over the course of 2017, our customers benefited from a 3x to 5x performance gain, resulting from short query acceleration, result caching, late materialization, and many other under-the-hood improvements. In this post, we highlight […]

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Dynamically scale up storage on Amazon EMR clusters

In a managed Apache Hadoop environment—like an Amazon EMR cluster—when the storage capacity on your cluster fills up, there is no convenient solution to deal with it. This situation occurs because you set up Amazon Elastic Block Store (Amazon EBS) volumes and configure mount points when the cluster is launched, so it’s difficult to modify […]

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Closing the customer journey loop with Amazon Redshift at Equinox Fitness Clubs

Clickstream analysis tools handle their data well, and some even have impressive BI interfaces. However, analyzing clickstream data in isolation comes with many limitations. For example, a customer is interested in a product or service on your website. They go to your physical store to purchase it. The clickstream analyst asks, “What happened after they […]

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