data pipeline

Aggregating Files in your Data Lake – Part 2

When I ran the Lambda from my previous post against Chariot’s CloudTrail repository, it took almost four minutes to process a single day’s worth of data. That seems like a long time, and as a developer I want to optimize everything I write. In this post I look into analyzing the current runtime, and options for improving it.

Aggregating Files in your Data Lake – Part 1

As I’ve written in the past, large numbers of small files make for an inefficient data lake. But sometimes, you can’t avoid small files. Our CloudTrail repository, for example, has 4,601,675 files as-of this morning, 44% of which are under 1,000 bytes long. In this post, I develop a Lambda-based data pipeline to aggregate these files, storing them in a new S3 location partitioned by date. Along the way I call out some of the challenges that face such a pipeline.

Introducing Team Data

This post is a quick primer on the basic titles and skills best suited to fulfill responsibilities along your company’s data pipeline.

IoT on AWS – Intro to Kinesis

This talk will cover the high-level design of Kinesis, how it scales, how clients can retrieve records that have been stored in it, and the use of Kinesis Analytics to to transform data and extract outliers.