AWS Big Data Blog Month in Review: March 2017
Another month of big data solutions on the Big Data Blog. Please take a look at our summaries below and learn, comment, and share. Thank you for reading!
Analyze Security, Compliance, and Operational Activity Using AWS CloudTrail and Amazon Athena
In this blog post, walk through how to set up and use the recently released Amazon Athena CloudTrail SerDe to query CloudTrail log files for EC2 security group modifications, console sign-in activity, and operational account activity.
Big Updates to the Big Data on AWS Training Course!
AWS offers a range of training resources to help you advance your knowledge with practical skills so you can get more out of the cloud. We’ve updated Big Data on AWS, a three-day, instructor-led training course to keep pace with the latest AWS big data innovations. This course allows you to hear big data best practices from an expert, get answers to your questions in person, and get hands-on practice using AWS big data services.
Analyzing VPC Flow Logs with Amazon Kinesis Firehose, Amazon Athena, and Amazon QuickSight
In this blog post, build a serverless architecture using Amazon Kinesis Firehose, AWS Lambda, Amazon S3, Amazon Athena, and Amazon QuickSight to collect, store, query, and visualize flow logs. In building this solution, you also learn how to implement Athena best practices with regard to compressing and partitioning data so as to reduce query latencies and drive down query costs.
Amazon Redshift Monitoring Now Supports End User Queries and Canaries
The serverless Amazon Redshift Monitoring utility lets you gather important performance metrics from your Redshift cluster’s system tables and persists the results in Amazon CloudWatch. You can now create your own diagnostic queries and plug-in “canaries” that monitor the runtime of your most vital end user queries. These user-defined metrics can be used to create dashboards and trigger Alarms and should improve visibility into workloads running on a Cluster.
Running R on Amazon Athena
In this blog post, connect R/RStudio running on an Amazon EC2 instance with Athena. You’ll learn to build a simple interactive application with Athena and R. Athena can be used to store and query the underlying data for your big data applications using standard SQL, while R can be used to interactively query Athena and generate analytical insights using the powerful set of libraries that R provides. This post has been translated into Japanese.
Top 10 Performance Tuning Tips for Amazon Athena
In this blog post, we review the top 10 tips that can improve query performance. We focus on aspects related to storing data in Amazon S3 and tuning specific to queries. Amazon Athena uses Presto to run SQL queries and hence some of the advice will work if you are running Presto on Amazon EMR. This post has been translated into Japanese.
Big Data Resources on the AWS Knowledge Center
The AWS Knowledge Center answers the questions we receive most frequently from AWS customers. It is a resource for you that is distinct from AWS Documentation, the AWS Discussion Forums, and the AWS Support Center. It covers questions from across every AWS service. This post is an introduction to Big Data resources on the AWS Knowledge Center.
Encrypt and Decrypt Amazon Kinesis Records Using AWS KMS
In this bog post, learn to build encryption and decryption into sample Kinesis producer and consumer applications using the Amazon Kinesis Producer Library (KPL), the Amazon Kinesis Consumer Library (KCL), AWS KMS, and the aws-encryption-sdk. The methods and the techniques used in this post to encrypt and decrypt Kinesis records can be easily replicated into your architecture.
Leave a comment below to let us know what big data topics you’d like to see next on the AWS Big Data Blog.