My first re:Invent

There were really lots of things to see and experience at the 2015 AWS re:Invent Conference in Las Vegas! Amazon Web Services (AWS) again introduced many new services that will make it easier and faster to implement powerful solutions with emphasis on data and analytics. There are many talented persons presenting great ideas and products! The third party tools and resources for AWS environments are way too numerous to list here, so I will focus on the products that I am excited about and that Amazon is rolling out now or relatively soon.

The service I am most excited about is the up and coming Amazon QuickSight. My initial impression is that this will be a real killer in certain use cases. Amazon itself defines QuickSight as an easy to use, super-fast, cloud-powered business intelligence (BI) service. The service was revealed on Wednesday, October 7th keynote speech and was described more in depth at a separate launch session.

In essence Amazon QuickSight is a managed AWS service that detects data sources in the users account and tries to find relations between these sources. According to the presentations these relations are discovered by examining the data types. I am sure there is an extensive logic behind the system and I am excited to test the system in practice. This, however, is just the beginning. We will provide a deeper analysis after getting some hands on experience with QuickSight.

As the QuickSight service is a BI tool, it also comes with extensive data analyzing and reporting capabilities. After the QuickSight has discovered or you have defined the available data sources it makes suggestions of what to report. This fulfills AWS marketing claim of “begin visualizing your data with actionable insights in about a minute”. The Amazon QuickSight also provides data analysts and developers the ability to drill down in to the data on a very granular level with ease and speed, at least according to the demos shown at the conference.  The QuickSight service achieves its speed by utilizing a new engine called “SPICE”. SPICE is an acronym for “Super-fast, Parallel, In-memory optimized Calculation Engine”. This feature can help us to understand new data and find meaning from it much faster and with less pain than before.  It is interesting to see just how much we can achieve with it.

Real-time data processing and data stream management are hot topics at the moment. AWS introduced new services and enhancements to existing services that will help implementing those use cases. One such newly revealed enhancement is Amazon Kinesis Firehose. Firehose ads in to the Kinesis family and provides the ability to direct your stream directly to S3 or Redshift. Currently only Redshift and S3 are supported but more options are coming in the future. Firehose currently only allows users to direct the data stream in to a single destination. This however is a limitation that can be circumvented with existing tools. In addition to Firehose, Amazon announced another Kinesis related service called Amazon Kinesis Analytics. This service enables users to connect to Kinesis streams or Firehose delivery streams and run standard SQL queries against the data streams. Kinesis Analytics is not yet available and will launch at later point in time.

In addition to new services and features Amazon is also increasing the number of available EC2 instance types. One of the new types is the X1 with a massive 2TB of memory and setup designed for demanding enterprise workloads. While the X1 adds to the extremely large instances, Amazon has not forgotten the little guys. Amazon also announced the T2.nano instance type. The T2.nano is a tiny instance with 1 vCPU and 512 MB of memory capable of building up CPU credits and bursting up processing power when needed (at the cost of CPU credits). The T2.nano is expected to be available later this year and X1 in the first half of the year 2016.

Last but not least I am especially happy to see Python support being added for Lambda as Python has been my preferred programming language lately