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Amazon Redshift Spectrum: Extending Our Data Warehouse Capabilities

Amazon Redshift is the primary data warehousing solution used at GumGum. Apart from the real time reports which are powered through Druid, Redshift fuels the majority of our reporting capabilities. Being a fully managed solution from Amazon, we do not have to maintain the Redshift cluster, be it the hardware or the redshift engine. Redshift is column oriented and its massively parallel processing architecture (MPP) makes it petabyte scalable. Amazon Redshift also includes Redshift Spectrum which can directly query unstructured data stored in S3.

GumGum is one of the enterprise level customers of AWS. We run our entire infrastructure on AWS. We run thousands of servers on AWS every day. AWS is very essential to GumGum’s success. And that’s why GumGum sent 8 of it’s engineers / engineering leaders to re:Invent this year. And from my personal experience, I think it’s was totally worth it. 

Okta Implementation at GumGum
DEEP LEARNING FOR NATURAL LANGUAGE PROCESSING : PART 2 - RNN
DEEP LEARNING FOR NATURAL LANGUAGE PROCESSING : PART 1 – WORD EMBEDDINGS

Deep Learning is a buzz word that gets thrown around a lot these days. It’s thought of the “next big thing” which has already started turning many heads and convinced many who initially thought of it as a bubble.

Detection is one of many classic computer vision problems that has significantly improved with the adoption of convolutional neural networks (CNNs).  When CNNs rose to popularity for image classification, many relied on crude and expensive preprocessing routines for generating region-proposals.

This is a first post in the series of three posts on GumSmash, an In-House event driven auto-remediation engine based on Ansible, that we developed at GumGum.

GumGum has been nominated for Tech In Motion's 2017 "Timmy" Awards! We would love to have your vote. Please vote once per day throughout this month for Best Tech Startup and Best Tech Manager and be sure to share on social media.

This is the first post in the series of three posts on Kafka Connect Implementation at GumGum. In this post, I have going to explain why we chose to implement Kafka Connect and what impact it had on GumGum’s data processing architecture. 

AWS’s Database Migration Service (DMS) is often misunderstood as a service that can only migrate your data to the cloud. But the service could be very useful for replicating data between the two datastores within the cloud as well. 

Here at GumGum, we build and work on many React JS web applications. As the number of apps grew, we found ourselves writing the same code and components for each app. 

Enabling general log in your MySQL RDS instance can be very useful. Especially for auditing and accountability purposes. It’s usually useful to debug problems too.

Much can be said about the cutting edge technologies developed and used by GumGum, but a core component of GumGum’s business involves the effective display of digital advertisements.

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