nClouds | AWS Case Studies AI Innovator

nClouds helps an AI innovator achieve 72% AWS cost savings by replacing Cloudera with Amazon S3, AWS Glue, and Amazon Kinesis.

About AI Innovator

The company is a fast-growth provider of an AI-powered software platform in the media space. It was founded in 2015 and has offices across the US.


AI, Computer Software, Media


United States


Optimize data analytics costs without sacrificing performance.

Featured Services

Amazon Athena, Amazon Simple Storage Service (Amazon S3), AWS Glue, Amazon Kinesis, nOps

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Benefits Summary


72% monthly cost savings.


Fast data ETL.


Better consumability and customization of AI-powered data.


Challenge: Optimize data analytics costs without sacrificing performance.

An AWS Well-Architected Review revealed to the company that data analytics running on the Cloudera platform was driving high costs. While they were satisfied with the performance of the Cloudera platform, they wanted to reduce their data analytics costs without sacrificing performance.

Why AWS and nClouds

The company turned to nClouds, a Premier Consulting Partner and Well-Architected Partner in the AWS Partner Network, to collaborate on an AWS Well-Architected Review based on a set of architectural best practices for reviewing critical workloads running on Amazon Web Services (AWS). The Review revealed opportunities for infrastructure improvement, including cost optimization, security, operational excellence, and reliability.

After the Review, based on nClouds’ AWS technical expertise in data and analytics, the company asked nClouds to help them optimize costs by migrating from the Cloudera platform to an AWS architecture featuring AWS managed services for data analytics with pay-as-you-go pricing.

And, the company asked nClouds to partner with them to enhance security. They implemented security best practices such as enabling MFA on the root; implementing life cycle, MFA, and password policies for all users; disabling or removing all inactive keys; restricting public access to virtual private cloud (VPC) resources; checking for Identity and Access Management (IAM) policies attached to users; and monitoring resources for encryption at rest.

AI Innovator leverages several Amazon services:

  • Amazon API Gateway - Makes it easy for the company’s developers to create, publish, maintain, monitor, and secure APIs at any scale.
  • Amazon Athena - An interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and the company pays only for the queries that are run.
  • Amazon Comprehend - A machine learning-powered service that makes it easy to find insights and relationships in text.
  • Amazon DynamoDB - A key-value and document database that delivers single-digit millisecond performance at any scale.
  • Amazon ElastiCache - Makes it easy for the company to scale out, scale in, and scale up to meet fluctuating application demands.
AWS Partner
  • Amazon Elasticsearch Service - A fully managed service that makes it easy for the company to deploy, secure, and operate Elasticsearch at scale with zero downtime.
  • Amazon Kinesis Data Firehose - Part of the Kinesis streaming data platform, it’s a fully managed service (so that the company doesn’t need to write applications or manage resources) that delivers real-time streaming data.
  • Amazon S3 - A flexible way to store and retrieve data, providing the company with cost optimization, access control, and compliance.
  • Amazon Fargate - Enables the company to run containers without having to manage servers or clusters.
  • Amazon Glue - A fully managed extract, transform, and load (ETL) service that makes it easy for the company to prepare and load their data for analytics.
  • Amazon Lambda - Enables the company to run code without provisioning or managing servers. They only pay for the compute time consumed – there is no charge when code is not running.

The company’s solution stack also includes:

  • nOps - A SaaS cloud management platform for AWS that facilitated the company’s AWS Well-Architected Review with automated discovery and enables them to optimize cost and manage security and compliance for their AWS resources.

nClouds' Solution Architecture for AI Innovator

The company engaged with nClouds to help them optimize their data analytics costs by migrating from the Cloudera platform to an AWS infrastructure featuring AWS Glue, Amazon Athena, and Amazon S3.

Amazon Glue:

AWS Glue ETL service prepares and loads the company’s data for analytics. It structures different formats of datasets in a standard way and puts a metadata layer on top of it (the AWS Glue metadata catalog) so that all data can be accessed in the same way. As a managed service, there are no resources to manage, no upfront costs, and there’s no charge for startup or shutdown time.

Amazon Athena:

Once the data is in the AWS Glue metadata catalog, it is sent to Amazon Athena, which provides significant cost savings and performance gains by compressing, partitioning, or converting data to reduce the amount of data that Athena must scan to execute a query.

Amazon S3:

The company can create policies to move less-frequently-accessed Amazon S3 data to cheaper storage tiers for considerable savings. And, there is no charge for transferring data between Amazon S3 storage options if they are within the same AWS Region. With Amazon S3 Select they can retrieve a subset of data from an object using simple SQL expressions, driving cost savings, and improving performance by up to 400%.1

High-level architecture diagram:

Solution Architecture

The Benefits

Teaming with AI Innovator, nClouds migrated data analytics from Cloudera to AWS. The project has yielded numerous benefits:


72% monthly cost savings.

With AWS Glue, the company pays only for the time their ETL job takes to run. Amazon Athena charges the company only for the queries that they run based on the amount of data scanned by each query. Amazon S3 saves storage costs via S3 Intelligent-Tiering, and data access costs are reduced (by as much as 80%) by using Amazon S3 Select.


Fast extract, transform, load (ETL) of data.

Using AWS Glue, the company’s data is immediately searchable, queryable, and available for ETL. It automates much of the effort in building, maintaining, and running ETL jobs. AWS Glue is serverless, so there is no infrastructure to provision or manage.


Better data consumability and customization.

AWS Glue takes datasets in different formats and converts them into a single, query-optimized format that can be easily consumed by various analytical tools.


1Amazon Web Services, Inc. (2018). Amazon S3 Select Is Now Generally Available.

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