Tenerity, an engagement company, helps over 2,000 client partners serve millions of customers and improve lifetime customer value with its reward platforms and programs. The company uses proprietary data analysis and technology to offer loyalty discounts and a consumer identity protection service to enhance brand loyalty and revenue.
We’re headquartered in the US but have associates working across 15 countries. We rely heavily on AWS services for our applications, data analysis, and operations.
Using a public cloud like AWS offers many benefits, such as unlimited scalability, flexibility, and outsourced maintenance. And critically, it’s a major efficiency driver—if it’s managed carefully.
Waste-free cloud usage is difficult in organizations with a large cloud footprint, especially fast-growing technology companies. Our AWS services include Amazon Elastic Compute Cloud (Amazon EC2), Amazon Relational Database Service (Amazon RDS), Amazon OpenSearch Service, Amazon ElastiCache, Amazon DynamoDB, Amazon CloudFront, Amazon Simple Storage Service (Amazon S3), and more—and that usage is managed by multiple groups across the organization. It’s easy to miss opportunities for savings.
Our cloud engineering team is responsible for managing these resources, with a focus on cost optimization and security. Having a large set of cloud resources spread over different teams made it impractical for each team to monitor KPIs, which meant we were missing cloud savings opportunities. Teams also had a hard time monitoring and remediating tagging concerns, resulting in compliance issues.
We opted to use Cloud Custodian, an open source, stateless rules engine, to manage our entire cloud estate. It filters, tags, and applies broad actions across resources. Cloud Custodian helps us identify filtering and tagging issues, and other hygiene concerns. But its communication and reporting wasn’t helping us make progress on those items.
In this post, we discuss how Tenerity used Cloud Custodian and Amazon QuickSight to build our business intelligence (BI) dashboard to boost the organization’s efficiency and bottom line.
Seeking an enterprise BI dashboard with easy implementation
Cloud Custodian has no central reporting portal with dashboard views—instead, the app was emailing findings and Excel files to multiple teams responsible for the services. This meant each team needed to manage multiple copies of the reports without a centralized view. Emails notoriously get lost or ignored, and the remediation actions required weren’t occurring in a systematic way.
We needed a BI dashboard that would be easy to integrate with other AWS services and tools, and show findings such as compliance monitoring logs based on custom rules and increase the visibility across cloud environments.
We couldn’t find tools available that offer an out-of-the-box, cost-effective solution that provides the level of detail Cloud Custodian gives us with a way to easily share findings across an organization. So we researched some dashboard tools and quickly discovered QuickSight to complement our Cloud Custodian offering. It was the easiest, fastest, and most cost-effective choice.
QuickSight allowed for all the Cloud Custodian data to be available in a central location, with the ability to apply filtering at a business unit level so that our teams can focus on the data relevant to them.
An architecture for cloud savings
Here’s how we use Cloud Custodian and QuickSight.
Cloud Custodian uses AWS APIs to pull in large quantities of complex data. Cloud Custodian reports on this in Excel files, one for each of our eight business units. Each business unit has a tag compliance tab with approximately 4,500 rows of data. There’s also an unused resources table with approximately 13,000 rows.
Reports are saved in Amazon S3 and then pulled into Amazon Athena through an AWS Glue crawler. QuickSight uses SPICE (Super-fast, Parallel, In-memory Calculation Engine), a robust in-memory engine engineered to rapidly perform advanced calculations and serve data. These reports are ingested into a centralized reporting dashboard, which makes them available as scheduled reports. The following diagram illustrates this workflow.
Users can filter reports to a business unit level so they only see the items their team is responsible for. The dashboard provides high-level alerts, as shown in the following screenshot.
Users can click on the alerts to get the appropriate level of detail to make decisions and take action.
This balances both worlds: we have a large, complex view of our whole AWS estate, and we don’t lose key details that could be buried in the data—it’s there when users need it.
The reporting functions of QuickSight also make it easy to send reporting snapshots with the appropriate level of detail to various stakeholders up and down our organization.
QuickSight allows for a centralized view of a large quantity of detailed, complex data from across our whole AWS estate. It’s a manageable solution that scales across the multiple business units responsible for our cloud services, helping us identify savings opportunities and maintain cloud tagging compliance.
What’s next
The dashboard is in the earliest stages of adoption, and it’s currently being used by 25 people in the cloud engineering team and five engineering leads, but we plan on rolling it out to more users. We are considering configuring QuickSight access through AWS IAM Identity Center (successor to AWS Single Sign On) to allow administrators and users to log in with their existing AWS credentials. For more information, refer to Configuring QuickSight access through IAM Identity Center.
We’re excited about QuickSight’s speed and out-of-the-box dashboards that are easy to customize. This implementation has established a framework for future dashboards for use cases that haven’t been defined yet.
Conclusion
QuickSight allowed us to turn a mass of data into a usable dashboard, allowing us to save money on our cloud accounts and easily manage tagging compliance and hygiene. As an AWS tool, it integrated seamlessly with our expansive AWS Cloud services and tools footprint. It automatically scales to hundreds of thousands of users without the need to set up, configure, or manage your own servers. And with pay-per-session pricing, the implementation was fast and cost-effective, requiring minimal technical resources and skill. We customized prebuilt dashboards to our purposes and quickly saw value from the combination of Cloud Custodian and QuickSight.
To learn more about how QuickSight can help you build a powerful BI dashboard quickly and cost-effectively, visit Amazon QuickSight.
About the Authors
Abhishek Jain is the Director of Cloud Engineering at Tenerity, where he spearheads the development and optimization of cloud functions. With a wealth of experience in building robust cloud infrastructures, Abhishek is dedicated to unlocking the full potential of cloud technology. As a certified FinOps practitioner, Abhishek specializes in the crucial intersection of cloud financial management and cutting-edge cloud solutions. His mission is to equip businesses with cost-effective, scalable, and secure cloud architectures.
Sam Egerton is a Senior Technical Account Manager at AWS. He has over 14 years of experience in IT, building solutions across multiple industries, specializing in VMware and SAP. At AWS, he focuses on enabling customers technical journeys in the cloud to build highly available and cost-optimized solutions. Outside of work, he enjoys snowboarding and motorsports.
This is a companion discussion topic for the original entry at https://aws.amazon.com/blogs/business-intelligence/tenerity-uses-amazon-quicksight-to-build-an-enterprise-business-intelligence-dashboard-that-saves-the-organization-time-and-money/