This Guidance shows how you can build automated Amazon QuickSight dashboards for all of your Amazon Connect data sources, allowing you to analyze your contact center data. It uses the built-in Amazon Connect data lake as the source for your dashboards, so each dashboard is delivered in sync with your data sources, and it provides advanced historical metrics in QuickSight. By setting up dashboards customized to your business needs, you’ll be able to derive insights to help you improve your contact center’s operations, quality of service, agent training, and the customer experience.

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Architecture Diagram

[Architecture diagram description]

Download the architecture diagram PDF 

Well-Architected Pillars

The AWS Well-Architected Framework helps you understand the pros and cons of the decisions you make when building systems in the cloud. The six pillars of the Framework allow you to learn architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable systems. Using the AWS Well-Architected Tool, available at no charge in the AWS Management Console, you can review your workloads against these best practices by answering a set of questions for each pillar.

The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.

  • This Guidance uses CloudWatch dashboards, which provide actionable insights derived from logs and metrics to help you troubleshoot operational problems. You can set alarms and automated actions to activate at predetermined filters and thresholds. Additionally, this Guidance uses Lambda, a serverless compute service that runs code in response to events and automatically manages the underlying compute resources. Using Lambda, you can extend other AWS services with custom logic in response to certain events, such as modifications to objects in Amazon S3, new streaming events in Kinesis Data Firehose, and new implementation logs in CloudWatch.

    Read the Operational Excellence whitepaper 
  • This Guidance uses QuickSight, which provides a comprehensive set of built-in security features. You can securely manage your users and content with role-based access controls, Microsoft Active Directory integration, CloudTrail auditing, single sign-on, VPC subnets, and data backup. QuickSight is also eligible for The Federal Risk and Authorization Management Program (FedRAMP), the Health Insurance Portability and Accountability Act (HIPAA), the PCI Security Standards Council (PCI DSS), the International Organization for Standardization (ISO), and the Security Operations Center (SOC) to help you meet industry-specific and regulatory requirements. QuickSight also offers row-level security, so dataset owners can control access to data by each row.

    This Guidance also uses CloudTrail to monitor and record account activity, helping you achieve compliance with various regulations, such as SOC, PCI, and HIPAA. Additionally, Amazon S3 maintains various compliance programs, and you can use Amazon S3 Block Public Access to block public access to all of your objects at the bucket or account level.

    Read the Security whitepaper 
  • This Guidance uses EventBridge, which lets you build loosely coupled, event-driven architectures at scale. You can create point-to-point integrations between event producers and consumers, connect AWS services and customer applications as event producers, and invoke millions of events and tasks from a single source. This Guidance also uses Athena, which maintains high availability by using compute resources across multiple facilities, automatically routing queries appropriately if a particular facility is unreachable. Data is also redundantly stored across multiple facilities and multiple devices in each facility. Additionally, Amazon S3, which provides the underlying data store for Athena, has a highly available infrastructure and is designed for durability of 99.999999999% (11 nines) of objects.

    Read the Reliability whitepaper 
  • This Guidance uses QuickSight, a serverless service with an in-memory calculation engine. QuickSight automatically scales to tens of thousands of users and provides consistently fast response times, removing the need to manage servers or scale databases for high workloads. Data Catalog serves as the central metadata repository, facilitating quick searches and queries of multiple datasets without the need to move data once catalogued.

    This Guidance also uses Kinesis Data Streams and Kinesis Data Firehose, fully managed services that run streaming applications on serverless infrastructure and can process any amount of streaming data with low latency. Additionally, Lambda optimizes code implementation time and performance by using the right function memory size, and it responds to high demand in milliseconds.

    Read the Performance Efficiency whitepaper 
  • This Guidance uses QuickSight, Data Catalog, and Amazon S3, which offer usage-based pricing. QuickSight removes the need to purchase thousands of user licenses for large-scale analytics deployments and removes upfront costs and complex capacity planning, with no software or servers to install beforehand. It also offers the SPICE (Super-fast, Parallel, In-memory Calculation Engine) feature, which rapidly performs advanced calculations and serves data, saving costs on Athena Query Scan. Data Catalog offers a free tier for storing up to a million objects, charging $1.00 per 100,000 objects over a million per month. Amazon S3 has no minimum charge and offers storage classes optimized for access patterns and archive needs. Additionally, Amazon S3 Intelligent-Tiering delivers automatic storage cost savings by moving objects to lower cost storage classes.

    Read the Cost Optimization whitepaper 
  • This Guidance uses Amazon S3, which offers a life cycle policy to automatically expire noncurrent data, helping you free up storage space and reduce ongoing cloud storage resources. Additionally, Lambda invokes code only when needed and automatically scales to support the rate of incoming requests, effectively optimizing and minimizing the environmental impact of every workload. It allocates CPU power, network bandwidth, and disk input or output proportional to the amount of memory allocated to the functions.

    Read the Sustainability whitepaper 

Implementation Resources

A detailed guide is provided to experiment and use within your AWS account. Each stage of building the Guidance, including deployment, usage, and cleanup, is examined to prepare it for deployment.

The sample code is a starting point. It is industry validated, prescriptive but not definitive, and a peek under the hood to help you begin.

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This [blog post/e-book/Guidance/sample code] demonstrates how [insert short description].


The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.

References to third-party services or organizations in this Guidance do not imply an endorsement, sponsorship, or affiliation between Amazon or AWS and the third party. Guidance from AWS is a technical starting point, and you can customize your integration with third-party services when you deploy the architecture.

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