This Guidance shows you how to implement a data mesh architecture in the context of building a unified view of an end-customer. Each producer domain will own the data and any third-party applications specific to their domain, exposing them through data catalogs. A person consuming the data can then use the data catalogs to find the data they need about their end-customer. This Guidance uses Amazon Connect and Amazon OpenSearch Service to stream contact center data—such as metrics, segments, events, and cases—for real-time analytics on AWS.

Please note: [Disclaimer]

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.

  • CloudWatch collects metrics about Amazon Connect instances to facilitate monitoring, troubleshooting, and alerts. Amazon Connect agent event streams provide near real-time reporting of agent activity and feed that information into analytics dashboards, helping you manage agent staffing and efficiency. Amazon Connect contact event streams facilitate monitoring. Amazon Connect case event streams can integrate into data lake solutions and dashboards to display case performance metrics, letting you implement business rules or automated actions based on case events.

    OpenSearch Service also provides built-in event monitoring and can automatically send alerts through CloudWatch based on preconfigured thresholds. Additionally, Lambda runs code and extends with other AWS services in response to multiple types of events in addition to automatically managing underlying compute resources.

    Read the Operational Excellence whitepaper 

  • This Guidance uses OpenSearch Service to securely connect applications to the OpenSearch environment, with configured network access using virtual private cloud (VPC) security groups or IP-based access policies. It provides granular permissions for indices, documents, and fields, and it supports built-in encryption for data at rest and in transit. OpenSearch Service systematically detects potential threats (such as cyberattacks or the exposure of confidential data) and reacts to a system’s state using machine learning, alerting, and visualization.

    Read the Security whitepaper 

  • This Guidance uses OpenSearch Service, a fully managed service designed to provide at least 99.9 percent monthly uptime. With the Multi-AZ with Standby deployment option, OpenSearch Service managed clusters are resilient to infrastructure failures like node drops or single Availability Zone (AZ) failures, helping prevent any impact to performance or availability. Additionally, OpenSearch Service provisions all the resources for OpenSearch clusters and launches them in any AWS Region within minutes. It automatically detects and replaces failed OpenSearch nodes, and you can scale your cluster horizontally or vertically—up to 3 PB of data—with virtually zero downtime. With this flexibility, OpenSearch Service can support any workload from single-node development clusters to production-scale multi-node clusters.

    Read the Reliability whitepaper 

  • Amazon Connect Contact Lens uses real-time segment streams that meet ultra-low latency requirements to assist agents on live calls; Amazon Connect voice ID generates events for every transaction and sends them to EventBridge; and Amazon Connect API facilitates reporting at scale. Additionally, Lambda automatically responds to code implementation requests at scale, optimizing implementation time and performance. Kinesis Data Streams and Kinesis Data Firehose capture, transform, and deliver streaming data to storage and analytics services at scale and with low latency.

    Read the Performance Efficiency whitepaper 

  • This Guidance uses UltraWarm storage for OpenSearch Service. This storage tier provides less expensive storage for older and less frequently accessed data while still providing an interactive querying experience. You can retain up to 3 PB of data in a single OpenSearch Service cluster while reducing cost per gigabyte by nearly 90 percent compared to the hot storage tier. Additionally, the cold storage tier lets you securely store and analyze historical logs on demand. It does not use compute when you are not actively performing data analysis, so you can keep your data readily available at low cost.

    Read the Cost Optimization whitepaper 

  • This Guidance uses OpenSearch Service, which offers hot, warm, and cold storage tiers for different access patterns and storage needs. These tiers help you optimize storage space use and reduce ongoing cloud storage resources. Additionally, Lambda supports sustainability by allocating CPU power, network bandwidth, and disk input or output that are proportional to the amount of memory allocated to functions. It invokes code only when needed and automatically scales to support the rate of incoming requests. This helps you effectively optimize and minimize your workload’s environmental impact.

    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.

Open implementation guide
Open sample code on GitHub

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Disclaimer

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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