Cloudwalker Solutions
Stop fighting centralised bottlenecks. Cloudwalker builds AWS-native Data Mesh architectures that let each business domain own, publish, and govern its data products — at scale.
What is Data Mesh
A Data Mesh is an architectural approach that decentralises data ownership to the business domains that produce and understand it best — while keeping governance, security, and quality consistent across the whole organisation.
Cloudwalker's AWS-native Data Mesh implementation puts each domain in its own isolated AWS account with its own pipelines, lake, and reporting layer. A shared Federated Governance Account enforces tagging, access control, and cataloguing through AWS Lake Formation — without a central team becoming the bottleneck.
The reference architecture is already running in production for betting operators processing millions of events per day across multiple jurisdictions and domains.
The problem we solve
Our approach
AWS Lake Formation as the central governance plane. Domain-level and PII tagging via tag-based access control. A governance catalog — the registry of registries — with separation of domain service roles and user roles. No central team gatekeeping: governance is policy, not people.
CloudFormation for all infrastructure-as-code — deterministic, auditable, zero drift. CodePipeline and CodeBuild for automated domain deployments. Each domain deploys independently through its own pipeline. Guardrails are enforced at the pipeline level, not by manual review.
Each business domain gets its own isolated AWS account. Ingestion via DMS CDC, Kinesis Firehose, Lambda, or AppFlow. S3 as the domain data lake. Glue for crawling and ETL. Step Functions for orchestration. Reporting via Redshift, Athena, QuickSight, or Power BI Gateway.
AWS DMS CDC provides low-latency, continuous replication from operational databases without impacting source systems. No big-bang migration — domains migrate at their own pace. Full auditability from source to lake.
Kinesis Firehose and Lambda handle high-velocity event streams — betting ticks, player activity, transaction events — directly into the domain S3 lake. Sub-second latency from operational system to analytics layer.
Each domain exposes data through its choice of consumption layer — Amazon Redshift for heavy SQL analytics, Amazon Athena for ad-hoc S3 querying, QuickSight for embedded BI, and EC2-hosted Power BI Gateway for clients who require PBI.
Engagement model
Current state analysis of data architecture and organisational structure. Domain identification and ownership mapping. Governance gap analysis against AWS Lake Formation capabilities. Recommended target architecture and migration roadmap tailored to your technology stack and team structure.
Federated Governance Account setup — Lake Formation, PII tagging taxonomy, and central catalog. CI/CD Account with CloudFormation stacks, CodePipeline, and CodeBuild pipelines. First Domain Account deployed as a reference implementation with full ingestion, processing, and reporting layers. Operational runbook and team enablement sessions.
Repeatable domain onboarding using CloudFormation templates from Phase 2. Source integration configured per domain — DMS CDC for transactional databases, Firehose for streaming, AppFlow for SaaS sources. Domain-specific Glue processing pipelines and Step Functions orchestration. Reporting layer activated. Each domain is independent from day one.
Industry applications
Built on AWS
Start with a 2-week assessment. We'll map your domains, identify governance gaps, and deliver an architecture blueprint before you commit to a full build.