AWS consulting and hands-on support

AWS is a public cloud platform used to provision on-demand infrastructure and managed services for building, running, and scaling applications without maintaining physical data centers. It is commonly used by engineering, IT, and data teams to host web applications, modernize legacy systems, and support analytics and machine learning workloads across multiple regions.

AWS environments are typically organized into multiple accounts and isolated networks, with infrastructure defined through automation to improve consistency and governance. It is often integrated into CI/CD workflows so teams can deploy changes across development, staging, and production with repeatable controls; related practices are covered in Platform Engineering.

• Compute, containers, and serverless services for APIs, workers, and batch processing
• Object, block, and file storage for application data, backups, and archives
• Managed databases, caching, and messaging to support core application workflows
• Identity and access management with policy-based permissions and account-level controls
• Monitoring, logging, and alerting for operational visibility and incident response

AWS is a public cloud platform used to provision on-demand infrastructure and managed services for building, running, and scaling applications. It is commonly chosen when teams need global reach, strong service depth, and flexible options for reliability, security, and cost management.

• Broad compute options enable right-sizing for diverse workloads, including VMs, containers, and serverless execution models.
• Global regions and availability zones support high availability designs, disaster recovery strategies, and low-latency deployments.
• Managed data services reduce operational overhead for relational databases, NoSQL, caching, streaming, and analytics pipelines.
• Identity and access controls with IAM and organizations help enforce least privilege, account separation, and centralized governance.
• Network and edge services support segmented architectures, private connectivity, and content delivery for internet-facing systems.
• Infrastructure as code support through CloudFormation and common tooling enables repeatable environments and safer change management.
• Observability primitives for metrics, logs, and traces support incident response workflows and reliability engineering practices.
• Security services for threat detection, encryption, and posture management help meet compliance and reduce attack surface.
• Cost controls such as tagging, budgets, savings plans, and autoscaling help manage spend as usage grows.
• Service integrations and a large ecosystem accelerate delivery for common patterns like event-driven systems and microservices.

AWS fits well for organizations that need a wide selection of managed services and fine-grained control over architecture, but it can introduce complexity in account structure, IAM policy design, and cost governance. Vendor-specific services can also increase switching costs, so portability requirements should be evaluated early.

Common alternatives include Microsoft Azure, Google Cloud Platform (GCP), and Oracle Cloud Infrastructure (OCI).

Our experience with AWS helped us develop repeatable patterns for account architecture, infrastructure automation, and day-2 operations that we use to improve reliability, security, and cost control across client cloud platforms. Across greenfield builds and migrations, we applied the AWS Well-Architected Framework to make production environments more predictable to operate and easier to scale.

Some of the things we did include:

• Designed multi-account landing zones with AWS Organizations, IAM Identity Center, SCP guardrails, centralized logging, and audited access workflows.
• Implemented Infrastructure as Code for VPCs, routing, security groups, and shared services using Terraform with Git-based CI/CD and environment promotion.
• Built container platforms on Kubernetes (EKS), including cluster upgrades, node lifecycle management, autoscaling, and workload isolation patterns.
• Modernized application delivery with automated pipelines (build/test gates, artifact versioning, canary/blue-green releases, and rollback automation).
• Standardized observability using CloudWatch logs/metrics/alarms, distributed tracing, and SLO-oriented alerting; integrated with Prometheus where it matched the operating model.
• Hardened security with least-privilege IAM, KMS encryption, Secrets Manager, WAF protections, and continuous compliance checks against baseline controls.
• Executed migration plans for legacy workloads, including network cutovers, data transfer strategies, and post-migration validation with clear runbooks and ownership boundaries.
• Implemented HA/DR patterns using multi-AZ architectures, backup automation, and cross-region replication aligned to RTO/RPO targets.
• Improved cost and performance through right-sizing, Savings Plans/Reserved Instances, storage tiering, and cost allocation tagging with attribution per environment and team.
• Delivered data foundations on AWS (S3, Glue, Athena, Redshift) and integrated orchestration with Apache Airflow for reliable scheduled and batch workloads.

This experience helped us accumulate significant knowledge across AWS use-cases—from new platform builds to regulated environments and large-scale migrations—and enables us to deliver AWS setups that are secure, observable, maintainable, and cost-aware in day-to-day operations.

Some of the things we can help you do with AWS include:

• Assess your current AWS environment and deliver a prioritized report of reliability, security, and cost opportunities.
• Define an AWS adoption roadmap and landing zone design aligned to your org structure, workload needs, and compliance requirements.
• Implement infrastructure as code (IaC) with Terraform to standardize provisioning, reduce drift, and accelerate delivery.
• Build secure foundations across networking, identity, and encryption (VPC, IAM, KMS) with least-privilege guardrails and clear ownership.
• Automate delivery with CI/CD pipelines, policy checks, and repeatable release patterns to ship changes safely and consistently.
• Establish observability (metrics, logs, traces), alerting, and incident-ready runbooks to improve detection, response, and recovery.
• Optimize performance and cost through right-sizing, autoscaling, and FinOps practices to control spend without sacrificing reliability.
• Harden security posture with centralized logging, baseline controls, and audit-ready evidence aligned to AWS Well-Architected best practices.
• Plan and execute migrations and workload refactors to AWS managed services to reduce operational overhead and improve scalability.
• Enable your team with hands-on training, documentation, and operational checklists so improvements stick long term.