Cloud Infrastructure & DevOps: Engineered for Immutable Reliability

After a short paid discovery (typically 1–3 weeks) you receive a fixed price with milestones. Fixed setup per environment plus walkthrough; monthly support optional. Discovery is credited toward the build if you proceed.

AWS CloudFormation is deeply integrated into AWS but restricts your infrastructure definitions strictly to the Amazon ecosystem. Terraform (and its open-source fork OpenTofu) provides a unified declarative syntax and provider ecosystem capable of managing AWS, Google Cloud, Azure, Cloudflare, Datadog, GitHub, and Kubernetes within a single coordinated codebase. By adopting Terraform or OpenTofu, your organization avoids single-vendor cloud lock-in, ensures multi-cloud portability where appropriate, and leverages the world's largest community of pre-audited infrastructure modules. During our engagements, we author clean, modular Terraform/OpenTofu code that your team can run independently without proprietary platform dependencies.

Traditional CI/CD pipelines (like Jenkins or basic GitHub Actions scripts) use a 'push' model: external build runners are granted direct administrative SSH or kubeconfig access to push changes into production clusters, creating significant security exposure if CI runners are compromised. GitOps, conversely, operates on an internal 'pull' model: an agent running inside your Kubernetes cluster (such as ArgoCD) continuously monitors your Git repository for declared state changes. When developers merge an approved pull request, ArgoCD pulls the new configuration and reconciles the cluster automatically. This eliminates external administrative cluster access, provides an immutable cryptographic audit log of all changes in Git, and enables instantaneous one-click rollbacks simply by reverting a Git commit.

Zero-downtime database schema migrations require disciplined architectural sequencing using the Expand-Contract pattern rather than destructive single-step alterations. In Phase One (Expand), we add new nullable database columns or new tables alongside existing structures without breaking running application versions. In Phase Two, application code is deployed that writes to both old and new columns simultaneously while reading from the old structure. In Phase Three, a background data backfill script synchronizes historical records. In Phase Four, code is switched to read from the new structure. Finally, in Phase Five (Contract), old deprecated columns are safely dropped. This process ensures database changes never lock tables or break compatibility with active user traffic.

We ensure structural parity between staging and production by provisioning both from the exact same modular Terraform blueprints, parameterizing only compute instance sizes, replica counts, and storage tiers. To eliminate unnecessary hosting expenses, we deploy staging environments using Kubernetes spot instances and lightweight managed database instances, and configure automated cron lifecycle rules that scale staging workloads to zero outside of normal business operating hours (such as 7:00 PM to 7:00 AM and weekends). This approach provides your developers with an identical testing topology while reducing non-production hosting expenses by over sixty-five percent.

Our FinOps engagement begins with a comprehensive cost audit. We immediately identify and terminate unattached EBS storage volumes, unassociated Elastic IP addresses, abandoned manual RDS snapshots, and outdated development test instances. Next, we rightsize over-provisioned compute resources by analyzing 30-day CPU and memory utilization percentiles, transitioning underutilized workloads to modern ARM-based instances (such as AWS Graviton3) which deliver up to 40% better price-performance. We implement Karpenter for Kubernetes compute to leverage spot instances for non-critical workloads, configure automated S3 intelligent tiering to transition aging data to Glacier storage, and assist leadership in purchasing Savings Plans or Reserved Instances for predictable baseline capacity.

We engineer cloud environments to satisfy enterprise compliance requirements from day one. This includes provisioning multi-account AWS Organizations landing zones that completely isolate production workloads from development and staging environments. We enforce encryption at rest across all databases and object storage buckets using customer-managed AWS KMS keys with automated annual key rotation. We configure AWS CloudTrail to write immutable, tamper-evident audit logs to a locked, separate security account with S3 Object Lock. We enforce multi-factor authentication (MFA) via enterprise Single Sign-On (SSO) with zero permanent IAM user access keys, and implement automated continuous compliance scanning using tools like Trivy and AWS Security Hub.

A disaster recovery plan that has never been tested is merely a theoretical hope. We implement automated multi-region backup architectures leveraging AWS Backup or native database replication. Transaction logs (WAL) are shipped continuously to support Point-in-Time Recovery (PITR) with recovery point objectives (RPO) under five minutes. To verify recovery time objectives (RTO), we engineer automated quarterly disaster recovery drills: an automated CI pipeline restores production database backups into an isolated sandbox environment, runs comprehensive synthetic application validation tests, verifies data integrity, and measures total restoration elapsed time, generating an executive audit report certifying business continuity.

We implement full-stack observability following the OpenTelemetry standard. Application services are instrumented to emit structured logs, metrics, and distributed traces. When a user initiates an action, a unique W3C trace context header propagates across all downstream API gateways, microservices, database queries, and external API calls. These traces are collected and visualized in Grafana Tempo or Datadog, allowing engineers to inspect the exact call hierarchy of slow requests and identify the specific database query or external service causing latency. We establish automated alerting rules on the Four Golden Signals: latency percentiles (p50, p95, p99), traffic volume, error rates (HTTP 5xx), and resource saturation.

Your organization maintains absolute, unconditional ownership of all cloud accounts, infrastructure source code, CI/CD pipeline definitions, and configuration secrets from the very first day. We perform all work directly within your corporate AWS, GCP, or Azure accounts and your corporate GitHub or GitLab repositories. We never utilize intermediary agency hosting accounts or proprietary closed-source deployment wrappers. Upon project handover, full administrative credentials, IAM policies, and comprehensive architectural documentation are verified in your custody with zero ongoing licensing encumbrances or vendor lock-in.

Following production cutover, we provide structured ongoing support agreements tailored to your internal team's capabilities. For organizations with dedicated in-house engineers, we offer tier-three architectural advisory retainers and quarterly security/FinOps reviews. For businesses requiring operational assistance, we offer ongoing DevOps support covering automated dependency security patching, Kubernetes version upgrades, CI/CD pipeline enhancements, and continuous infrastructure optimization. We configure automated alerting through PagerDuty or Opsgenie to ensure rapid triage and resolution of any infrastructure anomalies.

Discovery starts within days of agreement. Builds run in weekly sprints with a demo every week.

You do, under a signed agreement — code, docs and accounts are handed over at the end.