Cloud & DevOps Company in Boston

The compliance overlay, not the Terraform, decides where a Boston platform engagement lands. Builds run as a scoped AWS or Azure landing zone build for a Boston Series A or Series B SaaS over eight to fourteen weeks, covering multi-account separation, Terraform modules, GitHub Actions pipelines, Datadog observability, and a 201 CMR 17 WISP overlay, a full Kubernetes platform on EKS or AKS with ArgoCD GitOps, secrets management, policy-as-code, and HIPAA or FFIEC controls, or an ITAR/CMMC 2.0 enclave on AWS GovCloud for the MITRE or Lincoln Lab orbit, where the SSP, POA&M, and continuous monitoring tooling add real scope. Boston rates sit above secondary US markets because of the Akamai, Fidelity, and Datadog talent premium. Fixed-fee proposals tied to milestones, not open T and M.

AWS us-east-1 in Northern Virginia is the right primary for almost every Boston workload. It sits roughly 600km south of Boston with a measured 10 to 15ms latency, carries the deepest catalogue of HIPAA and FedRAMP-eligible managed services, and is the launch region for most new AWS capability. We pair it with us-east-2 in Ohio (around 25ms, 1,300km) as the warm disaster recovery region, which is also the standard pattern for HIPAA-compliant cross-region replication. For federal workloads we run AWS GovCloud (US-East) in Ohio, which carries the ITAR boundary, FedRAMP High authorisation, and DoD Impact Level 4 and 5 eligibility. We avoid us-west-2 as a primary for Boston unless a specific service is region-locked, because the latency hit (around 70ms cross-country) creates real product friction.

FFIEC and SR 11-7 buyers expect a documented landing zone with multi-account separation by environment and business unit, encryption at rest with customer-managed KMS keys, encryption in transit with TLS 1.2 or higher and mutual TLS where supported, immutable audit logging via AWS CloudTrail organisation trails or Azure Activity Logs shipped to a separate logging account, identity federation through Active Directory or Okta with conditional access, and continuous control monitoring via AWS Audit Manager, Azure Defender for Cloud, or Wiz. Model risk under SR 11-7 layers in lineage and challenger model documentation. SEC Reg SCI workloads add resilience and business continuity testing. We map controls to the FFIEC Cybersecurity Assessment Tool maturity tiers and produce the artefacts internal audit, the OCC, and the SEC examiner expect, rather than the generic Well-Architected Review deck.

Yes. MITRE Bedford, MIT Lincoln Laboratory, Draper Laboratory, and the broader Hanscom Air Force Base ecosystem operate under ITAR and EAR export controls, DFARS 252.204-7012 safeguarding rules, and CMMC 2.0 Level 2 or Level 3 obligations for any contractor handling Controlled Unclassified Information (CUI). We build on AWS GovCloud (US-East) or Azure Government Virginia inside an ITAR boundary, ship the System Security Plan (SSP) mapped to the 110 NIST 800-171 controls (plus the 24 additional 800-172 controls at Level 3), produce the POA&M, and instrument continuous monitoring via Splunk Enterprise Security or AWS Audit Manager. US-person-only access is enforced through identity federation. We are not a C3PAO and do not perform the CMMC assessment ourselves, but we deliver the technical and documentation pack that holds up under one.

Vertex, Moderna, Biogen, Takeda, and Sanofi Genzyme buy or build under HIPAA, HITRUST CSF, and 21 CFR Part 11 for any system touching PHI or GxP records. We run infrastructure in AWS us-east-1 or us-east-2 under a HIPAA-eligible account with a signed BAA, encrypt at rest with customer-managed KMS keys, encrypt in transit with TLS 1.2 or higher, and ship audit logging that captures every read and write against PHI to an immutable S3 bucket with Object Lock. HITRUST CSF mappings sit alongside the Terraform. For 21 CFR Part 11 we layer in audit trails on every record change, e-signature workflows with intent capture, and IQ, OQ, and PQ validation documentation. Veeva Vault and LabKey integrations are common scope. Discovery includes an OCR audit readiness review and a HITRUST gap assessment.

We standardise on Kubernetes via EKS, AKS, or GKE depending on the cloud, with ArgoCD or Flux driving GitOps reconciliation from a Git repo as the single source of truth. Helm or Kustomize handles templating, Open Policy Agent or Kyverno enforces policy-as-code (no privileged containers, no public load balancers without an exception, mandatory resource limits, image signature verification via Sigstore Cosign), and external-secrets-operator pulls credentials from AWS Secrets Manager, Azure Key Vault, or HashiCorp Vault rather than embedding them in manifests. Progressive delivery runs through Argo Rollouts with canary or blue-green strategies. Observability is Datadog or Prometheus plus Grafana, with distributed tracing via OpenTelemetry. The reference pattern works at HubSpot, Toast, and Klaviyo scale and ports cleanly into a Fidelity-pattern regulated environment with policy and audit overlays.

Akamai effectively invented the CDN from Cambridge in 1998 and still operates the largest distributed edge platform in the industry. For Boston products that need global low-latency delivery we evaluate Akamai, AWS CloudFront paired with Lambda@Edge or CloudFront Functions, Cloudflare with Workers, and Fastly with Compute@Edge. The right choice depends on the workload: Akamai for the deepest enterprise relationships and the largest PoP footprint, CloudFront for tight AWS integration, Cloudflare for developer experience and Workers, Fastly for edge compute on a real VCL or WASM runtime. We architect origin shielding, cache-key design, signed URLs and signed cookies for paid content, WAF rules aligned to OWASP Top 10, and DDoS protection via AWS Shield Advanced or Cloudflare Magic Transit. Edge cost models are documented per request and per GB so FinOps does not surprise the CFO.

Boston platform teams burn through cloud budget faster than any other category once Kubernetes, data, and AI workloads land in production. We instrument FinOps from day one: AWS Cost and Usage Reports or Azure Cost Management exported to Snowflake or BigQuery, allocation tags enforced via Service Control Policies or Azure Policy (untagged resources get blocked at creation), per-team and per-product unit economics dashboards in Cube, Looker, or Datadog, and Savings Plans, Reserved Instances, and Committed Use Discounts modelled monthly against actual usage. Kubernetes cost allocation uses OpenCost or Kubecost with namespace and label-level granularity. We have driven 25 to 45 percent monthly cloud spend reductions on Boston engagements without service degradation, mostly through right-sizing, S3 storage class transitions, and aggressive Savings Plan coverage rather than glamorous re-architecture.