Problem

Development and pre-production clusters running 24x7 despite being used only during business hours, driving unnecessary cloud spend that grew linearly with tenant count. A recurring cost pattern everyone knew about but nobody had time to fix.

Approach

Built a Lambda-EventBridge automation that scales dev cluster node groups to zero outside business hours and back up on-demand when engineers log in. Combined with namespace-level tagging to enable accurate cost attribution across dozens of tenants, so cost visibility grew with the platform instead of degrading with it. The build-vs-buy call: off-the-shelf solutions existed but locked into their own workflow, whereas the custom Lambda approach was ~200 lines of Python and integrated cleanly with the existing IaC.

Outcome

Problem

A platform-wide mutual TLS initiative needed a certificate authority architecture. The default "secure" answer — a two-tier CA hierarchy — came with a real, non-trivial monthly cost increase over a flatter single-tier setup. This was a decision leadership needed to make with full visibility, not one that should be made silently by an engineer who preferred one option over the other.

Approach

Modeled three concrete options — single-tier CA, standard two-tier hierarchy, and a two-tier hierarchy with an offline root — and presented the actual monthly dollar delta between "secure" and "more secure" alongside the security posture each option represented, framed as a cost-versus-blast-radius tradeoff rather than a technical recommendation. The winning insight: the two-tier-with-offline-root option came in at roughly the same monthly cost as the single-tier flat setup, because the offline root eliminated ongoing subordinate-CA idle costs — so the "more secure" option turned out to be the fiscally reasonable one too, but only after real modeling made that visible.

Outcome

Problem

Sev-1 incidents kept recurring with the same gap: the right people weren't getting looped into the incident channel or the postmortem in time — not from neglect, but because remembering exactly who owns which product area under pressure doesn't scale as a human process. Another wiki reminder wasn't going to fix a problem that was fundamentally about relying on human memory at the worst possible moment.

Approach

Instead of another process document, built the fix into the ticketing system itself: the moment a ticket crosses into the highest severity, it automatically posts a checklist mapped to a maintained product-to-owner table — so the right names show up without anyone needing to remember them. The ownership table is the single source of truth, versioned in git so ownership changes go through review like anything else. The principle: prefer system-level fixes over process-level fixes for anything that has to happen reliably under pressure.

Outcome

Problem

Cloud environments accumulate waste quietly — stopped instances, unattached volumes, empty load balancers, unused databases, orphaned snapshots — and manually auditing all of it across many separate customer environments isn't something anyone can realistically do by hand on a recurring basis.

Approach

Built a Python-based audit tool covering roughly 20 resource categories across compute, networking, storage, and database layers. Accepts a single environment ID or a full list of them, runs the same structured checks against each, and produces a clean categorized report. Ran read-only against production and included per-category confidence levels, so obvious waste (stopped instances for 90+ days) got flagged separately from potential-but-unsure findings (databases with low activity) instead of dumping everything into one undifferentiated list.

Outcome

Problem

A partner integration required encrypted files, uploaded via SFTP, to end up decrypted in a specific storage location for a downstream application. This was being handled with manual aws s3 cp commands every time a new file landed — functional, but a recurring manual chore with an unstated deadline attached to every drop, and a single point of human failure.

Approach

Replaced it with an event-driven pipeline: a new file landing triggers a decryption function that reads the file into memory — deliberately never writing decrypted plaintext to disk — decrypts it with a private key held in a secrets manager, and writes the result to its destination, with failure alerts wired to open a ticket automatically. Used a container-based function rather than a zip-and-layer function specifically because the decryption library needed a real system binary dependency, far more reliable to ship in a container image than to hand-assemble as a layer.

Outcome

Problem

A compliance-audit SaaS product on on-premise infrastructure needed to move to AWS — without weakening its posture, since its own customers were subject to SOC 2 and PCI-DSS audits. The existing infrastructure had no IaC at all: everything was hand-configured on physical servers, so there was no documented ground truth to migrate from.

Approach

Three phases: capture the existing on-prem architecture as Terraform first (which surfaced multiple undocumented dependencies), rebuild the same architecture on AWS with proper VPC/EC2/ELB/Auto Scaling/S3/Lambda/API Gateway foundations, then cut over customer by customer with rollback paths preserved. Compliance was designed in from day one — Rapid7 InsightIDR for SIEM, Nexpose for vulnerability scanning, Palo Alto and Fortinet firewalls managing the hybrid perimeter through the transition.

Outcome

Problem

Operating an enterprise datacenter with 10,000+ physical servers across IBM, Dell, and HP hardware plus EMC, NetApp, and Hitachi storage. At that scale, coordination becomes as much a failure mode as the hardware itself — knowing what depends on what, who's on point, and how to fail over cleanly matters more than any individual tool.

Approach

Ran L2 operations with 24x7 on-call coordinated through a formal Emergency Response Team. Standardized Linux service configuration (NFS, FTP, Postfix, DNS, SMTP) across RHEL, CentOS, SUSE, and Ubuntu so runbooks worked regardless of which OS a given customer's stack ran. The real reliability gains lived in preventive work — capacity forecasting, hardware refresh planning, HA cluster validation — ahead of incidents rather than after them.

Outcome

Problem

Hand-configured infrastructure meant "what's actually in production" and "what's in the documentation" were reliably different things — and nobody was surprised by that, which was the deeper problem. Without a source of truth, every incident started with archaeology, and every change was riskier than it needed to be.

Approach

Treated the transition to IaC as a cultural project, not a technical one. Captured existing state in Terraform without changing anything first, so code matched reality at t=0. Introduced drift detection so hand-changes to the console got flagged within a day and remediated through PR. Console access became break-glass only, tracked with reason and duration. The hardest part wasn't the tooling — it was building the habit that the code is the truth.

Outcome

Problem

A cloud estate with a hand-built Kubernetes cluster, no infrastructure code, no Helm charts, and deployments done by imperative apply with in-place text substitution of image tags — no rollback, no drift detection, no image scanning. Six weeks to build a production-grade platform and migrate the first real application onto it. A short timeline forces real engineering choices; every abstraction has to earn its place.

Approach

Terraform provisions the cluster, node groups, workload identity, add-ons, DNS, and the GitOps controller in a single apply. The GitOps controller then deploys the full platform stack — Istio in ambient mode (chosen over sidecars because per-pod overhead is hard to justify on a small node count), ingress, autoscaler, secret operator, monitoring — in dependency order via sync waves. Applications deploy by pipeline: build, scan, push an immutably tagged image, open a merge request against the GitOps repo. Merging is the deploy. Persistent resources (state bucket, registry) deliberately sit in a separate lifecycle from cluster resources, so a full teardown can never destroy images or state — that's what makes destroy-and-rebuild routine instead of terrifying.

Outcome

Problem

Every application's authentication depended on a single hand-configured VM running several parallel installs of the same software, with no repository describing what was actually live — its working tree held uncommitted local edits. The job: containerize it without breaking any downstream application's login.

Approach

Rebuilt the image with a pinned official base, multi-stage, non-root, key material mounted at runtime, and certificate validation restored on the directory-service client (it had been silently disabled). Replaced hostname-substring environment detection — which defaulted to production for anything unrecognized — with explicit configuration. Extracted live config by instantiating the application's own config class rather than transcribing values, guaranteeing an exact match to what the previous deployment used. One correction along the way: the initial plan was to generate a fresh signing keypair for the new environment — that would have broken login, since the same key both signs assertions and is what they're encrypted to. Caught by comparing the committed certificate against the configured value byte-for-byte, and reused the original instead.

Outcome

Problem

A self-hosted community-edition version control server with no enforced code-owner approvals and no standard for how repositories were created — every new repo was a fresh chance to forget branch protection, environment branches, or permission groups.

Approach

Built a pipeline that provisions a repository — settings, permission groups, environment branches, branch protection, initial files, review gate — in one trigger. The hard part: the community edition doesn't enforce code-owner approvals (a paid-tier feature). Recreated the equivalent as a pipeline job that queries the review API and fails when the only approval belongs to the author. Along the way, API writes against freshly created projects returned success but silently didn't persist, only when called from inside the CI runner — traced to the runner resolving an internal address that reached a different routing path where the new project hadn't yet propagated. Fixed with `git push` for the initial commit (a different network path) and moving config into a separate pipeline stage so scheduling provided the propagation delay, instead of papering over it with a sleep.

Outcome

Problem

Inherited a repository with committed secrets accumulated over years — the kind of situation where "we should rotate those" has been a to-do for so long nobody remembers what was actually leaked. Rotating everything blindly is expensive; rotating nothing is negligent.

Approach

Enumerated committed secrets across the repository's history and classified them by blast radius rather than by "is it a secret." Split findings into three tiers: signing material (rotation requires coordinating every relying service — expensive but critical), routine live-service credentials (rotate promptly), and retired/test-only credentials (revoke, low urgency). Moved credentials staying in service to a managed secret store with operator-based sync, so workloads no longer held their own cloud credentials.

Outcome