2018 · Foundation
Systems & infrastructure
Enterprise systems, security, automation, and operations established the habit of understanding how the whole environment behaves—not just one component.
Platform engineering · cloud infrastructure · data
Joshua
Brewer
I build systems that engineers can depend on.
Platform Engineer focused on cloud infrastructure, automation, observability, security, and data-driven systems. Currently expanding that foundation through an M.S. in Management Information Systems at Texas A&M University.
Systems→Cloud→Platform→Data
7+ yrs Systems, cloud & platform engineering
182+ Production-down AWS cases resolved
Production EKS Operated at Defense Unicorns
M.S. MIS Texas A&M, in progress
The path to platform + data engineering.
Select a milestone for the engineering context behind it.
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- 2018 · Systems & infrastructure
- Enterprise systems, security, automation, and operations established the habit of understanding how the whole environment behaves—not just one component.
- 2022 · AWS & Kubernetes
- Supporting enterprise container environments sharpened a methodical approach to Kubernetes troubleshooting, networking, scaling, upgrades, and documentation.
- 2023 · Platform engineering
- The focus moved from resolving individual operational problems to building reliable, repeatable foundations that help engineering teams deliver.
- 2026 · Texas A&M MS MIS
- Data analytics, warehousing, mining, Python, and SQL extend the platform lens: operational signals can become inputs to better technical and organizational decisions.
- Now · Platform + data engineering
- The current direction combines reliable infrastructure with operational data and information systems thinking—better context for better engineering decisions.
Explore my engineering environment
A sanitized, fictional platform model built from the real open-source stack I operate day to day. Select a layer to see what it does, why it exists, the relevant technologies, and where this connects to my own experience.
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- Cloud — AWS
- Cloud infrastructure creates a resilient foundation for applications and operations. Technologies: AWS · Terraform · IAM. Experience: operates AWS infrastructure in production as a Platform Engineer, architecting EKS, VPC, RDS, S3, and IAM with Terraform across four promotion environments, and previously supported enterprise AWS container environments directly as a Cloud Support Engineer.
- Packaging & delivery — Zarf, Helm, GitLab CI/CD
- Applications are packaged as versioned bundles so the same artifact can be validated once and promoted safely through every environment, including disconnected ones. Technologies: Zarf · Helm · GitLab CI/CD. Experience: contributed CLI enhancements directly to Zarf (public PRs #3568 and #3579), an open-source Kubernetes packaging tool built for air-gapped deployments, and builds Helm-based bundles delivered through CI/CD pipelines.
- Orchestration — EKS / Kubernetes
- Container orchestration and the platform foundation for repeatable workload delivery. Technologies: EKS · Cluster Autoscaler. Experience: manages full lifecycle operations for production EKS clusters, including zero-downtime control-plane upgrades and automated node scaling with Cluster Autoscaler.
- Ingress — Istio
- A controlled entry point that routes traffic, terminates TLS, and makes services discoverable. Technologies: Istio · Ingress Gateway · TLS. Experience: configures Istio ingress gateways and load-balancing for production Kubernetes workloads, and previously diagnosed ingress and routing issues across enterprise clusters as a Cloud Support Engineer.
- Identity
- Centralized authentication lets every application and every tenant trust the same source of truth instead of managing its own users. Technologies: Keycloak · OIDC · SAML. Experience: designed Keycloak-driven, OIDC-based identity mapping for a multi-tenant observability platform, and mentored teammates on AWS IAM Roles Anywhere CAC trust-anchor configuration.
- Services
- Application workloads are operated through clear interfaces, resource boundaries, and observable behavior. Technologies: Kubernetes · CI/CD · GitOps. Experience: operates production services delivered through GitOps and CI/CD pipelines as part of a live platform engineering role.
- Policy & admission
- Guardrails enforced at admission time catch misconfiguration before it reaches running workloads, instead of relying on after-the-fact audits. Technologies: Pepr · OPA/Rego. Experience: migrated OPA/Rego policy validation into the platform's default infrastructure-as-code stack and shipped JSON schema validation for air-gapped Kubernetes runners, enforcing tagging and configuration contracts across every component.
- Worker capacity
- Compute capacity is planned and scaled so workloads have a reliable place to run. Technologies: Autoscaling · Cluster Autoscaler · Multi-AZ. Experience: diagnosed capacity and autoscaling issues professionally, including the kind of node-capacity exhaustion modeled in this site's Incident Simulator.
- Runtime security
- Continuous scanning and runtime threat detection catch what static checks miss, once workloads are actually running. Technologies: Falco · NeuVector. Experience: integrated Falco runtime threat detection and NeuVector continuous container scanning into a hardened platform baseline aligned to NIST SP 800-53 and CIS benchmarks.
- Observability
- Metrics, logs, and dashboards help engineers move from symptoms to evidence. Technologies: Grafana · Loki · Vector · Prometheus · Splunk. Experience: designed and shipped a multi-tenant observability architecture on Grafana, Loki, and Vector for 13+ vendor teams, migrated Grafana configuration to Terraform for drift detection, and feeds centralized Splunk through Vector pipelines.