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Dev / Platform

Internal developer platforms, golden paths, and the teams building them. How to give developers self-service without losing control.

Pipelines, deployment strategies, ArgoCD, Flux, GitHub Actions, and everything that ships code from a commit to production.

Running K8s at scale — upgrades, multi-tenancy, cost management, and the operational reality behind the abstractions.

Monitoring, tracing, logging, SLOs, incident response, and keeping production boring in a good way.

Terraform, OpenTofu, Pulumi, Crossplane — declarative infrastructure management and the workflows around it.

Using AI and ML to improve ops workflows — AIOps, predictive alerting, automated remediation, and LLM-assisted tooling.

Identity-first security, ZTNA, conditional access, and killing the perimeter once and for all.

Securing cloud workloads, misconfig detection, runtime protection, and the alphabet soup of cloud security tooling.

Embedding security into the development lifecycle — SAST, DAST, SCA, policy-as-code, and making security a developer concern.

Vault, AWS Secrets Manager, SOPS, and the hard problem of keeping credentials out of repos and config files.

Pod security, network policies, admission controllers, image signing, and securing the K8s supply chain.

SOC2, HIPAA, PCI, FedRAMP — automating audit evidence, policy enforcement, and continuous compliance.

Running workloads across cloud and on-prem, cloud cost optimization, and the repatriation trend.

Post-Broadcom options — Nutanix, Proxmox, OpenStack, Harvester, and the great virtualization migration.

Backup, disaster recovery, immutable storage, ransomware resilience, and keeping the business alive when things go wrong.

Building and managing GPU clusters, AI/ML training infrastructure, inference at scale, and the datacenter power problem.

SD-WAN, SASE, network automation, intent-based networking, and making the network programmable.

Modern storage architectures — NVMe, S3-compatible object stores, distributed storage, and eliminating bottlenecks.