Cloud-native architectures with the boring reliability that lets product teams ship fast.
Praxvon designs cloud and DevOps infrastructure for product teams that have outgrown Vercel defaults — multi-region deployments, observability, infrastructure-as-code on AWS, Cloudflare or self-hosted Docker. Boring reliability, predictable costs, and a handoff your team can actually own.
Infrastructure is the part of software nobody sees until it breaks. Then it's the only thing anyone talks about. The teams that ship fastest aren't the ones with the cleverest infra — they're the ones whose infra stays out of the way.
We design cloud setups that scale predictably, cost what you expect, and recover from failures without a hero-engineer pulling an all-nighter. Boring is a feature.
AWS, GCP, or Azure — designed around your actual traffic patterns, not aspirational ones. Right-sized from day one.
Docker images that build fast and ship small. Kubernetes when you need it, simpler tools when you don't.
GitHub Actions, GitLab CI, or self-hosted runners — pipelines that run fast, catch regressions, and deploy with confidence.
Logging, metrics, traces, and on-call setup. You can't fix what you can't see — we make sure you can see everything.
We start by understanding what you have, what's working, and what's quietly costing you money or sleep.
Phased migrations with rollback plans. No big bangs. No 3 AM cutover windows unless absolutely necessary.
Runbooks, documentation, and training. We build infrastructure your team can own — not vendor lock-in.
Vercel is the right default for most Next.js apps — DX is excellent, CDN is global, builds are fast. We use it ourselves. But there are real reasons to leave: compliance constraints that require data residency we can audit (KVKK in Turkey, GDPR EU, SOC 2 in the US), cost at scale that swings into self-host territory, custom edge logic Vercel's runtime doesn't accommodate, or a customer that simply wants the infrastructure on their own AWS account.
Praxvon's own site (Next.js 16) and AKS Otomasyon both run on self-hosted Docker behind Cloudflare. The build is straightforward when you set it up early; the suffering is when teams try to swap hosting under a live app without preparing for it.
Most observability stacks generate dashboards nobody opens. We pick the smallest set that someone on the team will actually read: Sentry for runtime errors, OpenTelemetry for traces when the system is distributed enough to warrant it, Cloudflare Analytics + GA4 for traffic shape, and a single Slack channel per environment that posts when something interesting happens.
The discipline isn't "more metrics." It's "every alert has a runbook, and every runbook has been read." We deliver both.
Moving from a PaaS to self-hosted Docker affects a handful of decisions: SSL termination (we default to Cloudflare in front of the origin, with origin certs for full-strict), background job queues (something like BullMQ or RabbitMQ instead of Vercel cron), session storage (Postgres or Redis, not an opaque platform store), and deploys (GitHub Actions to a registry, then a thin shell script or Watchtower on the host).
Once it's set up, the operating cost is comparable to a managed platform for most workloads, and the data-residency and cost-predictability wins are real. We've helped teams move both directions and we're agnostic about which is "better" — there's just "right for your situation right now."
It depends on compliance, traffic shape, and how much your team wants to own the infrastructure. For most early-stage B2B SaaS, Vercel is still the right answer. For regulated industries, large-scale traffic with predictable bills, or teams that need custom edge logic, self-hosted Docker behind Cloudflare often makes more sense. We can model the cost both ways before you decide.
Cloudflare Workers for edge-served logic, regional Postgres replicas (or globally-replicated databases like Neon or Turso when latency demands it), and routing decisions made at the CDN layer. Multi-region is more often solved with caching and read replicas than with full active-active deploys — we recommend the smallest architecture that meets your real latency budget.
Probably not. For most B2B SaaS teams, Docker Compose on a single host, or a managed container service (ECS, Google Cloud Run, Fly.io), removes 90% of Kubernetes' operational cost without giving up much. We recommend K8s when the team is already running it well, or when the workload genuinely requires its scheduling guarantees — not as a default.
AWS Secrets Manager, GCP Secret Manager, 1Password Secrets Automation, or Doppler — depending on the rest of your stack. We avoid plain .env files in production and we treat staging secrets as carefully as production ones. Cross-environment naming conventions (and the cookie-prefix discipline) are part of the setup.
Through the first 90 days post-launch by default, then we hand off with documented runbooks. Long-term on-call belongs with the team running the product day-to-day; we'll train them, not become a permanent dependency.
Yes. Most migrations are mechanical (Dockerize the app, set up the new pipeline, validate against the old one, cut DNS). The risky part is the database — we plan logical replication or dump-and-load cutovers with rollback timing measured in minutes, not hours.
If your deploys take 30 minutes and your bills surprise you, we should talk.