Talk · Cloud Native Gandhinagar
Abstracting the Abyss:
How to Run Production Data
Workloads on Any Kubernetes Cluster
Agenda
What We'll Cover Today
- 01 3 doors for running data in your organization
- 02 The inception of Cloud Native
- 03 Getting Kubernetes production-ready for data
- 04 Running production databases on Kubernetes
- 05 Intro to OpenEverest
Three Paths
3 Doors for Running Data in Your Org
Managed Services
RDS, MongoDB Atlas, Cloud SQL…
- Fast to get started
- Vendor handles operations
- Expensive at scale
- Locked into one cloud
Legacy & DIY
Custom scripts, VMs, bare metal…
- Full control over setup
- Requires a dedicated DBA team
- Manual, error-prone processes
- Hard to scale consistently
Cloud Native
Kubernetes Operators, GitOps…
- Runs on any infrastructure
- Operations as code
- No vendor lock-in
- Day-2 ops automated
Door 1 · Managed Services
The Golden
Cage
Managed databases feel easy — until you start scaling. Then the hidden costs and constraints start to show.
RDS, MongoDB Atlas, Cloud SQL, PlanetScale, Neon…
Vendor Lock-in
Your data, their APIs, their region list, their outage schedule. Migrating out is painful and expensive.
Unpredictable Costs
Bills that grow non-linearly with traffic. Egress fees. Storage markups. Per-connection pricing surprises.
Limited Control
Can't tune storage drivers, OS configs, or networking. You get what they expose — nothing more.
Data Sovereignty
Regulated industries can't always let a third party hold the data. Compliance becomes your problem.
Door 2 · Legacy & DIY
The Hidden Tax of
Doing It Yourself
Full control sounds great — until your database expert leaves and no one knows how the provisioning script works.
Ticket-driven Provisioning
Developers open a ticket. A DBA creates the database. Days pass. Everyone is frustrated.
Zombie Scripts
Bash scripts and Ansible playbooks written years ago. Nobody wants to touch them. They "just work" — until they don't.
Knowledge Silos
One person knows the replication setup. Another knows the backup cron. Nobody knows both.
Doesn't Scale
10 databases: manageable. 100 databases: chaos. The linear growth of effort kills the team.
Incident-driven Ops
No automated failover. Failover is a 2 AM phone call, a runbook, and adrenaline.
Upgrade Paralysis
Upgrading PostgreSQL 13 → 16? That's a project, not a task. So it gets deferred indefinitely.
Door 3 · Cloud Native
Enter Kubernetes —
The Unifier
One API. Any infrastructure. Kubernetes became the platform for building platforms — and it runs everywhere.
The Myth vs. Reality
Kubernetes has grown up.
Data workloads belong.
Kubernetes 1.0 — Stateless first
Deployments and ReplicaSets designed for ephemeral, interchangeable pods. Storage was an afterthought.
StatefulSets & PersistentVolumes
Stable network identities, ordered deployment, and persistent storage. The first real foundation for data.
Storage Classes & CSI Drivers
Dynamic provisioning, volume snapshots, local NVMe support. Cloud-grade storage on any backend.
Operators — domain knowledge as code
PostgreSQL, MySQL, MongoDB, Redis — all managed by operators that encode DBA expertise into the control loop. This is where it gets interesting.
Cloud Native Databases