PostgreSQL Setup and Configuration#

Every PostgreSQL deployment boils down to three things: get the binary running, configure who can connect, and tune the memory settings.

Installation Methods#

Package Managers#

On Debian/Ubuntu, use the official PostgreSQL APT repository:

sudo apt install -y postgresql-common
sudo /usr/share/postgresql-common/pgdg/apt.postgresql.org.sh
sudo apt install -y postgresql-16

On macOS: brew install postgresql@16 && brew services start postgresql@16

On RHEL/Fedora:

sudo dnf install -y https://download.postgresql.org/pub/repos/yum/reporpms/EL-9-x86_64/pgdg-redhat-repo-latest.noarch.rpm
sudo dnf install -y postgresql16-server
sudo /usr/pgsql-16/bin/postgresql-16-setup initdb
sudo systemctl enable --now postgresql-16

Config files live at /etc/postgresql/16/main/ (Debian) or /var/lib/pgsql/16/data/ (RHEL).

Time-Series Database Selection and Operations#

Time-series databases optimize for a specific access pattern: high-volume writes of timestamped data points, queries that aggregate over time ranges, and automatic expiration of old data. Choosing the right one depends on your data model, query patterns, retention requirements, and operational constraints.

When You Need a Time-Series Database#

A dedicated time-series database is justified when you have high write throughput (thousands to millions of data points per second), queries that are predominantly time-range aggregations, and data that has a defined retention period. Common use cases: infrastructure metrics, application performance monitoring, IoT sensor data, financial tick data, and log analytics.

Choosing a Database Strategy#

Every Kubernetes-based platform eventually faces two questions: should the database run inside the cluster or as a managed service, and which database engine fits the workload? These decisions are difficult to reverse. A database migration is one of the highest-risk operations in production. Getting the initial decision roughly right saves months of future pain.

Where to Run: Kubernetes vs Managed Service#

This is not a technology question. It is an organizational question about who owns database operations and what tradeoffs the team will accept.

Database Connection Pooling: PgBouncer, ProxySQL, and Application-Level Patterns#

Database connections are expensive resources. PostgreSQL forks a new OS process for every connection. MySQL creates a thread. Both allocate memory for session state, query buffers, and sort areas. When your application scales horizontally in Kubernetes – 10 pods, then 20, then 50 – the connection count multiplies, and most databases buckle long before your application pods do.

Connection pooling solves this by maintaining a smaller set of persistent connections to the database and sharing them across many application clients. Understanding pooling options, deployment patterns, and sizing is essential for any production database workload on Kubernetes.

PostgreSQL 15+ Permissions: Why Your Helm Deployment Cannot Create Tables#

Starting with PostgreSQL 15, only the database owner and superusers can create objects in the public schema by default. This breaks a common Helm pattern where you create a user, grant privileges, and expect it to create tables. The application connects fine but fails on its first CREATE TABLE.

The Symptom#

Your application pod logs show something like:

Error: permission denied for schema public

Or from an ORM like Mattermost’s: