Latest posts from Jonathan S. Katz

Ensuring data can be securely transmitted is a requirement of many production systems. PostgreSQL supports TLS as a means of encrypting network communication, verifying hosts, and allowing for certificate-based authentication

What if I told you that you can create an out-of-the-box active-active, federated PostgreSQL cluster on Kubernetes?

Since logical decoding was introduced in PostgreSQL 9.4, I have been fascinated by the various applications it has. In fact, I've used this feature to apply the concepts of change data capture

We've seen an example of how to set up PostgreSQL monitoring in Kubernetes. We've looked at two sets of statistics to keep track of it in your PostgreSQL cluster: your vitals

I am an accidental DBA, with a huge emphasis on "accidental." I came to PostgreSQL as an application developer who really liked to program with SQL and use the database to help solve my problems. Nonetheless, these systems would enter into production, and as such I had to learn to support them.

PostgreSQL monitoring and performance optimization is a vast topic

My professional background has been in application development with a strong affinity for developing with PostgreSQL (which I hope comes through in previous articles). However, in many of my roles, I found myself as the "accidental" systems administrator, where I would troubleshoot issues in production and do my best to keep things running and safe.

When it came to monitoring my Postgres databases, I initially took what I knew about monitoring a web application itself, i.e. looking at CPU, memory, and network usage, and used that to try to detect issues. In many cases, it worked: for instance, I could see a CPU spike on a PostgreSQL database and deduce that there was a runaway query slowing down the system.

Over time, I learned about other types of metrics

You don't need monitoring until you need it. But if you're running anything in production, you always need it.

This is particularly true if you are managing databases. You need to be able to answer questions like "am I running out of disk?" or "why does my application have degraded performance?" to be able to troubleshoot or mitigate problems before they occur.

When I first made a foray into how to monitor PostgreSQL in Kubernetes

PostgreSQL 13 is a lucky release! There are some very impactful new features and the release is coming out at its regularly scheduled time in the fall.

One of my favorite parts around the PostgreSQL release process

I'll admit it: I used to have triskaidekaphobia, otherwise known as a "fear or avoidance of the number 13." After all, I grew up in an area with many tall buildings where the elevators have no 13th floor

I've made it no secret that I am a huge fan of PostgreSQL's SCRAM support: it provides a secure, standardized way of performing authentication with passwords, and is a method that can be universally applied.

The beauty of SCRAM is that both authenticating parties (in this case, your client/application and PostgreSQL) can both verify that each party knows a secret without ever exchanging the secret

Advanced PostgreSQL high-availability and disaster recovery strategies designed to maximize uptime involve distributing database clusters across multiple data centers. While on the surface, this may seem intuitive (e.g. eliminate outages due to a single-point-of-failure), there are many nuances to consider, including avoiding the dreaded split-brain