How to create a Kubernetes cluster from scratch, including getting it to run with cgroup v2 and swap turned on.
Welcome to Episode 2 of the "Musings of a PostgreSQL Data Pontiff" series! In this installment I’m aiming to achieve three objectives.
This is the first in a series of blogs on the topic of using PostgreSQL for "data science". I put that in quotes because I would not consider myself to be a practicing "data scientist", per se. Of course I'm not sure there is a universally accepted definition of "data scientist". This article provides a nice illustration of my point.
Recently I ran across grand sweeping statements that suggest containers are not ready for prime time as a vehicle for deploying your databases. The definition of "futile" is something like "serving no useful purpose; completely ineffective". See why I say this below, but in short, you probably are already, for all intents and purposes, running your database in a "container". Therefore, your resistance is futile.
When Linux detects that the system is using too much memory, it will identify processes for termination and, well, assassinate them. The OOM killer has a noble role in ensuring a system does not run out of memory, but this can lead to unintended consequences.
How can you get PostgreSQL to use FIPS 140-2 crypto? The answer, to some extent, depends on how rigorously you need to be able to prove your answer. If the proof required is more than a casual check, the process is not well documented as far as I can tell. Therefore I will attempt to address that deficiency here.
I was sent a link to a tweet regarding election night forecasting and of course the default questions was... could be run under PL/R inside Postgres. Like about everything else at Crunchy Data we believe all things are better with Postgres.
Learn how the HPE SSD issues can impact your PostgreSQL data, and what strategies you can take to protect your data.
CVE-2018-1058 discusses how a PostgreSQL user can create trojans with unexpected results. Learn how to prevent this along with other security concepts.
Explore how the PostgreSQL extension crunchy_check_access helps you to understand default PostgreSQL security settings and how it impacts your users.
Your PostgreSQL data model directly affects how much data is stored on disk. Additionally, your ingest rate and retention could affect whether you require 10TB or 100TB of storage! This deep dive can help you save orders of magnitude of disk space before using sharding or other distributed models.
Introduction to Spatial Analytics with PostgreSQL, PostGIS, PL/R and R Programming Language. Demonstration of preprocessing of Geospatial data using PostGIS.