Well folks, I have a confession to make. I've been maintaining an affair with two lovers. That's right; they're none other than PostgreSQL, and Google Cloud. While such polygamy may be shunned by the masses, I believe that somehow, some way, we can just make this ménage à trois work. What entices me about Cloud SQL is the existence of
Spin up a VPS and configure DNS with relative ease.
For the last few weeks I've been enamored with Google's cloud platform, aptly named Google Cloud Platform. GCP contains the things you might expect from a young player in the 'screw AWS' space: much of what exists on AWS has an equivalent on GPC, but certain subtleties exist, such as the lack of Python serverless functions and so forth. That
After achieving market dominance, Flask is a Python framework impossible to avoid.
Evidence of Flask’s rise to power has been all around us for a couple of years now. Anybody paying close attention to the technology stacks chosen by startups has undoubtedly noticed a flip: at some point, the industry standard flipped away from Django entirely.
Huge bets are being placed on Flask across the industry. Plotly’s famous Dash product
Forcefully use the Pandas library in your AWS Lambda functions.
In one corner we have Pandas: Python's beloved data analysis library. In the other, AWS: the unstoppable cloud provider we're obligated to use for all eternity. We should have know this day would come.
While not the prettiest workflow, uploaded Python package dependencies for usage in AWS Lambda is typically straightforward. We install the packages locally to a virtual env,
Get familiar with AWS as we set the stage to make something awesome.
There comes a surreal moment in nearly every profession in which perspective is violently forced into our own self-awareness. People with cooler jobs probably have that moment when they save their first patient, or launch their first rocket. For me, the idea of building an API was this moment in software development. All those past blackboxes which spat out results
Spinning up a standalone MySQL Database with Amazon.
Last time we became familiar with the handiwork of setting up MySQL locally, navigating databases via command line, and exposing your database to external access. While badass, it has come to my attention that most people don't bother doing things this way. Unless you're getting deep into some heavy architecture, most people opt to use cloud services such as AWS
Pairing Flask with zero-effort container deployments is a deadly path to addiction.
It's difficult to cover every cloud solution on the market without at least mentioning Heroku. Heroku contrasts nearly every cloud hosting solution by offering a clear purpose: make deploying apps of any kind as easy as possible. Deploying to a VPS requires knowledge of web servers and configurations. Deploying to containers requires knowledge of Docker or Kubernetes. Deploying to Heroku