software_dev

I’ve been playing around with using an in-process redis using miniredis as the backing store for a service that relies on go-workers2 for background processing. You can find the code in my example-miniredis project on GitHub. While miniredis was created as something to be only used in unit tests, this may be useful in running a service that normally requires a redis in a totally standalone mode. I view such a standalone mode as critical for a good development experience in creating integrations against a service, since you can run the service locally without any of its downstream dependencies and still expect to have it respond sensibly....

It has taken me far too long to figure out all the minute details of how to apply authentication to gRPC-based services, how to do that using the HTTP/JSON grpc-gateway, and then how to run a gRPC server and a grpc-gateway side-by-side using the same service instance in a way that makes sense to me. There’s a surprising amount of detail that is not documented and there are a few gotchas for the unwary traveller....

My day job currently includes writing and maintaining golang services. It’s not a bad language, and it certainly forces you to understand that everything will fail, far more obviously than Java’s checked exceptions. I’m not going to argue about the utility of checking/returning error instances, but I do find myself writing the same code over and over again, especially when I’m handling any SQL operations. So I’ve come up with a couple of templates to remove a bunch of the boilerplate code for transactions and for looping over SQL query result rows....

I’ve recently been involved with integration and administration of an OpenLDAP cluster, and was a little dismayed at the state of monitoring of OpenLDAP. You can certainly get good machine metrics using the Prometheus Node Exporter, but there wasn’t really anything good for OpenLDAP-specific metrics aside from an interesting project based on python. This exporter had some really good ideas, but I baulked at installing and running twisted python, irrespective how good it is, on slapd nodes....

Starting a HTTP server in python to serve files from a directory is a reasonably well-known one-liner. In python 2.x it is: python -m SimpleHTTPServer 8080 In python 3.x it is: python -m http.server 8080 But how do you something similar for HTTPS? Here’s a solution, which unfortunately is larger than one line: #!/usr/bin/python import BaseHTTPServer, SimpleHTTPServer import ssl httpd = BaseHTTPServer.HTTPServer(('0.0.0.0', 8443), SimpleHTTPServer.SimpleHTTPRequestHandler) httpd.socket = ssl.wrap_socket(httpd.socket, certfile='./certs_and_key.pem', server_side=True) httpd.serve_forever() Save that as an executable file, combine your PEM cert chain and key into a single file, and off you go!...

Everyone has a backup script that takes a tarball/zipfile/etc and uploads it somewhere for safe-keeping. In a lot of places where I’ve worked, the “somewhere” winds up being an Amazon S3 bucket (or lately a DigitalOcean Space). These scripts are lovingly crafted and sometimes quite clever, using the aws cli or s3cmd, or something custom. What I wanted was to encode my process for encrypting a backup and sending that backup to an S3 bucket....

SSL/TLS in Java is a pain in the behind. Not only is the setup verbose, but the format for certificates and keys is unique. Nginx/Apache/Go/etc seem to be happy using certifiates and keys encoded as PEM files, but Java has its own special KeyStores, with the JKS format being the default. There are a number of questions on forums, and custom recipes that involve openssl, to convert PEM certificates and keys into formats that can be imported into a Java keystore....

Welcome friend. Here’s something for you to read so that we can have some awesome arguments. The Pragmatic Programmer Design Patterns: Elements of Reusable Object-Oriented Software Refactoring: Improving the Design of Existing Code Domain-Driven Design: Tackling Complexity in the Heart of Software Working Effectively with Legacy Code Growing Object-Oriented Software, Guided by Tests Release It!: Design and Deploy Production-Ready Software Continuous Delivery: Reliable Software Releases through Build, Test, and Deployment Automation Building Microservices Pragmatic Thinking and Learning: Refactor Your Wetware Drift into Failure: From Hunting Broken Components to Understanding Complex Systems Building Evolutionary Architectures ...

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The most useful way I’ve seen such contract tests work is that the team that consumes the messages creates and publishes an artifact in their build pipeline for use by the creators of the messages. For this example let’s have it create a tarball with a shell script entry point. The inputs to the shell script can be a URL to the api-server and any other parameters required, like user IDs, oauth tokens, etc....