gitricko

All Languages

Any application can set variables through https://github.com/paketo-buildpacks/environment-variables

Any language can specify a launch configuration via Procfile which will override the language specific script detection.

Any language can specify labels to add to the image that's built: https://github.com/paketo-buildpacks/image-labels

"Multiple App Ports" Demo on Cloud Foundry

2017.03.29

These demos are validated against:

Deploying MicroPCF on AWS

January 5th, 2016

Instructions for deploying micropcf to AWS.

I encountered several challenges relating to AWS configurations and the available Vagrantfile while deploying micropcf to AWS. This documentation details the steps taken to successfully deploy micropcf to AWS.

System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

Clarify and agree on the scope of the system

User cases (description of sequences of events that, taken together, lead to a system doing something useful)
- Who is going to use it?
- How are they going to use it?

	#!/usr/bin/env python3
	# Based on: https://gist.github.com/nahushrk/5d980e676c4f2762ca385bd6fb9498a9
	#
	# The original script broke with newer Ollama versions due to hardcoded `library`
	# namespace paths and a malformed tar archive structure. This rewrite fixes those
	# issues and adds: namespaced/custom-registry model support, a `list` command,
	# `--as` (import under a different name), `--force`, `--output`, tag defaulting
	# to `latest`, auto-detection of the Ollama base path, and safe tarfile extraction
	# for Python 3.12+.
	"""

	#!/usr/bin/env python3
	"""
	Ollama Model Manager

	This script provides two modes of operation:
	- export: Exports an installed Ollama model to a tarball.
	- import: Imports an Ollama model from a tarball.

	The export mode reads a manifest file located at:
	<base_path>/manifests/registry.ollama.ai/library/<model_name>/<model_size>

	SHELL := /bin/bash
	export CLUSTER_NAME ?= epinio
	export TMP_DIR ?= /tmp
	IP_ADDR := $(shell ifconfig -a \| grep "inet " \| grep -v 127 \| awk 'NR==1{print $$2}')
	export DOMAIN ?= $(IP_ADDR).sslip.io
	export EPINIO_SERVER_VERSION ?= 1.11.0
	export ADM_USR ?= admin
	export ADM_PWD ?= password
	export ADM_PWD_ENCRYPT := '$(shell htpasswd -bnBC 10 "" ${ADM_PWD} \| tr -d :)'
	export DEV_USR ?= dev

	This gist I write, because I couldn't find any step by step instructions
	how to install and start postgresql locally (using conda within a conda environment - with the result
	that you can run it without sudo/admin rights on your machine!)
	and not globally in the operating system (which requires sudo/admin rights on that machine).

	I hope, this will help especially people new to postgresql
	(and those who don't have sudo/admin rights on a specific machine but want
	to run postgresql there)!

	Prerequisite is to have miniconda already installed in your Computer.

	const puppeteer = require('puppeteer');
	const request = require('request-promise-native');
	const poll = require('promise-poller').default;

	const siteDetails = {
	sitekey: '6LeTnxkTAAAAAN9QEuDZRpn90WwKk_R1TRW_g-JC',
	pageurl: 'https://old.reddit.com/login'
	}

	const getUsername = require('./get-username');

	from flask import Flask, request
	from nameko.standalone.rpc import ServiceRpcProxy

	app = Flask(__name__)


	@app.route('/')
	def task_list():
	return """
	<html>