Example on how to run locally an AWS Lambda via API Gateway using localstack.
Based on...
-- show running queries (pre 9.2) | |
SELECT procpid, age(clock_timestamp(), query_start), usename, current_query | |
FROM pg_stat_activity | |
WHERE current_query != '<IDLE>' AND current_query NOT ILIKE '%pg_stat_activity%' | |
ORDER BY query_start desc; | |
-- show running queries (9.2) | |
SELECT pid, age(clock_timestamp(), query_start), usename, query | |
FROM pg_stat_activity | |
WHERE query != '<IDLE>' AND query NOT ILIKE '%pg_stat_activity%' |
#cloud-config | |
ssh_authorized_keys: | |
- ssh-rsa <my-public-key> | |
rancher: | |
services: | |
nginx-proxy: | |
image: jwilder/nginx-proxy:0.4.0 | |
restart: unless-stopped | |
ports: | |
- "80:80" |
Example on how to run locally an AWS Lambda via API Gateway using localstack.
Based on...
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There are many Git workflows out there, I heavily suggest also reading the atlassian.com [Git Workflow][article] article as there is more detail then presented here.
The two prevailing workflows are [Gitflow][gitflow] and [feature branches][feature]. IMHO, being more of a subscriber to continuous integration, I feel that the feature branch workflow is better suited.
When using Bash in the command line, it leaves a bit to be desired when it comes to awareness of state. I would suggest following these instructions on [setting up GIT Bash autocompletion][git-auto].
When working with a centralized workflow the concepts are simple, master
represented the official history and is always deployable. With each now scope of work, aka feature, the developer is to create a new branch. For clarity, make sure to use descriptive names like transaction-fail-message
or github-oauth
for your branches.
// Use Gists to store code you would like to remember later on | |
console.log(window); // log the "window" object to the console |