Highly extensible software like Emacs, Vim, and Neovim tend to grow their own package managers. A software developer, for example, might want to install editor plugins that hook into a particular programming language's linter or language server. The programmer's text editor is therefore extended to support managing additional software to extend the text editor. If this loop continues for too long, the programmer's editor becomes more delicate and complex. The remedy for this problem is to manage software using dedicated tools apart
#!/usr/bin/env bash | |
export PROJECT_ID=$(gcloud config get-value project) | |
export PROJECT_USER=$(gcloud config get-value core/account) # set current user | |
export PROJECT_NUMBER=$(gcloud projects describe $PROJECT_ID --format="value(projectNumber)") | |
export IDNS=${PROJECT_ID}.svc.id.goog # workflow identity domain | |
export GCP_REGION="us-central1" # CHANGEME (OPT) | |
export GCP_ZONE="us-central1-a" # CHANGEME (OPT) | |
export NETWORK_NAME="default" |
#!/usr/bin/env bash | |
# Reference: https://cloud.google.com/memorystore/docs/redis/connect-redis-instance-functions#python | |
# enable APIs | |
gcloud services enable redis.googleapis.com | |
gcloud services enable cloudfunctions.googleapis.com | |
gcloud services enable vpcaccess.googleapis.com | |
# set these to your specific environment |
{ stdenv, dpkg, fetchurl, openssl, libnl, buildFHSUserEnv,... }: | |
stdenv.mkDerivation { | |
name = "falcon-sensor"; | |
version = "4.18.0-6402"; | |
arch = "amd64"; | |
src = fetchurl { | |
url = "https://storage.googleapis.com/company-tools/falcon-sensor/falcon-sensor_4.18.0-6402_amd64.deb"; | |
sha512 = "dc41cfe0232124480abdcf456df9a3bd6cab62716bc5beea089fbf99ac2e29bf1e1a44676591a71eeb35afe7f25e495b53ede007cfc15dcbf47df7ec0a016098"; | |
}; |
Moved to git repository: https://github.com/denji/nginx-tuning
For this configuration you can use web server you like, i decided, because i work mostly with it to use nginx.
Generally, properly configured nginx can handle up to 400K to 500K requests per second (clustered), most what i saw is 50K to 80K (non-clustered) requests per second and 30% CPU load, course, this was 2 x Intel Xeon
with HyperThreading enabled, but it can work without problem on slower machines.
You must understand that this config is used in testing environment and not in production so you will need to find a way to implement most of those features best possible for your servers.
Create an index with a nested mapping:
curl -XPUT 'http://127.0.0.1:9200/test/?pretty=1' -d '
{
"mappings" : {
"test" : {
"properties" : {
"title" : {
"type" : "string"
},
I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.
I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real