joho

#!/bin/bash
#
# Publishes CloudWatch metrics about Buildbox queue length

set -e

API='https://api.buildbox.io'
BUILDS_ROUTE='v1/accounts/ACCOUNT_NAME/projects/PROJECT_NAME/builds'

# Determines whether a binary exists on the current $PATH

jonhoo

Distributed Read-Write Mutex in Go

This project has moved to https://github.com/jonhoo/drwmutex so it can be imported into Go applications.

sapessi

You can use CodePipeline and CodeBuild to create a continuous deployment/integration pipeline for serverless applications build on AWS Lambda and Amazon API Gateway. This sample application is written in Go with the Gin framework and uses the eawsy API Gateway proxy shim: https://github.com/eawsy/aws-lambda-go-net

We initially detailed our methodology in this blog post: https://aws.amazon.com/blogs/compute/continuous-deployment-for-serverless-applications/

We have used the shim technology created by eawsy to run Golang applications inside AWS Lambda (https://github.com/eawsy/aws-lambda-go-shim) and created a container that can be used with CodeBuild as part of our original pipeline template.

The container is available on DockerHub and is called sapessi/aws-lambda-go18-codebuild:latest. To use this container, simply change the Image property of the CodeBuild project environment.

The pipeline template, sample app, buildspec and SAM files are attached to this gist.

jcloutz

image: golang:1.7
stages:
  - build
  - test

before_script:
  - go get github.com/tools/godep
  - cp -r /builds/user /go/src/github.com/user/
  - cd /go/src/github.com/user/repo

kartiksura

package main

import (
	"fmt"
	"time"

	"github.com/aws/aws-sdk-go/aws"
	"github.com/aws/aws-sdk-go/aws/session"
	"github.com/aws/aws-sdk-go/service/athena"
)

17twenty

package main

import (
	"fmt"
	"log"
	"net/http"
	"strings"
)

func main() {

trevnorris

The prep-script.sh will setup the latest Node and install the latest perf version on your Linux box.

When you want to generate the flame graph, run the following (folder locations taken from install script):

sudo sysctl kernel.kptr_restrict=0
# May also have to do the following:
# (additional reading http://unix.stackexchange.com/questions/14227/do-i-need-root-admin-permissions-to-run-userspace-perf-tool-perf-events-ar )
sudo sysctl kernel.perf_event_paranoid=0

dongri

#!/bin/sh

sudo ps aux | grep Netskope | grep -v grep | awk '{ print "kill -9", $2 }' | sudo sh
echo '[✓] Kill Netskope Process'

sudo rm -rf /Applications/Remove\ Netskope\ Client.app
echo '[✓] Removed Remove Netskope Client.app'

sudo rm -rf /Library/Application\ Support/Netskope
echo '[✓] Removed Agent of Netskope Client.app'

stevenringo

| Title | Description

lewtun

# This is a modified version of TRL's `SFTTrainer` example (https://github.com/huggingface/trl/blob/main/examples/scripts/sft_trainer.py), 
# adapted to run with DeepSpeed ZeRO-3 and Mistral-7B-V1.0. The settings below were run on 1 node of 8 x A100 (80GB) GPUs.
#
# Usage:
#   - Install the latest transformers & accelerate versions: `pip install -U transformers accelerate`
#   - Install deepspeed: `pip install deepspeed==0.9.5`
#   - Install TRL from main: pip install git+https://github.com/huggingface/trl.git
#   - Clone the repo: git clone github.com/huggingface/trl.git
#   - Copy this Gist into trl/examples/scripts
#   - Run from root of trl repo with: accelerate launch --config_file=examples/accelerate_configs/deepspeed_zero3.yaml --gradient_accumulation_steps 8 examples/scripts/sft_trainer.py