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kube2iam your security partner

• Introduction
• Setup kube2iam in your cluster
• Setting up the Role in AWS
  • The Role
• Trust Relationship

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module "vpc" {
  source = "git::[email protected]:rafaeljesus/vpc?ref=master"

  vpc_id          = var.vpc_id
  vpc_cidr_block  = var.vpc_cidr_block
  azs             = slice(data.aws_availability_zones.available.names, 0, 3)
  public_subnets  = var.vpc_public_subnets
  private_subnets = var.vpc_private_subnets
  igw_id          = var.vpc_igw_id

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before_script:
  - export GOPATH=$(pwd)

stages:
  - build
  - test
  - deploy

validate-schema:
  image: truongsinh/pg-client:9.4

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Producer

Setup
bin/kafka-topics.sh --zookeeper esv4-hcl197.grid.linkedin.com:2181 --create --topic test-rep-one --partitions 6 --replication-factor 1
bin/kafka-topics.sh --zookeeper esv4-hcl197.grid.linkedin.com:2181 --create --topic test --partitions 6 --replication-factor 3

Single thread, no replication

bin/kafka-run-class.sh org.apache.kafka.clients.tools.ProducerPerformance test7 50000000 100 -1 acks=1 bootstrap.servers=esv4-hcl198.grid.linkedin.com:9092 buffer.memory=67108864 batch.size=8196

sunnykrGupta

How To Serve Flask Applications with uWSGI and Nginx on Ubuntu 14.04

@credit Yan Zhu (https://github.com/nina-zhu)

Introduction

Flask is a microframework for Python based on Werkzeug, Jinja 2 and good intentions, it can help you get your Python application or website off the ground. Flask includes a simplified development server for testing your code locally, but for anything even slightly production related, a more secure and powerful web server is required.

In this guide, we will demonstrate how to install and configure some components on Ubuntu 14.04 to support and serve Flask applications. We will configure the uWSGI application container server to interface with our applications. We will then set up Nginx to reverse proxy to uWSGI, giving us access to its security and performance features to serve our apps.

Prerequisites and Goals

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#-------------- Node selector example

apiVersion: v1
kind: Pod
metadata:
  name: nginx
  labels:
    env: test
spec:
  containers:

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Convention
# RAM : Mi = MB, ie, 1024Mi is 1024 MB or 1GB
# CPU : m = milicpu , ie, 100m cpu is 100 milicpu, or say 0.1 CPU

apiVersion: v1
kind: Pod
metadata:
  name: cpu-ram-demo
spec:
  containers:

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## To view Nodes in a cluster
$kubectl get nodes

NAME                                          STATUS    AGE
gke-test-cluster-default-pool-2d123aa1-012f   Ready     2d
gke-test-cluster-default-pool-2d123aa1-e23k   Ready     2d

## To view the Deployment we created run:
$    kubectl get deployments

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###### cat sample-services.yaml

kind: Service
apiVersion: v1
metadata:
  name: my-service
spec:
  type: LoadBalancer
  loadBalancerIP: 10.10.10.1
  ports:

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#sample-deployment.yaml

apiVersion: apps/v1beta1
kind: Deployment
metadata:
  name: nginx-deployment
spec:
  replicas: 3
  template:
    metadata: