Scaling with Automation

Location : Bangalore
Date : 27th April, 2016
Name of the Speaker : Uchit Vyas
Company Name : Opex Software, Pune
IT Automation Summit 2016
http://www.unicomlearning.com/2016/IT_Automation_Summit/
Bangalore
27th April 2016

VCs on line 1
Scaling under pressure
with
Chef, Packer and Terraform

Who am I: Uchit Vyas
8+ years of exciting experience
Infrastructure automation domain
Leading Cloud Infrastructure
automation in Opex Software

Introduction
Single metric we measure: Speed with correctness
Mission: Automate IT. Create Time
Focus: SAAS applications

SAAS Startup Dream
Scaling with SPEED
How to make this happen, technically?
Images: 4actionmarketing.net, dreamstime.com, thenextweb.com

Pressure from investors
How to make this happen, technically?
Images: startupinitiative.com

SAAS is value: Step 1 of 3
Clear value is delivered

Onboarding new customers rapidly

Onboarding new customers rapidly
Upgrade fast, maintain lead,
make value irresistible

Mortality Rate
Images: jeepneymanilaph.files.wordpress.com

Execution Problems
All good
Harden the OS skill not available immediately
Automate app deploy/cfg after thought
Automate Testing fully after thought

Execution Problems
All good
Harden the OS skill not available immediately
Automate app deployment after thought
Automate app configuration after thought
Microservices independently upgradable?
Lead starting to lose speed, competition!
Images: avopress.com, animationmagazine.net, thenextweb.com

1412/05/15
DevOps + Strong Ops
Dev
Test
Ops

15
Transform test automation for DevOps
Test bed
Infrastructure
creation
Automation
Automated
Test Result
Analytics
Test
Automation
(Selenium,
QTP etc)

Strong Ops to scale
Helpdesk Monitoring
Configuration
Management
Auto-Self
healing
Synthetic
Monitoring
Log analytics

OS Hardening: Why is it imp?
protecting IP
unfair competition
cybersecurity
private data
direct or indirect
attacks via cloud
President Barack Obama delivers remarks at the Business Roundtable offices in Washington
September 16, 2015.

OS Hardening
Use Chef templates and Terraform
Include following in server configuration definition
Security Rules, Password policies,
Secure SSH, Compliance policy
Important agents (AV, monitoring)
Use “Chef-Vault” for storing secrets

Sample code: login definition
template '/etc/login.defs' do
source 'login.defs.erb'
mode '0444'
owner 'root'
group 'root'
variables(
additional_user_paths: node['env’] …
)
end

Sample code: erb file
'sample.erb'
<% if @port != 80 -%>
Listen <%= @port %>
<% end -%>
Two simple, but powerful concepts
a) Expression evaluation
b) Variable value replacement

Sample code: login definition
variables(
password_max_age: node['auth']['pw_max_age'],
password_min_age: node['auth']['pw_min_age'],
login_retries: node['auth']['retries'],
login_timeout: node['auth']['timeout'],
chfn_restrict: '', # "rwh"
allow_login_without_home:
node['auth']['allow_homeless'],
…
)

High speed lab creation
Terraform is parallelized
Auto-sequencing based on graphs
Terraform can integrate with any layer of the
stack
Lab setup on pre-existing servers, provisioning
servers from scratch - both are supported

Speed of provisioning
Why we chose terraform for high-speed scaling
Number of Machines Chef-metal Terraform
10 2.7 minutes 1.20 minutes

Distributing load elegantly
Next few slides explain the code.
Key highlighted portions are in a red rectangle
Use cases 1: Synthetic monitoring
Use case 2: Load balancing across all regions in a cloud
How to scale across AZs? How to scale across clouds?

.tf Provisioning (AWS multi AZs)
provider "aws" {
region = "us-west-2"
access_key = "XXXXXXX"
secret_key = "XXXXXXXXX"
}ia

variable "region"
{
default = "us-west-2"
}
variable "region_az" {
default = {
"us-east-1" = "us-east-1a,us-east-1c,us-east-1d,us-east-1e"
"us-west-1" = "us-west-1a,us-west-1b,us-west-1c"
"eu-west-1" = "eu-west-1a,eu-west-1b,eu-west-1c"
"eu-central-1" = "eu-central-1a,eu-central-1b"
"ap-southeast-1" = "ap-southeast-1a,ap-southeast-1b"
"ap-northeast-1" = "ap-northeast-1a,ap-northeast-1b,ap-northeast-1c"
"sa-east-1" = "sa-east-1a,sa-east-1b,sa-east-1c"
}
}
Variables for AZs and AMIs
Lets use this region to start

Region based AZ map
variable "region_az" {
default = {
"us-east-1" = "us-east-1a,us-east-1c,us-east-1d,us-east-1e"
"eu-west-1" = "eu-west-1a,eu-west-1b,eu-west-1c"
"eu-central-1" = "eu-central-1a,eu-central-1b"
"ap-northeast-1" = "ap-northeast-1a,ap-northeast-1b,ap-northeast-1c"
"sa-east-1" = "sa-east-1a,sa-east-1b,sa-east-1c"
}
}
variable "ami"
{
default = ...
used in lookup

variable "ami"
{
default =
{
"description" = "Ubuntu server 14.04 ami id"
"us-west-1" = "ami-df6a8b9b"
"us-west-2" = "ami-5189a661"
"us-east-1" = "ami-d05e75b8"
"eu-west-1" = "ami-47a23a30"
"eu-central-1" = "ami-accff2b1"
"ap-northeast-1" = "ami-936d9d93"
"ap-southeast-1" = "ami-96f1c1c4"
"ap-southeast-2" = "ami-69631053"
"sa-east-1" = "ami-4d883350"
}
}
Region based Ubuntu AMI map

resource "aws_instance" "web" {
ami = "${lookup(var.ami, var.region)}"
instance_type = "${var.instance_type}"
count = "${var.servers}"
availability_zone =
"${element(split(",",lookup(var.region_az,
var.region)),
count.index%length
(split(",",lookup(var.region_az,
var.region))
))}"
Resource declaration

resource "aws_instance" "web" {
ami = "${lookup(var.ami, var.region)}"
instance_type = "${var.instance_type}"
count = "${var.servers}"
availability_zone =
"${element(split(",",lookup(var.region_az,
var.region)),
count.index%length
(split(",",lookup(var.region_az,
var.region))
))}"
Scaling and iterating
Math library added from
terraform v0.4
Simulating iteration
Scaling to 100s of servers

Multi-cloud distribution
Step 1
Creating an image
for each cloud
Step 2
Using that image in
the code that we
just saw

Creating image using Packer
"provisioners": [{
"type": "shell",
"inline": [
"sleep 30",
"sudo apt-get update",
"sudo apt-get install -y redis-
server"
]
}] Provisioning Redis server

Strong Ops - Chef provisioner
"provisioners": [{
"type": "chef-client",
"server_url”: “https://mychefserver.com/”
}]
Cookbooks and Recipes:
Helpdesk, monitoring server, monitoring clients, antivirus
agents, auto-healing servers, analytics data couriers...
Using Chef client-server

Creating image using Packer
"builders": [{
"type": "amazon-ebs",
"access_key": "{{user `aws_access_key`}}",
"secret_key": "{{user `aws_secret_key`}}",
"region": "us-east-1",
"source_ami": "ami-de0d9eb7",
"instance_type": "t1.micro",
"ssh_username": "ubuntu",
"ami_name": "packer-example {{timestamp}}"
},
Build in Amazon Cloud

Same code for multi-cloud
"builders": [{
"type": "amazon-ebs",
"access_key": "{{user `aws_access_key`}}",
"secret_key": "{{user `aws_secret_key`}}",
"region": "us-east-1",
"source_ami": "ami-de0d9eb7",
"instance_type": "t1.micro",
"ssh_username": "ubuntu",
"ami_name": "packer-example {{timestamp}}"
},
{
"type": "digitalocean",
"api_token": "{{user `do_api_token`}}",
"image": "ubuntu-14-04-x64",
"region": "nyc3",
"size": "512mb"
}],
Build in Amazon Cloud Build in Digital Ocean Cloud

Beautiful multi-color output
amazon-ebs output will be in this color.
digitalocean output will be in this color.
==> digitalocean: Creating temporary ssh key for droplet...
==> amazon-ebs: Prevalidating AMI Name...
==> amazon-ebs: Inspecting the source AMI...
==> amazon-ebs: Creating temporary keypair: packer 55f6c5e5-2b50-c8c3-5e37-7d246b6f0bca
==> amazon-ebs: Creating temporary security group for this instance...
==> amazon-ebs: Authorizing access to port 22 the temporary security group...
==> amazon-ebs: Launching a source AWS instance...
==> digitalocean: Creating droplet...
==> digitalocean: Waiting for droplet to become active...

Pilot of great idea - clear value delivered - all good
Onboarding new customers rapidly without sacrificing quality
Harden the OS - chef-templates, packer, Terraform
Automate app deployment - Terraform + Chef
Automate app configuration - Terraform + Chef + Data bags
Pivot fast, maintain the lead, make value irresistible
DevOps for building new features fast - Adopt DevOps early
Upgrade customers DevOps pipeline + Roles + Environments
Hope this helps!

The 4th question in daily agile scrums that was never asked
4th question: Are you blocking Ops?
Meaning:
a) Are there any new binaries created/deleted?
b) Are there any configuration files that changed?
c) Are there any configuration attributes that changed?
Why DevOps projects fail

Recap, takeaway
Easy to code infrastructure
Easy to replicate infrastructure
Easy to distribute infrastructure across AZs
Easy to balance infrastructure across regions
Easy to balance infrastructure across clouds, countries
Easy to integrate with other apps
The 4th scrum question

IT Automation Summit 2016
http://www.unicomlearning.com/2016/IT_Automation_Summit/
Speaker Name: Uchit Vyas
Email ID: uchit.vyas@opexsoftware.com
Organized by
UNICOM Trainings & Seminars Pvt. Ltd.
contact@unicomlearning.com

Opex Software Thanks You
AUTOMATE IT. CREATE TIME

Hybrid SAAS Apps
App is on AWS (DO, Azure, other clouds)
Appliance, Sync process is on-prem with the tenant

Upgrading customers: Env
knife environment create ClientSetOne
name "ClientSetOne"
description "The packages and configuration used by ClientSetOne"
cookbook_versions({
"nginx" => "<= 1.1.0",
"apt" => "= 0.0.1"
})
override_attributes ({
"nginx" => {
"listen" => [ "80", "443" ]
},
"mysql" => {
"root_pass" => "root"
}
})

Upgrading customers: Associate
Each node can be in exactly one environment
STEP1: knife node edit clientOneAppliance
STEP2: {
"name": "clientOneAppliance",
"chef_environment": "ClientSetOne",
"normal": {
"tags": [
]
},
"run_list": [
"role[web_server]"
]
}

Language Integration challenges
Source: http://sdtimes.com/poll-the-language-i-use-most-at-work-is/

Terraform JSON file which can be executed
by terraform
Java beans for the all available TF resources.
Opening TF to Java world
Terraform Resource
(Java)
Transpiler with
Notification Provisioner
Injection
Terraform Resource
(JSON)
Convert TF Java bean into TF JSON. Injects
echos using local_exec.

Terraform JSON
Resource
Terraform
Executor(Java)
Terraform Action
Handler
Notify Action Handlers for
1. Resource Created
2. Provisioner Execution Started
3. Provisioner Execution Done
Execute Terraform JSON File
Terraform Executor(Java)

Scaling with Automation

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