Speaker: Cory Mintz, Lead Engineer, MongoDB It has been one year since MongoDB Atlas was revealed at MongoDB World 2016. In this session lead Atlas engineer Cory Mintz will walk you through new Atlas features that have been built over the last year, how they work under the hood, and some of the implementation challenges that the team faced. Cory will discuss the building blocks of IaaS providers and how we leverage them in Atlas. VPC peering and Live Import are on the agenda, as well as features so new that you will hear them announced at MongoDB World. What You Will Learn: - How to use the latest features in MongoDB Atlas

1. MongoDB Atlas -
A Tale of
Three
Cloud Providers

2. Narrator
Implementation Deep Dive
4+ years at MongoDB
2+ years: Lead for Ops Manager
Last 18+ months: Lead for Atlas

3. Flashback
December 2015
Implementation Deep Dive
Cloud Team was 4 years old
Define an Atlas MVP
Worked through Winter/Spring
Atlas released June 2016 at
MongoDB World

4. Flashback
December 2016
Implementation Deep Dive
AWS is great, but we want to be
on GCP/Azure too
Worked through Winter/Spring
Here we are at MongoDB World
2017 releasing on GCP/Azure.

5. Present Day
Implementation Deep Dive
Chapter 1: Hardware
Chapter 2: Account Layout
Chapter 3: Software
Epilogue: MongoDB 2018

6. Chapter 1: Hardware

7. 7
A Customer on AWS
AWS Account X - Region Y
VPC for Customer N
Availability Zone A Availability Zone B Availability Zone C
Subnet A Subnet B Subnet C
mongod - 27107 mongod - 27107 mongod - 27107

8. 8
A Customer on Azure
Azure Subscription X
Resource Group for Customer Y
VNET
Availability Set
mongod - 27107mongod - 27107mongod - 27107

9. 9
A Customer on Google Cloud Platform
GCP Organization
Project for Customer N
Zone A Zone B Zone C
Network
Subnet
mongod - 27107 mongod - 27107 mongod - 27107

10. 10
Disk Comparison
Cloud Storage Type Capacity Performance
AWS GP2 10GB - 16TB 3 IOPS/GB
AWS IO1 10GB - 16TB 15/30 IOPS/GB
Azure P-Series 128GB
512GB
1024GB
500 IOPS
2300 IOPS
5000 IOPS
GCP SSD Persistent Storage 1GB-64TB 30 IOPS/GB

11. 11
Instance Size Comparison
Cloud AWS Azure GCP
AWS T2-Series (M10/M20) ⅕ Core
⅖ Core
2GB
4GB
AWS M4-Series (M30+) 2 Core
4 Core
...
8GB
16GB
...
Azure DS_v2 1 Core
2 Core
...
3.5GB
7GB
...
GCP G1 Series 1/2 1.7GB
GCP N1 Series 1 Core
2 Core
...
3.75GB
7.5GB
...

12. Chapter 2: Account Structure

13. Goals
Implementation Deep Dive
Consolidated Authentication
Consolidated Billing
Scales

14. 14
AWS Account Layout
One root account
1000 customers per Account
Service account per Account
Consolidated billing to root account
Delegated auth from root account
AWS Root
Account
Dev
Account
QA
Account
Prod
Account
Dev
VPC N

15. 15
Azure Account Layout
Azure AD holds users / applications
Customer assigned to Subscription
400 customers per Subscription
Active
Directory
Dev
Sub.
QA
Sub.
Prod
Sub
Dev
Resource
Group N

16. 16
GCP Account Layout
One GCP Organization
A folder per environment
Customer gets a project in a folder
Service account per folder
Organization
Dev
Folder
QA
Folder
Prod
Folder
Dev
Project
N

17. Chapter 3: Software
What was easy and what was not

18. 18
Cloud Agents - Easy!
● Monitoring Agent, Backup Agent, Automation Agent
● Our tools, written in Go.
● Talk to / Manage MongoDB and report back to Cloud infrastructure

19. 19
Machine Images - Easy!
● All CentOS 7
● Minor updates to Chef cookbooks
● Scripts to build Azure/GCP Images

20. 20
Split Horizon DNS - More Difficult
AWS provided this for free
Need to build for Azure/GCP
Used multiple Zones (Route53)
Used dnsmasq on the VMs
mongodb.net
(Authoritative Zone)
mongodb.net
(Private Zone)
Customer Atlas Server
dnsmasq
Local DNS
Server
Local DNS
Server
Rest of
Internet

21. 21
Azure Availability Sets - More Difficult
AWS has Availability Zones
GCP has Zones
Azure has Availability Sets (FD, UD)
● Availability Set per shard
● Can not assign FD, UD
● Managed disk copies
Availability Set - Shard 1
FD0, UP0 FD1, UD1 FD2, UD2
Availability Set - Shard 2
FD0, UP0 FD2, UD2 FD1, UD1

22. 22
GCP is Under Construction - More Difficult
● Lots of feature we found critical were beta, or even alpha.
● Had to use beta endpoints for some changes
● Evaluate on a case-by-case basis if something was really needed

23. Epilogue

24. 24
MongoDB 2018 Preview
● Optimized disk and instance size upgrades on Azure/GCP
● Cross-region Clusters
● Cross-cloud Cluster

25. Questions