MongoDB is the leading open-source, document database. In this webinar we'll dive into the technical details of MongoDB by first focusing on what makes it different from traditional relational database management systems. We'll review data storage, high availability and scaling for MongoDB. Next we'll discuss what's involved in deploying MongoDB in production. Finally, we'll delve into some of the operational challenges including performance tuning, capacity planning and what it takes to deploy robust highly-available cluster topology.

1. General Technical Overview of
MongoDB for Ops Teams
Senior Solutions Architect, MongoDB
Asya Kamsky
#MongoDB

2. MongoDB

3. MongoDB
The leading NoSQL database
Document
Database
Open-
Source
General
Purpose

4. MongoDB Business Value
Enabling New Apps Better Customer Experience
Lower TCOFaster Time to Market

5. 4,000,000+
MongoDB Downloads
100,000+
Online Education Registrants
20,000+
MongoDB User Group Members
20,000+
MongoDB DaysAttendees
15,000+
MongoDB Management Service (MMS) Users
Global Community

6. MongoDB and Enterprise IT Stack
EDWHadoop
Management&Monitoring
Security&Auditing
RDBMS
CRM, ERP, Collaboration, Mobile, BI
OS & Virtualization, Compute, Storage, Network
RDBMS
Applications
Infrastructure
Data Management
Online Data Offline Data

7. Data HubUser Data Management
Big Data Content Mgmt & Delivery Mobile & Social
MongoDB Solutions

8. • 10 of the Top Financial Services Institutions
• 10 of the Top Electronics Companies
• 10 of the Top Media and Entertainment
Companies
• 8 of the Top Retailers
• 6 of the Top Telcos
• 5 of the Top Technology Companies
• 4 of the Top Healthcare Companies
Fortune 500 & Global 500

9. MongoDB Partners (200+)
Software & Services
Cloud & Channel Hardware

10. Data Model

11. Operational Database Landscape

12. RDBMS
Agility
MongoDB
{
_id : ObjectId("4c4ba5e5e8aabf3"),
employee_name: "Dunham, Justin",
department : "Marketing",
title : "Product Manager, Web",
report_up: "Neray, Graham",
pay_band: “C",
benefits : [
{ type : "Health",
plan : "PPO Plus" },
{ type : "Dental",
plan : "Standard" }
]
}

13. Document Data Model
Relational MongoDB
{
first_name: „Paul‟,
surname: „Miller‟,
city: „London‟,
location: [45.123,47.232],
cars: [
{ model: „Bentley‟,
year: 1973,
value: 100000, … },
{ model: „Rolls Royce‟,
year: 1965,
value: 330000, … }
}
}

14. Document Model Benefits
• Agility and flexibility
– Data models can evolve easily
– Companiescan adapt to changes quickly
• Intuitive, natural data representation
– Developers are more productive
– Many types of applicationsare a good fit
• Reduces the need for joins, disk seeks
– Programmingis more simple
– Performance can be delivered at scale

15. MongoDB is full featured
MongoDB
Rich Queries
• Find Paul’s cars
• Find everybody in London with a car
built between 1970 and 1980
Geospatial
• Find all of the car owners within 5km of
Trafalgar Sq.
Text Search
• Find all the cars described as having
leather seats
Aggregation
• Calculate the average value of every
user's car collection
Map Reduce
• What is the ownership pattern of colors
by geography over time? (is purple
trending up in China?)
{
first_name: „Paul‟,
surname: „Miller‟,
city: „London‟,
location: [45.123,47.232],
cars: [
{ model: „Bentley‟,
year: 1973,
value: 100000, … },
{ model: „Rolls Royce‟,
year: 1965,
value: 330000, … }
}
}

16. Shell
Command-line shell for interacting
directly with database
Shell and Drivers
Drivers
Drivers for most popular
programming languages and
frameworks
>
db.collection.insert({company:“10gen”, product:“MongoDB”}
)
>
> db.collection.findOne()
{
“_id” : ObjectId(“5106c1c2fc629bfe52792e86”),
“company” : “10gen”
“product” : “MongoDB”
}
Java
Python
Perl
Ruby
Haskell
JavaScript

17. Developers are more productive

18. Scalability

19. Automatic Sharding
• Increase or decrease capacity as you go
• Automatic balancing
• Three types of sharding:
 hash-based
 range-based
 tag-aware

20. Query Routing
• Multiple query optimization models
• Many sharding options appropriate for different apps

21. High Availability

22. • HighAvailability – Ensure application availability during many
types of failures
• Disaster Recovery –Address the RTO and RPO goals for
business continuity
• Maintenance – Perform upgrades and other maintenance
operations with no application downtime
Availability Considerations

23. Replica Sets
• Replica Set – two or more copies
• “Self-healing” shard
• Addresses many concerns:
- High Availability
- Disaster Recovery
- Maintenance

24. Replica Set Benefits
Business Needs Replica Set Benefits
High Availability Automated failover
Disaster Recovery Hot backups offsite
Maintenance Rolling upgrades
Low Latency Locate data near users
Workload Isolation Read from designated nodes
Data Consistency Tunable Consistency

25. Deployment Architecture

26. MongoDB Architecture

27. Deployment
• Automated failover
• Tolerates server failures
• Tolerates rack failures
• Number of replicas
defines failure tolerance
Primary – A Primary – B Primary – C
Secondary – A Secondary – ASecondary – B
Secondary – BSecondary – CSecondary – C

28. Global Deployment/Local Writes
Primary:NYC
Secondary:NYC
Primary:LON
Primary:SYD
Secondary:LON
Secondary:NYC
Secondary:SYD
Secondary:LON
Secondary:SYD

29. Global Data Distribution
Real-time
Real-time Real-time
Real-time
Real-time
Real-time
Real-time
Primary
Secondary
Secondary
Secondary
Secondary
Secondary
Secondary

30. Performance

31. Better Data
Locality
Performance
In-Memory
Caching
In-Place
Updates

32. • Entertainment Company: 1,400 servers
• Craigslist: 5B documents
• Carfax: 11B documents
• Tier 1 Bank: 30K ops/sec
• Major Retailer: 50K ops/sec
• FedAgency: 500K ops/sec
• Wordnik: 20B documents, 35,000 ops/sec
Performance at Scale

33. MongoDB Performance*
Top 5 Marketing
Firm
Government
Agency
Top 5 Investment
Bank
Data Key/value 10+ fields, arrays,
nested documents
20+ fields, arrays,
nested documents
Queries Key-based
1 – 100 docs/query
80/20 read/write
Compound queries
Range queries
MapReduce
20/80 read/write
Compound queries
Range queries
50/50 read/write
Servers ~250 ~50 ~40
Ops/sec 1,200,000 500,000 30,000
* These figures are provided as examples. Your application governs your performance.

34. Capacity Planning
• Requirements
• Testing
• Monitoring
Key Deployment Considerations

35. Capacity Planning
• Requirements
• Testing
• Monitoring
Performance Tuning
• Understanding
• Adjusting
• Monitoring
Key Performance Considerations

36. Monitoring

37. Monitoring
• CLI and internal status commands
• mongostat; mongotop; db.serverStatus()
• Plug-ins for munin, Nagios, cacti, etc.
• Integration via SNMP to other tools
• MMS

38. MongoDB Management Service
Cloud-based suite of services for managing MongoDB deployments

39. • Charts, custom
dashboards and
automated alerting
• Tracks 100+ metrics –
performance, resource
utilization, availability and
response times
• 15,000+ users
MongoDB Management Service
Cloud-based suite of services for managing MongoDB deployments

40. • Backup and restore with
– point-in-time recovery,
– support for sharded clusters
Cloud-based suite of services for managing MongoDB deployments
• MMS On-Prem included with MongoDB Enterprise
(backup coming soon)
MongoDB Management Service

41. A Picture Speaks a Thousand Words

42. Symptoms
High Use CPU Similar Query Pattern

43. Monitoring Best Practices
• Monitor Logs
– Alert, escalate
– Correlate
• Disk
– Monitor
• Instrument/MonitorApp (including logs!)
• Know your application and application (write)
characteristics

44. Questions?

45. Thank You
Senior Solutions Architect, MongoDB
Asya Kamsky
#MongoDB