Downloaded 63 times
![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" }
]
}](https://image.slidesharecdn.com/9-26gentechoverviewforops-130926173104-phpapp01/75/Webinar-General-Technical-Overview-of-MongoDB-for-Ops-Teams-12-2048.jpg)
![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, … }
}
}](https://image.slidesharecdn.com/9-26gentechoverviewforops-130926173104-phpapp01/75/Webinar-General-Technical-Overview-of-MongoDB-for-Ops-Teams-13-2048.jpg)
![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, … }
}
}](https://image.slidesharecdn.com/9-26gentechoverviewforops-130926173104-phpapp01/75/Webinar-General-Technical-Overview-of-MongoDB-for-Ops-Teams-15-2048.jpg)
Uploaded byMongoDB
Webinar: General Technical Overview of MongoDB for Ops Teams
The document provides a technical overview of MongoDB, highlighting its capabilities as a leading NoSQL database that offers agility, flexibility, and scalability for various applications. It emphasizes the benefits of using MongoDB for data management in industries such as finance, retail, and healthcare, showcasing its performance and architecture features like automatic sharding and high availability. Additionally, it introduces the MongoDB Management Service (MMS) for monitoring and managing deployments, ensuring optimal performance and disaster recovery.
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Webinar: General Technical Overview of MongoDB for Ops Teams
- 1. General Technical Overviewof MongoDB for Ops Teams Senior Solutions Architect, MongoDB Asya Kamsky #MongoDB
- 2.
- 3. MongoDB The leading NoSQLdatabase Document Database Open- Source General Purpose
- 4. MongoDB Business Value EnablingNew Apps Better Customer Experience Lower TCOFaster Time to Market
- 5. 4,000,000+ MongoDB Downloads 100,000+ Online EducationRegistrants 20,000+ MongoDB User Group Members 20,000+ MongoDB DaysAttendees 15,000+ MongoDB Management Service (MMS) Users Global Community
- 6. MongoDB and EnterpriseIT 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 DataManagement Big Data Content Mgmt & Delivery Mobile & Social MongoDB Solutions
- 8. • 10 ofthe 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.
- 11.
- 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 RelationalMongoDB { 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 fullfeatured 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 forinteracting 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 moreproductive
- 18.
- 19. Automatic Sharding • Increaseor decrease capacity as you go • Automatic balancing • Three types of sharding: hash-based range-based tag-aware
- 20. Query Routing • Multiplequery optimization models • Many sharding options appropriate for different apps
- 21.
- 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 • ReplicaSet – two or more copies • “Self-healing” shard • Addresses many concerns: - High Availability - Disaster Recovery - Maintenance
- 24. Replica Set Benefits BusinessNeeds 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.
- 26.
- 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.
- 29. Global Data Distribution Real-time Real-timeReal-time Real-time Real-time Real-time Real-time Primary Secondary Secondary Secondary Secondary Secondary Secondary
- 30.
- 31.
- 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 5Marketing 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.
- 37. Monitoring • CLI andinternal 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-basedsuite of services for managing MongoDB deployments
- 39. • Charts, custom dashboardsand 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 andrestore 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 Speaksa Thousand Words
- 42. Symptoms High Use CPUSimilar 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.
- 45. Thank You Senior SolutionsArchitect, MongoDB Asya Kamsky #MongoDB