MongoDB Stitch is a serverless platform designed to help you easily and securely build an application on top of MongoDB Atlas. It lets developers focus on building applications rather than on managing data manipulation code, service integration, or backend infrastructure. MongoDB Stitch also makes it simple to respond to backend changes immediately, allowing you to simplify client side code and build complex flows more easily. This talk will cover ways that MongoDB Stitch helps you respond to changes in your database and take your applications to the next level.

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Ch-ch-ch-ch-changes
Taking Your Stitch Application to the Next Level
with Stitch Triggers

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Robert Walters
Product Marketing
Twitter: @RobsCranium

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Industry Trends
Monolithic
Server Applications

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Industry Trends
Monolithic
Server Applications
Virtualization

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Industry Trends
Monolithic
Server Applications
Virtualization Containers

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Industry Trends
Monolithic
Server Applications
Virtualization Containers Serverless

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Industry Trends
Monolithic
Server Applications
Virtualization Containers Serverless
Microservices

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MongoDB Stitch Serverless Platform Services
Monolithic
Server Applications
Virtualization Containers
Serverless

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“We set out to build a database that we would want to use, so that
whenever developers wanted to build an application, they could
focus on the application, not on working around the database.”
- Eliot Horowitz

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MongoDB Stitch Triggers
Faster Cheaper Easier

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DEMO

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The evolution of MongoDB
3.0 3.2
Document Validation
$lookup
Fast Failover
Simpler Scalability
Aggregation ++
Encryption At Rest
In-Memory Storage Engine
BI Connector
MongoDB Compass
APM Integration
Profiler Visualization
Auto Index Builds
Backups to File System
Doc-Level
Concurrency
Compression
Storage Engine API
≤50 replicas
Auditing ++
Ops Manager
Linearizable reads
Intra-cluster compression
Views
Log Redaction
Linearizable Reads
Graph Processing
Decimal
Collations
Faceted Navigation
Zones ++
Aggregation ++
Auto-balancing ++
ARM, Power, zSeries
BI & Spark Connectors ++
Compass ++
Hardware Monitoring
Server Pool
LDAP Authorization
Encrypted Backups
Cloud Foundry Integration
3.4 3.6
Change Streams
Retryable Writes
Expressive Array Updates
Query Expressivity
Causal Consistency
Consistent Sharded Sec. Reads
Compass Community
Ops Manager ++
Query Advisor
Schema Validation
End to End Compression
IP Whitelisting
Default Bind to Localhost
Sessions
WiredTiger 1m+ Collections
MongoDB BI Connector ++
Expressive $lookUp
R Driver
Atlas Cross Region Replication
Atlas Auto Storage Scaling
4.0
Multi-Document ACID Transactions
Atlas Global Sharding
Atlas HIPAA
Atlas LDAP
Atlas Audit
Atlas Encrypted Storage Engine
Atlas AWS Backup Snapshots
Snapshot Reads
Agg Pipeline Type Conversions
40% Faster Shard Migrations
Non-Blocking Secondary Reads
SHA-2
TLS 1.1+
Compass Agg Pipeline Builder
Compass Export to Code
Charts Beta
Monitoring Cloud Service
Ops Manager K8s & OpenShift
MongoDB Stitch GA
MongoDB Mobile (Private Beta)

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OPLOGOPLOG OPLOG
Application
W
db.users.insert({,,,})
PRIMARY SECONDARY SECONDARY
db.users.insert({,,,})
A
C
K
db.users.insert({,,,})
What’s an Oplog?
OUT OF DATE OUT OF DATE

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OPLOGOPLOG OPLOG
Application
W
db.users.insert({,,,})
PRIMARY SECONDARY SECONDARY
db.users.insert({,,,})
A
C
K
db.users.insert({,,,})
W
db.users.update({,,,}) db.users.update({,,,})
A
C
K
db.users.update({,,,})
Monitor
R R
If (insert) {
aws.s3.insertObject(…);
}
Responding to change via tailing the OpLog
TAILING THE OPLOG

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Responding to Database Changes in the Past
Before Change Streams: Oplog
{
"ts" : Timestamp(1395663575, 1),
"h" : NumberLong("-5862498903080440015"),
"v" : 2,
"op" : "i",
"ns" : ”music.songs",
"o" : {
"_id" : ObjectId("533024470d7e2c31d4443d22"),
"author" : ”David Bowie",
"title" : ”Changes"
}
}

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Responding to Database Changes in the Past
Before Change Streams: Oplog
var MongoDB = require('mongodb');
oplogurl = 'mongodb+srv://mike:<PASSWORD>@dotlocaltalk-hhfkg.mongodb.net/test?retryWrites=true’;
MongoDB.MongoClient.connect(oplogurl, function(err, db) {
db.collection("oplog.rs", function(err, oplog) {
oplog.find({}, {
ts: 1
}).sort({
$natural: -1
}).limit(1).toArray(function(err, data) {
lastOplogTime = data[0].ts;
if (lastOplogTime) {
queryForTime = {
$gt: lastOplogTime
};
} else {
tstamp = new MongoDB.Timestamp(0, Math.floor(new Date().getTime() / 1000))
queryForTime = {
$gt: tstamp
};
}
cursor = oplog.find({
ts: queryForTime
}, {
tailable: true,
awaitdata: true,
oplogReplay: true,
numberOfRetries: -1
});
stream = cursor.stream();
stream.on('data', function(oplogdoc) {
console.log(oplogdoc);
});
});
});
})

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Setting up a Change Stream (NodeJS)

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Setting up a Change Stream (NodeJS)

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Change Streams Implementation
Apps register for notifications via API
Change streams are:
• Flexible: deltas or the full document, filter on specific events only
• Consistent: total ordering of data across shards
• Secure: enforces collection’s user access privileges
• Reliable: only notifies once write committed on majority of replicas
• Resumable: from node failure
• Concurrent: up to 1,000 changes streams per MongoDB instance
• Familiar: use regular MongoDB query language and drivers

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Triggers

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Adding Triggers to Stitch
Reduce Time to Market
Functions as a Service: No waiting on
infrastructure
Reduce boilerplate: Save code
Cross-Platform: Develop once
Existing Apps Untouched: No reverse-
engineering
Reduce Ops costs
Serverless: Zero wasted capacity
Payment: No up-front cost
Capacity on Demand: No need to over-
provision in advance
Secure by Default: Less operational effort
Reduce Dev Effort
Backend Integration Built in: No generic
backend code
HA & Scalability Built in: Hard and time
consuming to build Orchestrate Services:
Reuse what's out there
Faster Cheaper Easier

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Appendix

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When do we want functions to execute?
AUTHENTICATION
WEBHOOK/
INTEGRATION
DATABASE EVENTS
3 Contexts Where Functions
Execute

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Event Driven Life-cycle
Pending SucceededOwned
Failed Dead
Event is …
Waiting for a ConsumerAttempting ExecutionCompletedAwaiting RetriesRe-Attempting ExecutionUnable to Execute
(Trigger Disabled)

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What do change events look like?
Event Subscription (Trigger) Event Source (Actual event document)

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Example Trigger
Name of the Trigger
Type: DATABASE, AUTHENTICATION
Type of Operation to Trigger
Database
Collection
Match Criteria
Full Document or Partial
Function to be called on Trigger

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Example Trigger Event Document
Type of Database Operation
Full Document impacted by operation
Database
Collection