MongoDB database administration for web application

Our company is engaged in the development, support and maintenance of sites of any complexity. From simple one-page sites to large-scale cluster systems built on micro services. Experience of developers is confirmed by certificates from vendors.

Development and maintenance of all types of websites:

Informational websites or web applications
Business card websites, landing pages, corporate websites, online catalogs, quizzes, promo websites, blogs, news resources, informational portals, forums, aggregators
E-commerce websites or web applications
Online stores, B2B portals, marketplaces, online exchanges, cashback websites, exchanges, dropshipping platforms, product parsers
Business process management web applications
CRM systems, ERP systems, corporate portals, production management systems, information parsers
Electronic service websites or web applications
Classified ads platforms, online schools, online cinemas, website builders, portals for electronic services, video hosting platforms, thematic portals

These are just some of the technical types of websites we work with, and each of them can have its own specific features and functionality, as well as be customized to meet the specific needs and goals of the client.

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MongoDB Database Administration for Web Applications

MongoDB is a document database with horizontal scaling. Flexible schema is convenient during development, but in production requires discipline: without indexes queries become collection scans, without compaction WiredTiger doesn't free space, without oplog monitoring replicas lag and lose synchronization.

Initial Audit

// mongosh
use mydb

// Database statistics
db.stats({ scale: 1024 * 1024 }) // in MB

// Collection statistics
db.runCommand({ listCollections: 1 }).cursor.firstBatch.forEach(c => {
    const stats = db[c.name].stats({ scale: 1024 })
    printjson({
        name: c.name,
        docs: stats.count,
        size_kb: stats.size,
        storageSize_kb: stats.storageSize,
        totalIndexSize_kb: stats.totalIndexSize,
        nindexes: stats.nindexes
    })
})

// Collection indexes with sizes
db.orders.stats().indexSizes

// Operations running right now (> 1 second)
db.currentOp({ "secs_running": { $gt: 1 } })

Indexing

// Compound index for typical query by user and date
db.orders.createIndex(
    { user_id: 1, created_at: -1 },
    { background: true, name: "idx_user_date" }
)

// Partial index — only for active orders
db.orders.createIndex(
    { created_at: -1 },
    {
        partialFilterExpression: { status: { $in: ["pending", "processing"] } },
        name: "idx_active_orders_date"
    }
)

// TTL index for auto-deleting expired sessions
db.sessions.createIndex(
    { expires_at: 1 },
    { expireAfterSeconds: 0, name: "ttl_sessions" }
)

// Check index usage
db.orders.aggregate([
    { $indexStats: {} }
]).forEach(stat => {
    if (stat.accesses.ops === 0) {
        print("UNUSED INDEX: " + stat.name)
    }
})

background: true allows creating indexes without locking the database. In MongoDB 4.2+ this is the default behavior.

Explain and Query Optimization

// Analyze query execution plan
db.orders.find({ user_id: "507f1f77bcf86cd799439011", status: "pending" })
    .explain("executionStats")

// Key fields in executionStats:
// - stage: "COLLSCAN" means full collection scan — need an index
// - stage: "IXSCAN" — uses index, good
// - nReturned vs totalDocsExamined — closer to 1:1 ratio, the better the index
// - executionTimeMillis — execution time

Enable profiler to find slow queries:

// Profile queries > 100ms
db.setProfilingLevel(1, { slowms: 100 })

// View slow queries
db.system.profile.find(
    { millis: { $gt: 100 } },
    { ns: 1, command: 1, millis: 1, ts: 1 }
).sort({ millis: -1 }).limit(20)

// Disable profiler (affects performance!)
db.setProfilingLevel(0)

Replica Set: Setup and Monitoring

// Initialize replica set
rs.initiate({
    _id: "rs0",
    members: [
        { _id: 0, host: "mongo1:27017", priority: 2 },
        { _id: 1, host: "mongo2:27017", priority: 1 },
        { _id: 2, host: "mongo3:27017", arbiterOnly: true }
    ]
})

// Replication status
rs.status()

// Replica lag (critical: if oplog overflows — replica loses synchronization)
rs.printSecondaryReplicationInfo()

// Oplog size (should cover several hours of operations)
rs.printReplicationInfo()
// oplog size: 5760MB
// log length start to end: 14400 secs (4 hrs)
// If less than 4–6 hours — increase:
db.adminCommand({ replSetResizeOplog: 1, size: 10240 }) // 10 GB

Backup

mongodump — for databases up to several GB:

# Backup with consistency point on replica set
mongodump \
  --uri="mongodb://backup_user:password@mongo1:27017,mongo2:27017/mydb?replicaSet=rs0" \
  --readPreference=secondary \
  --oplog \
  --gzip \
  --out=/backups/dump_$(date +%Y%m%d_%H%M)

# Restore
mongorestore \
  --uri="mongodb://admin:password@localhost:27017" \
  --gzip \
  --oplogReplay \
  /backups/dump_20250101_0300

mongodump with --oplog only blocks reads on secondary — for production always backup from secondary.

For large databases (>100 GB) — filesystem snapshots (LVM, AWS EBS Snapshot) are faster physically.

WiredTiger: Compaction

MongoDB (WiredTiger) doesn't return freed space to OS automatically. After bulk document deletion — run compact:

// Compact specific collection
// WARNING: locks database during execution!
db.runCommand({ compact: "orders" })

// On replica set — compact sequentially on secondary, then switch primary
// Run during maintenance window

Check overhead before and after:

const stats = db.orders.stats({ scale: 1024 * 1024 })
console.log({
    dataSize: stats.size.toFixed(1) + ' MB',
    storageSize: stats.storageSize.toFixed(1) + ' MB',
    overhead_pct: ((1 - stats.size / stats.storageSize) * 100).toFixed(1) + '%'
})

User Management

use mydb

// Create application user
db.createUser({
    user: "app_user",
    pwd:  "strong_password",
    roles: [
        { role: "readWrite", db: "mydb" }
    ]
})

// Read-only for analytics
db.createUser({
    user: "analytics",
    pwd:  "analytics_password",
    roles: [
        { role: "read", db: "mydb" }
    ]
})

// List users
db.getUsers({ showCredentials: false })

Connection Pooling

Mongoose (Node.js) opens 5 connections by default. For high-load applications:

mongoose.connect(process.env.MONGO_URI, {
    maxPoolSize:     50,  // maximum connections in pool
    minPoolSize:     5,
    serverSelectionTimeoutMS: 5000,
    socketTimeoutMS: 45000,
    connectTimeoutMS: 10000
})

For PHP (MongoDB extension):

$client = new MongoDB\Client(
    "mongodb://app_user:password@mongo1:27017,mongo2:27017/mydb",
    ["replicaSet" => "rs0", "readPreference" => "secondaryPreferred"],
    ["typeMap" => ["root" => "array", "document" => "array"]]
);

Monitoring via mongostat and mongotop

# Real-time operation statistics (each second)
mongostat --uri="mongodb://admin:password@localhost:27017" --discover

# Top collections by read/write time
mongotop --uri="mongodb://admin:password@localhost:27017" 5

# Key metrics to monitor in Prometheus (via mongodb_exporter):
# - mongodb_ss_globalLock_currentQueue_total > 0 — lock queue
# - mongodb_ss_connections_current vs maxIncomingConnections
# - replication lag on secondary
# - opcounters: insert/query/update/delete per second