The Official MongoDB Guide : Resilience, Scalability, Security and Performance.

Format:

Book

Author/Creator:

Palmer, Rachelle.

Contributor:

Allen, Jeffrey.

Faucher, Parker.

Huh, Alison.

Kerbey, Lander.

Raman, Maya.

Tran, Lauren.

Language:

English

Subjects (All):

MongoDB.

Physical Description:

1 online resource (368 pages)

Edition:

1st ed.

Place of Publication:

Birmingham : Packt Publishing, Limited, 2025.

Summary:

The official guide to MongoDB architecture, tools, and cloud features, written by leading MongoDB subject matter experts to help you build secure, scalable, high-performance applications Key Features Design resilient, secure solutions with high performance and scalability Streamline development with modern tooling, indexing, and AI-powered.

Contents:

Cover

FM

Contributors

Preface

Chapter 1: Introduction to MongoDB

Why MongoDB?

Who uses MongoDB?

MongoDB architecture

Clusters

Sharded clusters

Collections

What's new in MongoDB?

Performance

Encryption

Cost and scaling

Resilience

Summary

Chapter 2: MongoDB Architecture

Replication

Replica set elections

Replication election protocol

Heartbeats

Member priority

Mirrored reads

Loss of a data center

Network partition

Replica set oplog

Oplog buffers

The oplog window

Oplog size

Replica set deployment architecture

Strategies for deploying replica sets

Replica set arbiter

Hidden replica set members

Fault tolerance

Adding capacity ahead of demand

Geographic distribution

Read-heavy applications

Example deployment architectures

Primary with two secondary members

Primary with a secondary member and an arbiter

Three-member replica set distributed across two data centers

Five-member replica set distributed across three data centers

Write concern

Read preference

Read concern

Compaction

Background compaction

TCMalloc performance optimization

Platform support

Enabling Transparent Huge Pages (THP)

Enabling per-CPU caches

Replication methods

Replication commands

Replication versus sharding

Sharding

Why do you need sharding?

Key elements of a sharded cluster

Config shards

Converting a replica set to a sharded cluster with a config shard

Transitioning from a config shard to a dedicated config server

Advantages of sharding

Data distribution

Shard key

Resharding a collection

Refining a shard key

Chunks

Ranges

Zones

Balancer

Balancing window

Sharding strategies

Ranged sharding

Hashed sharding

Hashed versus ranged sharding scenarios.

Production configurations

Development configuration

Sharded and non-sharded collections

Unsharding a collection

Moving an unsharded collection

Querying sharded data

Find operations

sort(), limit(), and skip() operations

Update and delete operations

Hedged reads

Sharding methods

Chapter 3: Developer Tools

Integrated development environment extensions

MongoDB for VS Code extension

Getting started with the VS Code extension

Data exploration

Query prototyping

CRUD capabilities in the MongoDB Playground for VS Code

Prototyping aggregations in the MongoDB Playground for VS Code

MongoDB IDE extension for IntelliJ

Compass

Getting started

Interacting with your data

Managing documents

Querying documents in MongoDB Compass

Natural language querying in Compass

MongoDB MCP Server

Chapter 4: Data Modeling and Index Optimization

Document data model

BSON and its data types

Embedded data

Schema design

Identify the application workload

Map schema relationships

Optimizing queries for articles

Optimizing queries for articles and authors

Modeling relationships

One-to-one relationships

One-to-many relationships

Many-to-many relationships

Embedding versus references

Applying schema design patterns

The bucket pattern

The attribute pattern

The polymorphic pattern

The extended reference pattern

The approximation pattern

The computed pattern

The outlier pattern

The subset pattern

The document versioning pattern

The schema versioning pattern

The tree pattern

Schema design anti-patterns

Indexes

Determining whether a query used an index

Index types

Single-field indexes

Compound indexes

Multikey indexes

Text search

TTL indexes

Partial indexes

Geospatial indexes.

Wildcard indexes

Hidden indexes

Hashed indexes

Clustered indexes

Identifying common queries

Persistent query settings for indexes

Covered queries

Indexing strategies

Chapter 5: Queries

Technical requirements

MongoDB CRUD operations

Basic CRUD with mongosh

Connecting to MongoDB

Creating documents

Reading documents

Updating documents

Deleting documents

Basic CRUD with the Python driver

Installing and connecting to PyMongo

Deleting a document

Bulk operations

Syntax

Aggregations in MongoDB

Introduction to the aggregation framework

Aggregation pipeline example

Benefits of the aggregation framework

Aggregation stages

Compatibility

Common aggregation stages

MongoDB 8.0 aggregation stage enhancements

Advanced aggregation pipelines

Best practices

Code modularity

Streaming and blocking stages of a pipeline

Query shapes

Query settings

Query settings commands

queryStats statistics

Fields, operands, and aggregation pipelines

New database commands

Collection database commands

Server database commands

Chapter 6: Database Operations

Monitoring

Why monitor?

Cluster monitoring

Memory metrics

Page faults

Resident memory

Virtual memory

WiredTiger

In-memory storage engine

I/O metrics

Waits and queues

Free disk space

Monitoring replication

Network monitoring

Cursors and connections

Replication opcounters

Working set considerations

Indexes and the working set

Considerations for sharded clusters

Config server health

Locks

Data consistency

MongoDB reporting tools

Local tools

First-party tools

Third-party tools.

Monitoring with the Atlas CLI

Common monitoring pitfalls

MongoDB backups

Backing up with Atlas

Self-managed platform backup

Local backups

Consistency requirements

Full versus incremental backup

Backing up with mongodump

Filesystem snapshots

Backing up with cp or rsync

Cluster-to-cluster sync

Common backup pitfalls

Auditing

System logging versus auditing

System logging

Verbosity

Redaction

Logging on managed deployments

Audit logging

Audit log formats

Types of auditable events

Enabling auditing in self-managed deployments

Enabling auditing in Atlas

Audit filters

Database profiling

Viewing and downloading logs

Log rotation

Case study: Auditing for compliance

Troubleshooting auditing

Tools for audit analysis

Chapter 7: Security

Application security

SCRAM

X.509 certification

Authorization and role-based access control

User-defined roles

Data security

Encryption at rest with key management

Encryption in transit with TLS

Client-Side Field Level Encryption

Queryable Encryption

Comparing CSFLE and Queryable Encryption

redact pipeline operator

Security in MongoDB deployments

LDAP deprecation

Why deprecation?

OIDC overview

Using OIDC with MongoDB

Kerberos

Network hardening

Chapter 8: MongoDB Atlas

Setting up your organization

Managing organizations in MongoDB Atlas

Project-level configuration

Understanding clusters

Exploring tools for interacting with MongoDB Atlas

Atlas UI

Atlas CLI

Programmatic access and automation

What is the Atlas Kubernetes Operator?

The power of declarative management

Getting started with the Atlas Kubernetes Operator

Exploring data through the Atlas BI Connector.

Benefits of DirectQuery for MongoDB Atlas

Atlas Charts

Enhancing table charts with hyperlinks

Creating charts with Natural Language Mode

Familiar tools

Sizing an Atlas cluster

Storage, RAM, CPU, IOPS, and connections per tier

Storage requirements

Document size calculation

Collection size calculation

Total collection size

Index size

WiredTiger compression

Buffer size

Future growth projections

Additional considerations

RAM requirements

WiredTiger memory allocation

RAM calculation example

IOPS and performance analysis

IOPS provisioning and scaling

Provisioned IOPS for write-heavy workloads

Using monitoring tools to scale effectively

Network throughput and connections

Bandwidth calculation

Connection management

Region selection

Latency optimization

Final cluster selection

Scaling in Atlas

Why is choosing the right scaling strategy so important?

Vertical scaling in Atlas

Trade-offs and limitations

Vertical scaling implementation options

Auto-scaling capabilities

Storage auto-scaling

Cluster tier auto-scaling

Auto-scaling considerations

Horizontal scaling in MongoDB Atlas

Components of a sharded cluster

Shard key selection

Global Clusters for geographic distribution

Administrative considerations

Cost and operational trade-offs

Horizontal versus vertical scaling

Creating a comprehensive scaling strategy

Configuring authentication and authorization

Understanding authentication and authorization

The control plane and data plane

Workforce versus workload

Authentication

Atlas workforce user authentication

Atlas workload user authentication

Database user authentication

Authorization

Role-based access control

Atlas user roles

Database user roles

Custom roles

Securing your Atlas deployments.

Why security from the beginning matters.

Notes:

Description based upon print version of record.

Optimizing queries for articles

Description based on publisher supplied metadata and other sources.

ISBN:

1-83702-196-1

1-83702-197-X

OCLC:

1534808396