Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top

2020 | Book

Core Concepts Read chapter Read first chapter

MongoDB Topology Design

Scalability, Security, and Compliance on a Global Scale

Author: Nicholas Cottrell

Publisher: Apress

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

Login to get access
insite
SEARCH

About this book

Create a world-class MongoDB cluster that is scalable, reliable, and secure. Comply with mission-critical regulatory regimes such as the European Union’s General Data Protection Regulation (GDPR). Whether you are thinking of migrating to MongoDB or need to meet legal requirements for an existing self-managed cluster, this book has you covered. It begins with the basics of replication and sharding, and quickly scales up to cover everything you need to know to control your data and keep it safe from unexpected data loss or downtime.
This book covers best practices for stable MongoDB deployments. For example, a well-designed MongoDB cluster should have no single point of failure. The book covers common use cases when only one or two data centers are available. It goes into detail about creating geopolitical sharding configurations to cover the most stringent data protection regulation compliance. The book also covers different tools and approaches for automating and monitoring a cluster with Kubernetes, Docker, and popular cloud provider containers.

What You Will LearnGet started with the basics of MongoDB clustersProtect and monitor a MongoDB deploymentDeepen your expertise around replication and shardingKeep effective backups and plan ahead for disaster recoveryRecognize and avoid problems that can occur in distributed databasesBuild optimal MongoDB deployments within hardware and data center limitations
Who This Book Is For
Solutions architects, DevOps architects and engineers, automation and cloud engineers, and database administrators who are new to MongoDB and distributed databases or who need to scale up simple deployments. This book is a complete guide to planning a deployment for optimal resilience, performance, and scaling, and covers all the details required to meet the new set of data protection regulations such as the GDPR. This book is particularly relevant for large global organizations such as financial and medical institutions, as well as government departments that need to control data in the whole stack and are prohibited from using managed cloud services.

Table of Contents

Frontmatter
Chapter 1. Core Concepts
Abstract
For those coming from the world of traditional relational database management systems or even enterprise-level Microsoft SQL Server or Oracle, MongoDB presents an innovative way of thinking about scaling and availability. This chapter introduces all the core concepts of MongoDB deployments and explains how MongoDB nodes achieve high-availability, low-latency replication, and handle unexpected infrastructure failures.
Nicholas Cottrell
Chapter 2. Fault-Tolerant Design
Abstract
This chapter delves deeper into the fault-tolerant nature of MongoDB and explores some of the special types of nodes and how they should be used on production systems. We look at common errors that may occur in real-world systems and how to mitigate them.
Nicholas Cottrell
Chapter 3. Security
Abstract
This chapter looks at the main security features related to MongoDB cluster designs, including how to secure a system at the infrastructure level, and to encrypt data in transit and at rest, and how to protect against attacks via application code and interfaces.
Nicholas Cottrell
Chapter 4. Compliance and GDPR
Abstract
The ability to store humongous amounts of data creates opportunities for powerful analytical insights. With the advent of new data protection regulations around the world, it also creates compliance and security risks for companies because data is often dumped into data lakes or data warehouses without proper labeling, auditing, or policy enforcement.
Nicholas Cottrell
Chapter 5. Basic Topologies
Abstract
This chapter walks through common deployment topologies depending on the number of data centers available. We address the limitations of each topology and how to best configure nodes and backups to optimize availability.
Nicholas Cottrell
Chapter 6. Global Topologies
Abstract
This chapter continues with a deeper dive on topology recommendations for different types of global sharding options depending on whether low latency or data control/sovereignty is the priority.
Nicholas Cottrell
Chapter 7. Deployment and Monitoring
Abstract
This chapter looks at the most common tools and techniques for automating MongoDB deployments in production, on-prem, and in cloud-based self-managed environments. We also review different monitoring solutions and tips to help DevOps teams avoid issues and react quickly to changes in the deployment.
Nicholas Cottrell
Chapter 8. Special Use Cases and Configurations
Abstract
In this chapter, we cover a series of use cases for specific configurations of MongoDB in production, such as hybrid on-prem/cloud clusters, low-latency applications, using an LDAP pool for authentication, and how to store large binary files.
Nicholas Cottrell
Chapter 9. Backups and Restores
Abstract
This chapter covers backup decisions related to topology design. We look at MongoDB’s own enterprise tools for performing point-in-time restores of sharded cluster, to using scripts to snapshot geographically sharded clusters and retaining backup data in the same country of origin to comply with GDPR.
Nicholas Cottrell
Chapter 10. Advanced Sharding
Abstract
In this chapter, we expand the discussion on sharding by planning for deployments with very large datasets or extensive write workloads. We review challenging for sharding in these cases and explore methods to avoid or mitigate problems as the data grows.
Nicholas Cottrell
Chapter 11. Extreme Sharding
Abstract
This chapter goes even deeper into sharding specifics and introduces configurations that can increase write throughput when faced with hardware constraints. We also look at partitioning user data to adhere to data protection regulations, minimize costs, and optimize reads across shards.
Nicholas Cottrell
Backmatter
Metadata
Title
MongoDB Topology Design
Author
Nicholas Cottrell
Copyright Year
2020
Publisher
Apress
Electronic ISBN
978-1-4842-5817-0
Print ISBN
978-1-4842-5816-3
DOI
https://doi.org/10.1007/978-1-4842-5817-0

Premium Partner

    Image Credits