High Availability, Scaling, Workload Isolation

Question 1

High Availability

Answer 1

The ability of a database system to remain operational and accessible with minimal downtime, often achieved through redundancy and failover

Question 2

Replica Set

Answer 2

a group of nodes that maintain the same data set, providing redundancy and automatic failover for high availability

Question 3

Primary vs Secondary Node

Answer 3

Primary: the replica set member that accepts all write operations, replicating data to secondary nodes

Secondary Node: a replica set member that replicates data from the primary node and can serve read operations or become primary during failover

Question 4

Failover

Answer 4

Process where a replica set automatically elects a new primary node if the current primary fails

Question 5

Arbiter

Answer 5

A lightweight node in a replica set that participates in elections but does not store data, used to break ties in voting

Question 6

Write Concern

Answer 6

setting that specifies the number of nodes that must acknowledge a write operation to ensure data durability

Question 7

Scalability

Answer 7

the ability of a database to handle increased load (more users, data, queries) by adding resources or distributing workload

Question 8

Sharding

Answer 8

Method for horizontal scaling by distributing data across multiple servers (shards) based on a shard key

Question 9

shard

Answer 9

a single partition of a database, storing a subset of the data in a sharded cluster

Question 10

Shard Key

Answer 10

The field used by MongoDB to determine how data is distributed across shards, critical for efficient sharding

Question 11

Horizontal Scaling

Answer 11

Adding more servers (nodes or shards) to a database system to increase capacity, as opposed to upgrading a single server

Question 12

Vertical Scaling

Answer 12

Increasing the resources (CPU, RAM, storage) of a single server to handle more load, limited by hardware constraints

Question 13

Workload Isolation

Answer 13

The practice of separating different types of database workloads (e.g. transactional, analytical) to prevent resource contention and optimize performance

Question 14

Read/Write Separation

Answer 14

Directing read operations to secondary nodes and write operations to the primary node in a MongoDB replica set to isolate workloads and improve performance

Question 15

Dedicated Workload Clusters

Answer 15

Using separate MongoDB clusters or replica sets for distinct workloads (e.g. one for OLTP, another for analytics) to ensure resource isolation

Question 16

OLTP

Answer 16

Online Transaction Processing

A workload type focused on high speed, transactional operations (e.g. inserts, updates), requiring low latency and high availability

Question 17

OLAP

Answer 17

Oline Analytical Processing

Workload type focused on complex queries and data anlysis, often requiring significant compute resources and isolated from transactional workloads

Question 18

Analytics Node

Answer 18

A dedicated secondary node in a MongoDB replica set configured for analytical queries, isolating resource intensive OLAP workloads from transactional operations

Question 19

Zone Sharding

Answer 19

MongoDB sharding strategy that assigns data to specific shards based on tags, enabling workload isolation by directing queries to designated shards

Question 20

Resource Contention

Answer 20

Competition for system resouces (CPU, memory, disk) between workloads, mitigated through workload isolation techniques like read/write separation or dedicated clusters