Recognize and interpret essential integration concepts and terminology20% of the exam

Virtualization, containers and system scalability

The compute and storage building blocks behind Mule deployments (virtual machines, bare-metal servers, containers on Kubernetes, replica disk and external object stores) and the principles of vertical and horizontal scaling, high availability clusters and load balancing.

Official exam objective
Identify the types of virtualization, computing, and storage infrastructure required by enterprise systems and describe the principles of system scalability.

~7 min read · 3 practice questions ·

What the exam expects

  • Identify the compute options enterprise systems run on: bare-metal servers, virtual machines and containers orchestrated by Kubernetes.
  • Explain what a hypervisor does and tell block, file and object storage apart.
  • Distinguish local, volatile storage on a runtime instance from external persistent storage such as an object store or persistent queue.
  • Tell vertical scaling (a bigger node) from horizontal scaling (more nodes) and name the limits of each.
  • Explain how a high availability cluster and a load balancer keep a service running when a node fails.

Key terms:

  • Virtual machine (VM): a virtualized server, as opposed to a bare-metal server.
  • Hypervisor: software installed on a host machine that provisions the resources to create and run virtual machines.
  • Container: an isolated unit that runs one application's runtime; Kubernetes orchestrates many of them.
  • Vertical scaling: adding cores or memory to one node (scale up).
  • Horizontal scaling: adding nodes, replicas or workers that share the workload (scale out).
  • High availability (HA) cluster: multiple nodes acting as a unit so that service continues when one fails.

Key facts

Runtime Fabric infrastructure
Detail
Customer-managed Kubernetes on AWS, Azure, VMs or bare metal
Hypervisor
Detail
Installed on a host machine; provisions and runs virtual machines
Container vs VM
Detail
Containers share the host OS and kernel; each VM has its own OS
Storage categories
Detail
Block (addressed chunks), file (hierarchy), object (flat, unique ID)
Runtime Fabric and Docker/Kubernetes
Detail
Older page: bundled; today's overview: you provide them; exam aligns to Spring '24
Runtime Fabric isolation
Detail
A separate Mule runtime server per application
CloudHub 2.0 isolation
Detail
Each replica runs in a separate container
CloudHub 2.0 vertical scaling
Detail
Choose a vCore size; minimum 8 GB storage per replica
CloudHub 2.0 local disk
Detail
Cleared on restart or redeploy; use Object Store v2 to persist
Persistent queue retention
Detail
Up to 4 days
Minimum Mule cluster
Detail
At least two Mule runtime engines on different machines
Active-active model
Detail
No primary server; any node takes over
Sources for this section (11)
  • Why can adding nodes slow down an application that relies heavily on Object Stores?
  • When does a CloudHub 2.0 application need Object Store v2 instead of its local disk?
  • How long can a message wait in a CloudHub persistent queue?

The questions are free to read. Answers with their sources and self-grading are included with the pack.

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