Based on the Linux Master 2 exam syllabusReport an error
[ User ]
│
▼
┌─────────────────────────────┐
│ Several computers (nodes) │
│ are tied together and │
│ look like a single machine │
│ ▢ ▢ ▢ ▢ │
└─────────────────────────────┘| Category | Scale-up | Scale-out |
|---|---|---|
| Method | Replace one machine with better parts | Increase the number of machines |
| Limit | Part performance has a ceiling and the price rises sharply | More machines means more to manage |
| Failure | If that one machine stops, everything stops | If one machine stops, the rest remain |
| Relation to clusters | — | A cluster is this approach |
| Type | Purpose | Keywords |
|---|---|---|
| HPC cluster (High Performance Computing) | Fast computation | Parallel processing, supercomputer |
| HA cluster (High Availability) | A service that never stops | Redundancy, failover |
| LB cluster (Load Balancing) | Split requests and process them | Traffic distribution |
Memorizing the definitions separately is the whole point of this unit. Questions come in the form of picking which of the three is being described.
The quickest question for telling the three apart is "what do the machines share?"
| Question | HPC | HA | LB |
|---|---|---|---|
| What is split | One big job, broken into pieces | Nothing is split. They only stand ready to do the same job | Many unrelated requests, one at a time |
| Relationship between nodes | Cooperate, exchanging pieces | Monitor each other | Don't need to know each other |
| Criterion for success | Computation finishes quickly | The service never gets cut off | Many requests are handled |
| If one machine stops | The job slows down or must be rerun | The standby node takes over | The remaining nodes share the requests |
| Representative name | Beowulf | heartbeat | LVS |
| Item | Details |
|---|---|
| Full name | High Performance Computing |
| Purpose | Process one big computation split up and run at the same time |
| Used for | Weather forecasting, genome analysis, simulation |
| Representative | Beowulf cluster |
User ──► Master node ──┬── Compute node 1 computes piece A
(splits the ├── Compute node 2 computes piece B
job, hands ├── Compute node 3 computes piece C
out pieces, └── Compute node 4 computes piece D
collects │
results) ▲ │
└── results merged into one answer ──┘| Item | Details |
|---|---|
| Full name | High Availability |
| Purpose | Keep the service running even when a failure occurs |
| Method | Normally the primary server works, and when it dies the standby server takes over |
| Keywords | Redundancy · failover · heartbeat |
Primary server (Active) ──── serving
│ heartbeat checks that each is alive
Standby server (Standby) ── waiting
If the primary dies → the standby takes over immediately (failover)The terms used in an HA setup follow one after another.
| Term | Meaning |
|---|---|
| Single point of failure (SPOF) | A point where, if that one thing stops, everything stops. High availability is about eliminating these |
| Redundancy | Having two or more devices that play the same role |
| Heartbeat | The "I'm alive" signal that nodes exchange periodically |
| Failover | When the signal stops, the standby node takes over the role |
| Failback | After repairing the failed node, returning to the original arrangement |
| Setup | Normally | On failure | Characteristics |
|---|---|---|---|
| Active-Standby | Only one machine works and the other stands by | The standby server takes over | Simple. The standby machine sits idle normally |
| Active-Active | Both work | The remaining machine takes on everything | Uses all resources, but one machine must have enough headroom to carry the load alone |
Availability is "the percentage of time alive", so it is promised as a number. Each additional 9 cuts the allowed downtime to one tenth.
| Availability | Allowed downtime per year |
|---|---|
| 99% | About 3.65 days |
| 99.9% | About 8.76 hours |
| 99.99% | About 53 minutes |
| 99.999% | About 5 minutes |
| Item | Details |
|---|---|
| Full name | Load Balancing |
| Purpose | Distribute incoming requests across several servers |
| Used for | Web servers and services with heavy traffic such as online shops |
| Representative | LVS (Linux Virtual Server) |
Requests
│
┌─────┴─────┐
Load balancer
┌────┬────┬────┐
Web1 Web2 Web3 Web4LVS (Linux Virtual Server) is a project that builds a load balancer with a feature of the Linux kernel.
| Name | Role |
|---|---|
| Virtual IP (VIP) | One representative address that users connect to. Users do not know how many servers are behind it |
| Director | The load balancer that receives requests and passes them back |
| Real server | The back-end servers that actually process the requests |
ipvsadm | The admin command that configures LVS distribution rules |
| Scheduling | Selection criterion |
|---|---|
| Round Robin | Takes turns, rotating one request at a time |
| Weighted Round Robin | More often to higher-performance servers |
| Least Connection | To the server with the fewest connections right now |
| Weighted Least Connection | Considers the server's performance weight as well as the connection count |
Web services usually combine load balancing and high availability. Splitting requests across several servers (load balancing) while the rest keep handling requests even if one dies (high availability) means the two goals fit together naturally.
User requests
│
┌─────────────┴─────────────┐
Balancer A (Active) ══heartbeat══ Balancer B (Standby) ← high availability
└─────────────┬─────────────┘
┌───────┼───────┐
Web1 Web2 Web3 ← load balancing| Situation | What is needed | Combination |
|---|---|---|
| A busy online shop or portal | Request distribution + no downtime | Load balancing + high availability |
| Weather forecasting, genome analysis | Big computation, quickly | HPC |
| A bank ledger DB with few requests that must never stop | No downtime | High availability |
Passages leak keywords instead of the cluster name. Practice picking the box from the words.
| Expression in the passage | Answer |
|---|---|
| "One big computation is split among several nodes and run in parallel" | HPC |
| "Supercomputer-class performance with cheap PCs" | HPC (Beowulf) |
| "Using parallel libraries such as MPI and PVM" | HPC |
| "So that the service does not stop even if a failure occurs" | HA |
| "Primary and standby servers, checking status with a heartbeat" | HA |
| "Redundancy", "failover" | HA |
| "Spread incoming requests evenly across several servers" | Load balancing |
| "Large volumes of web traffic", "round robin" | Load balancing |
| "LVS", "several servers behind a single virtual IP" | Load balancing |
| "Using the spare resources of geographically separated computers" | Not a cluster but a grid |
| Concept | Meaning |
|---|---|
| Cluster | Several computers tied together as one — same location, tightly connected |
| Grid computing | Gathers and uses the spare resources of computers that are scattered |
| Cloud computing | A service model where you rent resources |
| Embedded system | A system built into a device for a specific function |
Tomorrow we cover virtualization technologies and the features of each product.
Click a choice to reveal the answer and explanation.
Question 1
Which of the following is the cluster configured so that the service does not stop even if a failure occurs in the system?
Question 2
Which of the following is hard to consider a type of cluster?
Question 3
Which of the following is the classic HPC cluster built by tying cheap PCs together with Linux?
Question 4
Which of the following is the cluster that distributes incoming requests across several servers to increase throughput?
Question 5
Which of the following is the combination of clusters generally applied together when building a web service with heavy traffic?