Why serving architecture affects latency and cost in MLOps - Visual Breakdown

Process Flow - Why serving architecture affects latency and cost

Client sends request

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Serving Architecture Choice

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Monolithic

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Process Request

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Response Sent

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Latency & Cost Impact Based on Architecture

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User Experience & Budget Outcome

The flow shows how the choice of serving architecture affects how requests are processed, which impacts latency and cost, ultimately influencing user experience and budget.

Execution Sample

MLOps

# Pseudocode for request handling
architecture = 'serverless'
if architecture == 'monolithic':
    latency = 100
    cost = 50
elif architecture == 'microservices':
    latency = 70
    cost = 70
else:
    latency = 50
    cost = 90

This code simulates how different serving architectures affect latency and cost values.

Process Table

Step	Architecture	Condition	Latency (ms)	Cost ($)	Explanation
1	monolithic	architecture == 'monolithic'	100	50	Monolithic chosen: higher latency, lower cost
2	microservices	architecture == 'microservices'	70	70	Microservices chosen: balanced latency and cost
3	serverless	else	50	90	Serverless chosen: lowest latency, highest cost
4	-	End of decision	-	-	Latency and cost set based on architecture

💡 All architecture options evaluated, latency and cost assigned accordingly

Status Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	Final
architecture	undefined	monolithic	microservices	serverless	serverless
latency	undefined	100	70	50	50
cost	undefined	50	70	90	90

Key Moments - 3 Insights

Why does serverless architecture have higher cost but lower latency?

Serverless runs code on demand with fast scaling, reducing latency, but the pay-per-use model increases cost as shown in execution_table row 3.

Why does monolithic architecture have higher latency but lower cost?

Monolithic runs all in one place, causing slower response (higher latency) but simpler infrastructure lowers cost, as seen in execution_table row 1.

How does microservices balance latency and cost?

Microservices split functions, improving latency over monolithic but adding overhead costs, balancing both as shown in execution_table row 2.

Visual Quiz - 3 Questions

Look at the execution_table, what is the latency value when architecture is microservices?

A 100 ms

B 70 ms

C 50 ms

D 90 ms

💡 Hint

Check execution_table row 2 under 'Latency (ms)' column

At which step does the cost become highest according to the execution_table?

A Step 3

B Step 2

C Step 1

D Step 4

💡 Hint

Look at the 'Cost ($)' column in execution_table rows

If the architecture changed from serverless to monolithic, how would latency and cost change?

A Latency decreases, cost increases

B Both latency and cost increase

C Latency increases, cost decreases

D Both latency and cost decrease

💡 Hint

Compare latency and cost values in execution_table rows 1 and 3

Concept Snapshot

Serving architecture affects latency and cost:
- Monolithic: higher latency, lower cost
- Microservices: balanced latency and cost
- Serverless: lowest latency, highest cost
Choose based on user experience needs and budget.

Full Transcript

This visual execution shows how different serving architectures impact latency and cost. The client sends a request, which is processed differently depending on the architecture chosen: monolithic, microservices, or serverless. Each architecture affects latency and cost differently. Monolithic has higher latency but lower cost due to simpler infrastructure. Microservices improve latency but add overhead cost. Serverless offers the lowest latency with fast scaling but costs more due to pay-per-use pricing. The execution table traces these values step-by-step, and the variable tracker shows how latency and cost change with architecture. Understanding these trade-offs helps choose the right serving architecture for balancing user experience and budget.