Metrics collection in HLD - Architecture Diagram

System Overview - Metrics collection

This system collects and stores metrics from various services to monitor performance and health. It must handle high volumes of data, provide near real-time insights, and support querying for analysis.

Architecture Diagram

User Services
    |
    v
Load Balancer
    |
    v
API Gateway
    |
    v
Metrics Collector Service
    |
    v
Message Queue
    |
    v
Metrics Processor Service
    |
    v
Time-Series Database
    |
    v
Cache
    |
    v
Dashboard/UI

Components

User Services

service

Generate and send metrics data

Load Balancer

load_balancer

Distribute incoming metric data requests evenly

API Gateway

api_gateway

Authenticate and route metric data requests

Metrics Collector Service

service

Receive and validate incoming metrics

Message Queue

queue

Buffer metrics for asynchronous processing

Metrics Processor Service

service

Aggregate and transform metrics before storage

Time-Series Database

database

Store time-stamped metrics efficiently

Cache

cache

Speed up frequent metric queries

Dashboard/UI

service

Display metrics and analytics to users

Request Flow - 8 Hops

User Services → Load Balancer

Load Balancer → API Gateway

API Gateway → Metrics Collector Service

Metrics Collector Service → Message Queue

Metrics Processor Service → Message Queue

Metrics Processor Service → Time-Series Database

Dashboard/UI → Cache

Cache → Dashboard/UI

Failure Scenario

Component Fails:Message Queue

Impact:Metrics processing delays; metrics may be lost if queue is full or down

Mitigation:Use replicated queue clusters and persistent storage to avoid data loss; alert on queue health

Architecture Quiz - 3 Questions

Which component buffers metrics for asynchronous processing?

A Message Queue

B API Gateway

C Cache

D Load Balancer

Design Principle

This design uses asynchronous processing with a message queue to handle high volumes of metrics efficiently. Caching improves query speed for dashboards, and a time-series database stores data optimized for time-based queries.

Practice

1. What is the main purpose of using aggregate functions like COUNT, SUM, and AVG in metrics collection?

easy

A. To create new tables for storing data

B. To change the structure of the database tables

C. To calculate totals, averages, and counts from data

D. To delete unwanted data from the database

Solution

1. Step 1: Understand aggregate functions

   Aggregate functions like COUNT, SUM, and AVG are used to calculate summary values from multiple rows of data.

2. Step 2: Identify their purpose in metrics

   These functions help get totals, averages, and counts which are useful for metrics and reports.

3. Final Answer:

   To calculate totals, averages, and counts from data -> Option C

4. Quick Check:

   Aggregate functions = summary numbers [OK]

Hint: Aggregate functions summarize data into numbers fast [OK]

Common Mistakes:

• Thinking aggregate functions modify data structure
• Confusing aggregate functions with data deletion
• Believing aggregate functions create tables

2. Which of the following SQL queries correctly counts the number of orders in a table named Orders?

easy

A. SELECT COUNT(Orders) FROM *;

B. SELECT COUNT FROM Orders;

C. SELECT SUM(*) FROM Orders;

D. SELECT COUNT(*) FROM Orders;

Solution

1. Step 1: Recall correct COUNT syntax

   The correct syntax to count rows is COUNT(*) inside SELECT.

2. Step 2: Check each option

   SELECT COUNT(*) FROM Orders; uses COUNT(*) correctly. Others have syntax errors or wrong functions.

3. Final Answer:

   SELECT COUNT(*) FROM Orders; -> Option D

4. Quick Check:

   COUNT(*) counts rows correctly [OK]

Hint: Use COUNT(*) to count all rows in a table [OK]

Common Mistakes:

• Omitting parentheses after COUNT
• Using COUNT without specifying columns or *
• Confusing SUM with COUNT

3. Given the table Sales with columns amount and region, what will this query return?

SELECT AVG(amount) FROM Sales WHERE region = 'East';

medium

A. The average sales amount for the East region

B. The total sales amount for all regions

C. The count of sales records in the East region

D. An error because AVG cannot be used with WHERE

Solution

1. Step 1: Understand the WHERE clause effect

   The WHERE clause filters rows to only those where region is 'East'.

2. Step 2: Understand AVG function

   AVG calculates the average of the filtered amount values.

3. Final Answer:

   The average sales amount for the East region -> Option A

4. Quick Check:

   AVG with WHERE filters = average for filtered data [OK]

Hint: WHERE filters rows before aggregate functions run [OK]

Common Mistakes:

• Thinking AVG returns total sum
• Confusing COUNT with AVG
• Believing WHERE cannot be used with aggregates

4. Identify the error in this SQL query that tries to get the total sales for the 'West' region:

SELECT SUM(amount) FROM Sales WHERE region == 'West';

medium

A. Using double equals (==) instead of single equals (=) in WHERE clause

B. SUM cannot be used with WHERE clause

C. Missing GROUP BY clause for aggregation

D. amount column cannot be summed

Solution

1. Step 1: Check WHERE clause syntax

   SQL uses single equals (=) for comparison, not double equals (==).

2. Step 2: Confirm aggregate and WHERE usage

   SUM works with WHERE filtering; GROUP BY is not needed here.

3. Final Answer:

   Using double equals (==) instead of single equals (=) in WHERE clause -> Option A

4. Quick Check:

   Use = for comparisons in SQL WHERE [OK]

Hint: Use single = for comparisons in SQL WHERE [OK]

Common Mistakes:

• Using == instead of = in WHERE
• Thinking GROUP BY is always required with SUM
• Assuming SUM cannot be used with WHERE

5. You want to find the average order amount per customer but only for customers who placed more than 5 orders. Which SQL approach correctly achieves this?

hard

A. Use WHERE COUNT(*) > 5 and SELECT AVG(amount) without GROUP BY

B. Use GROUP BY customer_id with HAVING COUNT(*) > 5 and SELECT AVG(amount)

C. Use WHERE AVG(amount) > 5 and GROUP BY customer_id

D. Use HAVING AVG(amount) > 5 without GROUP BY

Solution

1. Step 1: Understand grouping by customer

   To get average per customer, group rows by customer_id.

2. Step 2: Filter groups with more than 5 orders

   Use HAVING with COUNT(*) > 5 to keep only customers with more than 5 orders.

3. Step 3: Select average order amount

   Use AVG(amount) in SELECT to get average per filtered customer group.

4. Final Answer:

   Use GROUP BY customer_id with HAVING COUNT(*) > 5 and SELECT AVG(amount) -> Option B

5. Quick Check:

   GROUP BY + HAVING filters groups before AVG [OK]

Hint: Use HAVING to filter groups after GROUP BY [OK]

Common Mistakes:

• Using WHERE to filter aggregated counts
• Forgetting GROUP BY when using aggregates per group
• Using HAVING without GROUP BY