System Design Document Template

System design at scale – requirements, capacity estimates (KaTeX), API, data model, HLD, deep dives, reliability, cost, trade-offs

आर्किटेक्चर और सिस्टम डिज़ाइनपूर्णsystem design document mathअपडेट किया गया 20 अक्टू॰ 2026

एडिटर में खोलें.md डाउनलोड करें

उपयोग कैसे करें: New services or major redesigns. Write requirements and capacity estimates before any diagram, keep every estimate as a formula with its inputs, and fill section 10 with the options you rejected – reviewers will ask. Replace the URL-shortener example numbers with your own.

प्रीव्यू

System Design: [System or feature name]

Complete system design document for a service or platform at scale: requirements, capacity estimates, API, data model, high-level and detailed design, scaling, reliability, security, operations, cost and trade-offs. Replace every [bracketed] value and every value marked Example. Worked numbers use a URL-shortening service so the formulas stay concrete; swap in your own.

Document control

Field	Value
Document ID	[SDD-SYSTEM-001]
System / feature	[Name]
Version	[0.1]
Status	[Draft / In review / Approved / Implemented / Superseded]
Author(s)	[@author]
Reviewers	[@reviewer-1], [@reviewer-2]
Last updated	YYYY-MM-DD
Related	[PRD / SRS], [Architecture description], [ADRs]

Approvals

Role	Name	Decision	Date
Tech lead	[@name]	[Approved / Changes requested]	YYYY-MM-DD
Staff / principal engineer	[@name]	[Decision]	YYYY-MM-DD
SRE / operations	[@name]	[Decision]	YYYY-MM-DD
Security	[@name]	[Decision]	YYYY-MM-DD

Revision history

Version	Date	Author	Change summary
0.1	YYYY-MM-DD	[@name]	First draft for design review
0.2	YYYY-MM-DD	[@name]	Example: Switched ID generation to base62 counter ranges after review
1.0	YYYY-MM-DD	[@name]	Example: Approved

Overview
Requirements
Capacity estimation
API design
Data model
High-level design
Detailed design
Scalability and performance
Reliability, security and operations
Trade-offs and alternatives
Delivery plan and risks
Appendices

1. Overview

1.1 Problem statement

[What problem exists today, who has it, and what it costs. Example: "Our marketing links are 120+ characters, break in SMS, and give us no click data."]

1.2 Proposed solution

[One paragraph. Example: "A stateless redirect service backed by a key-value store and a CDN, generating 7-character base62 keys from pre-allocated counter ranges, with click events streamed to the analytics pipeline."]

1.3 Decisions requested from reviewers

ID	Question	Recommended option	Section
Q-01	Example: Counter ranges or hashing for key generation?	Counter ranges	7.1, 10
Q-02	Example: Accept eventual consistency for click counts?	Yes, up to 60 s lag	7.3
[Q-nn]	[Question]	[Option]	[Section]

2. Requirements

2.1 Functional requirements

ID	Requirement	Priority
FR-01	Example: Create a short link for a long URL, optionally with a custom alias	Must
FR-02	Example: Redirect a short link to its long URL	Must
FR-03	Example: Expire links at an optional expiry date	Should
FR-04	Example: Show click counts per link per day	Should
[FR-nn]	[Requirement]	[Must / Should / Could]

2.2 Non-functional requirements

ID	Quality	Target	Measured as
NFR-01	Latency	Example: Redirect p99 at or below 50 ms at the edge	Edge logs, rolling 5 min
NFR-02	Availability	Example: 99.99% monthly for redirects	Synthetic checks
NFR-03	Durability	Example: No created link is ever lost	Backup and restore drills
NFR-04	Consistency	Example: A new link redirects within 1 s of creation	Integration test
NFR-05	Security	Example: No open redirect to blocklisted domains	Security test suite
[NFR-nn]	[Quality]	[Target]	[Measurement]

2.3 Out of scope

[Example: link editing after creation]
[Example: user accounts beyond API keys]
[Item deferred, with the release that will take it]

3. Capacity estimation

3.1 Assumptions

Input	Symbol	Value	Source
New links per month	$N_w$	Example: 100 million	Marketing forecast
Read to write ratio	$r$	Example: 100 : 1	Comparable services
Average stored record	$s$	Example: 500 bytes	Schema in 5.2
Retention	$Y$	Example: 5 years	Product decision
Peak to average factor	$k$	Example: 3	Traffic history

3.2 Throughput

Average write rate, with $2.6 \times 10^6$ seconds in a month:

QPS_w = \frac{N_w}{2.6 \times 10^{6}} = \frac{10^{8}}{2.6 \times 10^{6}} \approx 40 \ \text{writes/s}

Reads and peak:

QPS_r = r \cdot QPS_w \approx 4\,000 \ \text{reads/s}, \qquad QPS_{peak} = k \cdot QPS_r \approx 12\,000 \ \text{reads/s}

3.3 Storage

S = N_w \times 12 \times Y \times s = 10^{8} \times 12 \times 5 \times 500 \ \text{B} = 3 \ \text{TB}

With replication factor 3 the raw footprint is about 9 TB.

3.4 Bandwidth and memory

B_{out} \approx QPS_{peak} \times 500 \ \text{B} \approx 6 \ \text{MB/s}

Caching the hottest 20% of daily read keys (Pareto assumption):

M = 0.2 \times QPS_r \times 86\,400 \times s \approx 35 \ \text{GB}

3.5 Key space

With base62 keys of length $L$ the key space is $62^{L}$ . For $L = 7$ :

62^{7} \approx 3.5 \times 10^{12} \gg 6 \times 10^{9} \ \text{links in 5 years}

3.6 Summary

Quantity	Estimate	Design consequence
Write rate	~40/s average	A single partitioned store handles writes
Read rate	~4 000/s average, ~12 000/s peak	Reads must be served from cache and CDN
Storage	~3 TB logical, ~9 TB replicated	Horizontally partitioned key-value store
Cache	~35 GB	Fits a small in-memory cache cluster
[Quantity]	[Estimate]	[Consequence]

4. API design

4.1 Endpoints

Method	Path	Purpose	Auth	Idempotent
POST	`/v1/links`	Create a short link	API key	With `Idempotency-Key` header
GET	`/{key}`	Redirect (302) to the long URL	None	Yes
GET	`/v1/links/{key}`	Read link metadata	API key	Yes
GET	`/v1/links/{key}/stats?from=&to=`	Daily click counts	API key	Yes
DELETE	`/v1/links/{key}`	Disable a link	API key	Yes

4.2 Request and response examples

Create a link. The Idempotency-Key header makes retries safe: the same key within 24 hours returns the original response instead of a second link.

POST /v1/links HTTP/1.1
Content-Type: application/json
Idempotency-Key: 7f9c2ba4-e88f-11ee-a951-0242ac120002

{"url": "https://example.com/campaigns/spring?utm_source=sms", "alias": null, "expiresAt": "2027-01-01T00:00:00Z"}

HTTP/1.1 201 Created
Location: /v1/links/aZ3kP9q
Content-Type: application/json

{"key": "aZ3kP9q", "shortUrl": "https://sho.rt/aZ3kP9q", "url": "https://example.com/campaigns/spring?utm_source=sms", "expiresAt": "2027-01-01T00:00:00Z"}

4.3 Errors

HTTP/1.1 409 Conflict
Content-Type: application/problem+json

{"type": "https://sho.rt/problems/alias-taken", "title": "Alias already in use", "status": 409, "detail": "The alias 'spring' belongs to another link.", "instance": "/v1/links"}

Status	Problem type	When
400	`invalid-url`	URL is malformed or not http(s)
403	`blocked-domain`	Target domain is on the abuse blocklist
409	`alias-taken`	Custom alias exists
429	`rate-limited`	Client exceeded its quota; `Retry-After` is set

4.4 Rate limits and versioning

Rate limit: [Example: 100 creates per minute per API key, token bucket].
Versioning: path prefix /v1; breaking changes go to /v2 with a [12-month] deprecation window announced by the Deprecation header.

5. Data model

5.1 Entities

Logical entities and their keys. Physical types depend on the stores chosen in 5.2.

5.2 Storage choices

Data	Store	Partition key	Main queries	Why
Links	Example: Distributed key-value store	`key`	Get by key	Single-key lookups at high read rate
Daily clicks	Example: Wide-column or time-series store	`key`, `day`	Range by key and day	Append-heavy counters
API keys	Example: Relational database	`id`	Get by id	Small, transactional
[Data]	[Store]	[Key]	[Queries]	[Reason]

6. High-level design

Component	Responsibility	Scales by
CDN / edge cache	Serve popular redirects close to users	Provider
Redirect service	Resolve key, emit click event, return 302	Stateless replicas
Link API service	Create, read, disable links; enforce quotas	Stateless replicas
Key range allocator	Hand out unique counter ranges to API instances	Single leader, rarely called
Click aggregator	Turn click events into daily counts	Consumer group partitions
[Component]	[Responsibility]	[Scaling unit]

7. Detailed design

7.1 Key generation

[Describe the algorithm. Example: each API instance leases a block of 1 000 000 counter values from the allocator, encodes the next value in base62 and pads to 7 characters. Leases are stored durably; a crashed instance wastes at most one block. Custom aliases are inserted with a conditional write that fails if the key exists.]

7.2 Redirect path

The redirect never waits for analytics: the click event is published asynchronously after the long URL is known, and a cache miss repopulates the cache for later requests.

7.3 Click counting

[Example: redirect instances publish click events without waiting; the aggregator consumes per partition, counts in memory for 30 s and adds the totals to the daily row. Counts may lag by up to 60 s and may over-count by duplicates on consumer restart; dashboards state this.]

7.4 Expiry and deletion

[Example: expiry is checked on read; a daily job removes expired links from the store and purges them from the CDN.]

8. Scalability and performance

Concern	Approach	Limit before redesign
Read throughput	CDN and in-memory cache absorb most reads; redirect service scales horizontally	Example: ~200 000 reads/s per region
Write throughput	Partitioned key-value store; key ranges avoid coordination	Example: ~5 000 writes/s
Hot keys	CDN caching with short TTL; request coalescing in the redirect service	One viral link at ~50 000 reads/s
Storage growth	Add partitions; expire old links	[Limit]
[Concern]	[Approach]	[Limit]

Latency budget for a redirect cache miss (target p99 50 ms):

Step	Budget
Edge to region network	20 ms
Load balancer and service	5 ms
Cache lookup	2 ms
Key-value lookup on cache miss	10 ms
Headroom	13 ms

9. Reliability, security and operations

9.1 Failure modes

Failure	Impact	Detection	Mitigation
Cache cluster down	Higher latency, more store load	Cache error rate	Fall through to store; store sized for full read load at reduced latency
Key-value store partition unavailable	Some keys fail	Error rate per partition	Replication factor 3, quorum reads
Event stream down	Click counts lag	Consumer lag alert	Redirects never block on events; replay from buffer
Region outage	Full outage in region	Synthetic checks	Active-active in two regions with replicated store
[Failure]	[Impact]	[Signal]	[Mitigation]

9.2 Security and abuse

Threat	Control
Malicious target URLs (phishing, malware)	Domain blocklist and URL reputation check at creation; periodic rescans
Key enumeration	Non-sequential presentation of keys; rate limits on reads per IP
API key leakage	Keys hashed at rest, per-key quotas, rotation endpoint
Data exposure	TLS everywhere; minimal personal data; access logging
[Threat]	[Control]

9.3 Observability

Signal	Metric or log	Alert threshold
Redirect latency	p50, p99 per region	p99 above 50 ms for 10 min
Redirect errors	5xx rate	Above 0.1% for 5 min
Cache hit ratio	Hits / requests	Below 85% for 30 min
Click pipeline lag	Consumer lag seconds	Above 120 s
[Signal]	[Metric]	[Threshold]

9.4 Cost estimate

Item	Unit cost	Quantity	Monthly cost
Compute (redirect + API)	[$/instance-month]	[n]	[$]
Key-value store	[$/TB-month]	[9 TB]	[$]
Cache	[$/GB-month]	[35 GB]	[$]
CDN egress	[$/GB]	[GB/month]	[$]
Total			[$]

10. Trade-offs and alternatives

Decision	Options	Chosen	Why	What we give up
Key generation	Hash of URL; random keys with collision check; counter ranges	Counter ranges	No collisions, no read-before-write	Keys reveal rough creation order unless shuffled
Redirect status	301 permanent; 302 temporary	302	Every click reaches us for counting and disabling	More origin traffic than 301
Click counts	Synchronous increment; async stream	Async stream	Redirect latency unaffected	Counts lag up to 60 s
[Decision]	[Options]	[Chosen]	[Why]	[Cost]

11. Delivery plan and risks

11.1 Milestones

Milestone	Scope	Exit criterion	Target date
M1	Create and redirect, single region	Load test at 2x peak passes	YYYY-MM-DD
M2	Click counts and dashboards	Lag below 60 s for 7 days	YYYY-MM-DD
M3	Second region, active-active	Region failover drill passes	YYYY-MM-DD
[Mn]	[Scope]	[Criterion]	YYYY-MM-DD

11.2 Rollout and rollback

[Feature flags, canary percentage, metrics watched during rollout, and the exact rollback steps.]

11.3 Risks

ID	Risk	Likelihood	Impact	Mitigation	Owner
R-01	Example: Traffic forecast is 3x too low	Medium	High	Load test at 5x; autoscaling limits reviewed	[@name]
R-02	Example: Abuse overwhelms blocklist process	Medium	Medium	Automated reputation service; manual review queue	[@name]
[R-nn]	[Risk]	[L / M / H]	[L / M / H]	[Mitigation]	[@name]

12. Appendices

12.1 Open questions

ID	Question	Owner	Due
OQ-01	Example: Do we need per-link analytics beyond daily counts?	[@name]	YYYY-MM-DD
[OQ-nn]	[Question]	[@name]	YYYY-MM-DD

12.2 Glossary

Term	Meaning
QPS	Queries (requests) per second
p99	99th percentile latency
TTL	Time to live of a cached entry
Base62	Encoding with digits, lowercase and uppercase letters
[Term]	[Meaning]

12.3 References

Reference	Use
RFC 9110 HTTP Semantics	Status codes and methods
RFC 9457 Problem Details for HTTP APIs	Error format in 4.3
[Internal ADR or document]	[Use]

Standard and licence note

Based on common industry practice for system design documents and on the HTTP standards cited in 12.3. Original text written for this collection; example numbers are illustrative. Template licence: MIT.