Project: IoT Time-Series, TTL आणि Rollups — DynamoDB

By Ravindra Bagale, trainer · LinkedIn · Last updated: 31 October 2026

1. रोजचे उदाहरण: weather notebook

Raw TTL; averages rollup; shard spines.

2. Vertical steps

3. हे का लागतं?

हे का लागतं?

Hot PK + endless raw = pain. Shard+TTL+rollup.

4. हे काय आहे?

हे काय आहे?

Sharded raw + ROLLUP#hour; Streams worker.

5. कसं करायचं

कसं करायचं (step by step)

1. Patterns.
2. Shard+SK.
3. Table+TTL.
4. Ingest.
5. Rollup.
6. Query+cleanup.

6. Key sketch

7. Commands

aws dynamodb create-table --table-name lab-ddn-telemetry \
  --attribute-definitions AttributeName=PK,AttributeType=S AttributeName=SK,AttributeType=S \
  --key-schema AttributeName=PK,KeyType=HASH AttributeName=SK,KeyType=RANGE \
  --billing-mode PAY_PER_REQUEST --region ap-south-1
aws dynamodb update-time-to-live --table-name lab-ddn-telemetry \
  --time-to-live-specification "Enabled=true, AttributeName=expires_at"
aws dynamodb put-item --table-name lab-ddn-telemetry --item '{
 "PK":{"S":"DEVICE#d1#0"},"SK":{"S":"1730000000123"},
 "temp":{"N":"31.2"},"expires_at":{"N":"1730003600"}}'
aws dynamodb query --table-name lab-ddn-telemetry \
  --key-condition-expression "PK = :pk AND SK BETWEEN :a AND :b" \
  --expression-attribute-values '{":pk":{"S":"DEVICE#d1#0"},":a":{"S":"1730000000000"},":b":{"S":"1730001000000"}}'
# Output: window of points. Meaning: time Query on shard; rollups queried separately.

TTL seconds; shard; async rollup.

8. Industry stories

• Mfg
• Fleet
• Energy
• Agri
• Health
• City

9. Lab

कसं करायचं (step by step)

1. Start.
2. Rollup.
3. Cleanup.

Cleanup

1. Lab delete करा.
2. Confirm gone.

10. Ops checklist (ship आधी)

1. TTL attr + seconds.
2. Delete policy.
3. PITR on.
4. RPO/RTO doc.
5. Multi-region rules.
6. DAX miss path.
7. Tags.
8. Budget alert.

11. Copy-paste CLI starters

export AWS_DEFAULT_REGION=ap-south-1

# TTL status
aws dynamodb describe-time-to-live --table-name ShopApp

# PITR / continuous backups
aws dynamodb describe-continuous-backups --table-name ShopApp

# On-demand backup
aws dynamodb create-backup --table-name ShopApp --backup-name lab-shop-$(date +%Y%m%d)

# List backups
aws dynamodb list-backups --table-name ShopApp

# Global table description (v2)
aws dynamodb describe-table --table-name ShopApp --query 'Table.Replicas'

12. अजून industry stories

• Retail TTL carts
• Bank PITR drill
• Travel GT
• Gaming DAX
• Social edges
• IoT TTL

13. Glossary

14. Practice: मोठ्याने explain

1. 60s delete modes.
2. 60s PITR vs backup.
3. 60s GT.
4. 60s DAX.
5. 60s CartLite.
6. 60s social.
7. Record ×2.

15. Safe lab hygiene

• Budget alert.
• lab- prefix.
• Delete paid extras.
• GT write plan.
• Tags.
• S3 cleanup.

16. या set ची links

• Modeling
• Transactions
• Streams
• CRUD TTL
• Intro

17. Delete / archive pad

18. दहा oral drills

1. TTL units?
2. Instant?
3. PITR window?
4. GT conflict?
5. Sticky?
6. DAX vs?
7. Cart PK?
8. Lines PK?
9. Follow SK?
10. Unread GSI?

19. RPO / RTO mini workshop

1. RPO minutes.
2. RTO.
3. Map tools.
4. Drill.
5. Owner.

20. Cost watch list

• Backup storage
• GT writes
• DAX idle
• Export/S3
• TTL→Streams

21. Project Definition of Done

1. Patterns done.
2. Samples.
3. Lab hygiene.
4. Condition/txn.
5. Cleanup notes.
6. Oral.

22. Batch आतील links

• TTL→Backup
• GT→hot
• DAX after model
• P1 reuse
• P2 reuse

23. Quick self-check

1. TTL delay?
2. Soft vs hard?
3. PITR start?
4. GT no?
5. DAX≠key fix?
6. Cart keys?
7. Follow edge?
8. Cleanup habit?

24. सामान्य errors आणि fixes

प्रत्येक row = खरी चूक. Panic करण्याआधी fix वाचा.

25. Troubleshooting checklist

1. Shards.
2. Enable.
3. Idempotent.
4. Units.
5. Lag.

26. FAQ

27. Interview Q&A

28. Tips — English, मराठी आणि हिंदी

उजळणी, मुलाखत आणि तुलना cards

हा lesson काही मिनिटांत revise करा. Cards phone वर save करा किंवा PNG download करा. प्रत्येक card वरचा QR हा lesson उघडतो.

अजून cards: Ravi Sir's Cards.