Михаил Максимов ( Software engineer, DataArt. AWS certified Solution Architect)
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Serverless architectures allow developers to run code without provisioning or managing servers. With serverless, code runs in ephemeral containers that are managed by third-party cloud providers. Key benefits include automatic scaling, high availability, and paying only for the resources consumed. Some limitations are vendor lock-in, memory and computing limits per function, and potential cold start delays. Serverless functions can be triggered synchronously, asynchronously via events, or via streaming data sources. Common event sources that trigger serverless functions include S3, API Gateway, IoT, and SQS. Serverless is well suited for building event-driven architectures and processing streaming data at scale.
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Paper - 109: Literary Theory & Criticism and Indian Aesthetics
Submitted Date: April 5, 2025
Paper Name: Literary Theory & Criticism and Indian Aesthetics
Topic: Archetypal Journeys in ‘Interstellar’: Exploring Universal Themes in Nolan’s Cosmic Odyssey
[Please copy the link and paste it into any web browser to access the content.]
Video Link: https://youtu.be/vHLaLZPHumk
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Михаил Максимов ( Software engineer, DataArt. AWS certified Solution Architect)
- 2. Serverless architectures Maximov Mikhail Software engineer in DataArt Certified AWS Solution Architect
- 3. Serverless
- 4. Serverless
- 6. • No servers to provision or manage • Scales with usage • Never pay for idle • Availability and fault tolerance • Memory and storage limits • Vendor lock • Computing time limits Serverless means
- 8. • Managing Concurrency • Top memory size of 3GB • Up to 80% faster cold start times What’s new?
- 9. What’s new?
- 10. Synchronous (push) Asynchronous (events) Stream-based (pull) FaaS execution models
- 11. Synchronous: • Application backend • Legacy API proxy • Bots and skills • Hybrid & compute as a Glue Use cases Asynchronous: • Data processing and manipulation (ETL) • Event-driven services • Scheduled events • Hybrid & compute as a Glue Stream-based: • Stream-based
- 12. Data sources: • S3 • DynamoDB • Amazon Kinesis • AmazonCognito Event sources that can trigger AWS Lambda Endpoints: • AWS API Gateway • AWS IoT • AWS Step functions • AmazonAlexa Event/message services: • AWS SNS • Cron events • SQS Deployment and management tools: • Cloud Watch • Cloud Trail • Cloud Formation
- 16. Legacy API proxy
- 17. Backend
- 18. SPA with GraphQL
- 19. Step functions
- 20. AWS X-Ray
- 21. Infrastructure CloudFormation-based Framework-based Other Tools Chailice
- 22. Problems: • Warm up time • State • Pricing • Tooling Real world problems Fixes: • Warming trigger • CloudWatch Event/5 min • External state store • S3, DynamoDB • Use shorter operations (optimization)
- 23. Example from Vitaly Haritonsky’s speech:“Python over Go” Let's calculate the price : • 10 images per second = 26784000 images per month. Average time of processing of source image (1.5 MB 3872 × 2576) is around: 500 ms for 256 MB lambda Example
- 24. Example
- 25. Pricing
- 26. Input size: 26784000 images * 1.5 MB = 40.17600 TB Example
- 28. Why we need multi-regions setup: • High Availability (Active-Active setup) • Regional fallback • Improved overall Latency (latency-based routing) Example (Multi-regions)
- 32. Vendors
- 34. Vendors
- 35. Pros: • Reduced cost • Scalability • Optimization is the root of some cost savings • Easier operational management • Reduced packaging and deployment complexity • Community • “Greener” computing Hype and reality Cons: • Vendor lock • Multi tenancy problems • No in-server state • Testing
- 36. Maximov Mikhail Software engineer in DataArt Certified AWS Solution Architect Telegram: https://t.me/maximov_m Email: [email protected] Thank you! Q&A
- 37. Books