AWS Serverless Examples
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The document discusses AWS serverless architecture, detailing its components, pros, and cons, focusing on real-life implementation flows. It covers various architecture patterns using Amazon services like API Gateway, Lambda, DynamoDB, and Kinesis for tasks such as autoscaling and event processing. The document also includes links to external resources and contact information for further inquiries.
AWS Serverless Examples
- 3. AWS Serverless - Previous Slides Recap ● In previous slides we analyzed AWS main serverless components (https://www.slideshare.net/DimosthenisBotsaris/aws-serverless-introduction ● In these slides we will explore serverless architecture flows to solve real life issues. ● We try to define AWS Serverless components to use to achieve serverless flow, in production environment. ● Implementation of some flows can be found on: https://github.com/arconsis/aws-network-microservices-warmup
- 4. Serverless Architectures Pros ● Cost: Pay per invocation, no costs for unused servers ● Scaling: Auto scaling in response to spikes in traffic ● Productivity: Responsible only for your code, AWS handles managing and provisioning of servers Cons ● Vendor lock-in: Seamlessly integration with other services from AWS, hard to move over to other Cloud Providers ● Testing: Difficult to perform integration tests ● Performance: Cold starts may add latency to some users
- 5. 3-tier Serverless Flow (1) ● Amazon API GW in a public subnet, as entry point of backend. ● Amazon API GW handles routing, aggregation, authorization. ● Amazon ECS in private subnets handles orchestration management & auto- scale of our backend. ● Amazon Fargate in private subnets used as our server. ● Amazon DynamoDB in private subnets is used as database.
- 6. 3-tier Serverless Flow (2) ● Amazon API GW in a public subnet, as entry point of backend. ● Amazon API GW handles routing, aggregation, authorization. ● Amazon Lambda in private subnets, used as servers, which auto-scale. ● Amazon DynamoDB in private subnets is used as database.
- 7. 3-tier Serverless Flow (3) ● Amazon API GW in a public subnet, as entry point of backend. ● Amazon API GW handles routing, aggregation, authorization. ● Amazon Lambda in private subnets, used as servers, which auto-scale. ● Amazon S3 is used to store files. ● S3 event notification will be fired towards SQS. ● Amazon DynamoDB in private subnets is used as database.
- 8. AWS Microservices Event Driven Flow (1)
- 9. AWS Microservices Event Driven Flow (2) ● Amazon API GW in a public subnet, as entry point of backend. ● Amazon API GW handles routing, aggregation, authorization. ● Amazon ECS in private subnets handles orchestration management & auto-scale of our backend. ● Amazon Fargate in private subnets used as our servers. ● Amazon SNS + SQS combination is used to create Fan-Out pattern, to serve an event to two or more downstream services. ● The SQS queue stores the event for asynchronous processing ● Amazon DynamoDB in private subnets is used as databases.
- 10. AWS S3 Events - FanOut (1)
- 11. AWS S3 Events - FanOut (2) ● Amazon S3 is used as file storage. ● Client uploads a file, which is stored to AWS S3. ● S3 event notification will be fired towards SNS. ● Amazon SNS + SQS combination is used to create Fan-Out pattern, to serve an event to two or more downstream services. ● Amazon SQS DLQ is used for messages that can't be processed (consumed) successfully. ● The SQS queue stores the event for asynchronous processing. ● Amazon Lambda in private subnets, used as servers, which auto-scale. ● Amazon DynamoDB in private subnets is used as databases.
- 12. AWS S3 Events - Lambda (1)
- 13. AWS S3 Events - Lambda (2) ● Amazon S3 is used as file storage. ● Client uploads a file, which is stored to AWS S3. ● S3 event notification will be fired towards Lambda. ● Amazon SQS is used for communication among Lambdas - decouple them! ● Amazon SQS DLQ is used for messages that can't be processed (consumed) successfully. ● The SQS queue stores the event for asynchronous processing. ● Amazon API GW in a public subnet, as entry point of backend. ● Amazon API GW handles routing, aggregation, authorization. ● Amazon Lambda in private subnets, used as servers, which auto-scale. ● Amazon DynamoDB in private subnets is used as databases.
- 14. AWS Real Time Analytics Stream Platform (1)
- 15. AWS Real Time Analytics Stream Platform (2) ● Amazon API GW in a public subnet, as entry point of backend and acts as Kinesis Proxy (decouple client from Kinesis) ● Amazon Kinesis Data Stream ingests and collects large amount of data records in real time. ● Amazon Kinesis Data Analytics used to transform and analyze streaming data in real time. ● Amazon Lambda in private subnets, used to add our business logic e.g. remove duplicate values. ● Amazon DynamoDB in private subnets is used as databases to store processed data. ● Amazon DynamoDB streams used to fire transactional logs events. ● Amazon SNS used to send sms / emails to clients. ● Amazon Kinesis Data Firehose used as ETL service that streams data into Amazon S3 into correct format. ● Amazon S3 used to store raw data. ● Amazon Athena used interactive query service to query / analyze data from S3
- 16. AWS Kinesis AutoScale ● Amazon CloudWatch Metrics used to capture metrics from Kinesis Data Stream. ● Amazon CloudWatch alarms (scale- up/down), used to decide when to scale. ● When scaling takes place, an event fired to Amazon SNS. ● Amazon Lambda async consumes SNS events and increase or decrease Amazon Kinesis shards and updates alarms with new shards counter.
- 17. Contact Info ● Arconsis: ○ Website: https://www.arconsis.com ○ Github: https://github.com/arconsis ● Dimos Botsaris: ○ Website: https://www.eldimious.com/ ○ Github: https://github.com/eldimious ○ Email: botsaris.d@gmail.com ● Alexandros Koufatzis: ○ Github: https://github.com/akoufa ○ Email: akoufa@gmail.com