This document discusses serverless computing beyond just AWS Lambda. It defines serverless as focusing on business problems by using managed services wherever possible and connecting them with ephemeral compute functions. A variety of AWS services are identified that can fulfill the different needs of building applications like data stores, APIs, authentication, compute, messaging, orchestration, and analytics in a serverless way. Serverless architectures are described as masonry with functions as mortar and managed services as load-bearing bricks.

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Ben Kehoe
Cloud Robotics Research Scientist at iRobot
AWS Serverless Hero
@ben11kehoe
Serverless beyond AWS Lambda

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Understanding serverless
• Often equated with Lambda
• This misses the bigger picture
• And the smaller picture
@ben11kehoe

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Understanding serverless
• Serverless is about letting you focus on your business
problems
• Use (and abuse) managed services wherever you can
• “Service-full”
• Glue it together with managed, ephemeral compute
• FaaS is one example, but there are others
@ben11kehoe

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Serverless is masonry:
FaaS is the mortar; buy your bricks
@ben11kehoe

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Service-full
• Break your business problem down: what parts aren’t core
to what you’re doing for your customers?
• Use (or abuse) a managed service for those
• What to look for in a managed service:
• Resources billed → resources used
• Smaller, more abstract control plane
@ben11kehoe

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Why is serverless a thing now?
• Managed services have been around forever
• But business logic has to go somewhere…
• Managed rules engines exist
• But you can only get so far without actually coding
something…
• Ephemeral compute has enabled providers to manage
code
@ben11kehoe

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Ephemeral compute
• Compute with a defined, finite lifetime
• Temporal: FaaS, streaming compute
• Input: managed batch compute
@ben11kehoe

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What’s needed to build an application?
1. Data stores (DB, blob, …)
2. API
3. Auth+sec
4. Compute
5. Message bus
6. Orchestration
7. Analytics
@ben11kehoe

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Data stores
• Serverless means you don’t pay for idle
• What does “idle” mean with respect to a data store?
• Storage itself is usage
• “Warmth” of data is usage
@ben11kehoe

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Data stores
• S3
• DynamoDB
• Autoscaling (performance implications)
• Aurora “serverless”
• No HTTP interface → does not play well with Lambda
@ben11kehoe

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API
• AppSync
• CRUD backend? AppSync + DDB and you’re done
• API Gateway
@ben11kehoe

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Auth+sec
• Client identity: Cognito
• Federated identity or User Pools?
• Got a 3rd party federated identity provider (e.g., Auth0)?
Still works with Cognito federated identity!
• Can even allow direct access to AWS services, for thinner
backends
• Policies and scoping becomes really really important
• More service = more IAM
@ben11kehoe

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Compute
• Lambda
• Event-driven
• Request-response
• Periodic
• AWS Glue
• AWS Batch
• Not Fargate
@ben11kehoe

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Message bus
• SNS
• SQS
• Kinesis Data Streams
• Kinesis Firehose
• Kinesis Analytics
• AWS IoT
• Not Amazon MQ
@ben11kehoe

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Analytics
• S3 + Athena
• AWS IoT Analytics
• AWS Glue
• RedShift, kinda?
@ben11kehoe

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Summing up
• Serverless is masonry
• FaaS (and other ephemeral compute) is just mortar
• Managed services are your load-bearing bricks
@ben11kehoe

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Thank you!