A Gentle Introduction to Functions-as-a-Service

Aug 14, 20180 likes85 views

Slides from my talk on functions-as-a-service at Wyncode Academy in Miami in April '18. Provides an overview of the tradeoffs between different FaaS providers

A Gentle Introduction to
Functions-as-a-Service
Valeri Karpov
@code_barbarian
github.com/vkarpov15

About Me
● Backend Lead @ Booster, Node.js OSS
● Core contributor for Mongoose, Mocha
● Blogger, thecodebarbarian.com
● Early employee at LevelUp, MongoDB, Booster
● Invented the MEAN stack

What’s This Talk About?
● The progression of dev-ops for startups
● Why FaaS is the next natural step for dev-ops
● Retaining state in “stateless” functions
● Trade-offs between different FaaS providers

2008: Physical Machine in Dorm Room
● EC2 was limited, other hosting services sucked
● LevelUp’s first release on an Ubuntu tower
○ Physical machines die or get shut down
○ Campus ISP is slow or changes the IP
○ Limited scale: shipping a new PC takes days

2012: Amazon EC2
● My next few startups all ran on 1-5 EC2 VMs
● Cloud VMs solve most physical machine issues
○ Power outages much less likely
○ Reliable internet maintained by Amazon
○ Spinning up a new VM takes minutes

2012: Amazon EC2
● Vanilla EC2 was great for single server apps
● But what about multiple app servers?
○ 2 services on the same VM in isolation
○ Continuous Deployment
○ Scaling horizontally with a click

2015: Containers and Orchestration
● Docker, Mesos, Kubernetes, etc.
● Compelling for CD and isolation
● Still Have Problems with Resource Usage
○ Memory limits per VM
○ Docker hogs disk space

Functions as a Service
● Instead of deploying an app, you deploy a
bunch of stateless functions
● No VMs, no OS updates
● Resource limits (RAM, CPU) per function call
● Functions run in response to triggers

API Gateways
● Cloud functions respond to triggers
● HTTP is a trigger, but what about:
○ API keys / auth
○ Rate limits
● FaaS providers have API Gateways for this

FaaS Providers
● Amazon AWS Lambda
● Microsoft Azure Functions
● Google Cloud Functions
● IBM Cloud Functions
● Oracle Cloud Fn
● LunchBadger, + many more

FaaS Open Source Libraries
● Kubeless
● OpenWhisk
● Fission

FaaS Advantages
● Easier to scale, no need to worry about too
much load on one service
● Cheaper for low-usage services
● Cheap and easy development environments
● Resource issues rare and easy to debug

FaaS Problems
● No strong best practices yet
● Completely different way of writing apps
● Limited language support
● Managing triggers and API Gateways
● Sometimes you want to retain state...

Why Retain State?
● Think about a persistent database connection

Stateless is a Big Performance Problem
● Connecting to a database on every function
call is slow

But You Can Retain Global State
● Put db handle in global scope

Common Trick Across FaaS Providers
● AWS Lambda: bit.ly/mongodb-lambda
● Azure Functions: bit.ly/mongodb-azure
○ Also With C#: bit.ly/csx-azure-state
● IBM Cloud: bit.ly/mongodb-ibm-cloud

Trade-offs Between Popular Providers
● AWS Lambda
● Azure Functions
● Google Cloud Functions

Size Restrictions
● Size limit per function (node_modules)
○ AWS Lambda: 50MB
○ Azure Functions: None (*)
○ Google Cloud: 100MB zipped, 500MB
unzipped

Primary Fee Structure
● AWS Lambda: $0.00001667 / GB-s, $0.20 / 1M
● Azure Functions: $0.000016 / GB-s, $0.20 / 1M
● Google Cloud: $0.0000025 / GB-s, $0.0000100
/ GHz-s

Hidden Fees: API Gateways
● AWS Lambda: $3.50 / 1M + data
● Azure Functions: no extra cost necessary
● Google Cloud Functions: no extra cost
necessary

Overall FaaS Recommendations
● Check out Azure Functions
● AWS Lambda and IBM Cloud are a mess

Further Reading
● My Blog:
○ bit.ly/mongodb-azure
○ bit.ly/mongodb-ibm-cloud

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This document provides an overview of querying and aggregating a dataset containing NBA box scores for over 30,000 games since 1985 using MongoDB. It demonstrates various MongoDB query and aggregation operations including findOne(), find(), count(), distinct(), $elemMatch, $sort, $limit, $unwind and aggregation pipelines to analyze and extract insights from the data such as answering questions about individual player and team statistics and performance.

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A Gentle Introduction to Functions-as-a-Service

1. A Gentle Introduction to Functions-as-a-Service Valeri Karpov @code_barbarian github.com/vkarpov15

2. About Me ● Backend Lead @ Booster, Node.js OSS ● Core contributor for Mongoose, Mocha ● Blogger, thecodebarbarian.com ● Early employee at LevelUp, MongoDB, Booster ● Invented the MEAN stack

3. What’s This Talk About? ● The progression of dev-ops for startups ● Why FaaS is the next natural step for dev-ops ● Retaining state in “stateless” functions ● Trade-offs between different FaaS providers

4. 2008: Physical Machine in Dorm Room ● EC2 was limited, other hosting services sucked ● LevelUp’s first release on an Ubuntu tower ○ Physical machines die or get shut down ○ Campus ISP is slow or changes the IP ○ Limited scale: shipping a new PC takes days

5. 2012: Amazon EC2 ● My next few startups all ran on 1-5 EC2 VMs ● Cloud VMs solve most physical machine issues ○ Power outages much less likely ○ Reliable internet maintained by Amazon ○ Spinning up a new VM takes minutes

6. 2012: Amazon EC2 ● Vanilla EC2 was great for single server apps ● But what about multiple app servers? ○ 2 services on the same VM in isolation ○ Continuous Deployment ○ Scaling horizontally with a click

7. 2015: Containers and Orchestration ● Docker, Mesos, Kubernetes, etc. ● Compelling for CD and isolation ● Still Have Problems with Resource Usage ○ Memory limits per VM ○ Docker hogs disk space

8. Functions as a Service ● Instead of deploying an app, you deploy a bunch of stateless functions ● No VMs, no OS updates ● Resource limits (RAM, CPU) per function call ● Functions run in response to triggers

9. API Gateways ● Cloud functions respond to triggers ● HTTP is a trigger, but what about: ○ API keys / auth ○ Rate limits ● FaaS providers have API Gateways for this

10. FaaS Providers ● Amazon AWS Lambda ● Microsoft Azure Functions ● Google Cloud Functions ● IBM Cloud Functions ● Oracle Cloud Fn ● LunchBadger, + many more

11. FaaS Open Source Libraries ● Kubeless ● OpenWhisk ● Fission

12. FaaS Advantages ● Easier to scale, no need to worry about too much load on one service ● Cheaper for low-usage services ● Cheap and easy development environments ● Resource issues rare and easy to debug

13. FaaS Problems ● No strong best practices yet ● Completely different way of writing apps ● Limited language support ● Managing triggers and API Gateways ● Sometimes you want to retain state...

14. Why Retain State? ● Think about a persistent database connection

15. Stateless is a Big Performance Problem ● Connecting to a database on every function call is slow

16. But You Can Retain Global State ● Put db handle in global scope

17. Common Trick Across FaaS Providers ● AWS Lambda: bit.ly/mongodb-lambda ● Azure Functions: bit.ly/mongodb-azure ○ Also With C#: bit.ly/csx-azure-state ● IBM Cloud: bit.ly/mongodb-ibm-cloud

18. Trade-offs Between Popular Providers ● AWS Lambda ● Azure Functions ● Google Cloud Functions

19. Size Restrictions ● Size limit per function (node_modules) ○ AWS Lambda: 50MB ○ Azure Functions: None (*) ○ Google Cloud: 100MB zipped, 500MB unzipped

20. Primary Fee Structure ● AWS Lambda: $0.00001667 / GB-s, $0.20 / 1M ● Azure Functions: $0.000016 / GB-s, $0.20 / 1M ● Google Cloud: $0.0000025 / GB-s, $0.0000100 / GHz-s

21. Hidden Fees: API Gateways ● AWS Lambda: $3.50 / 1M + data ● Azure Functions: no extra cost necessary ● Google Cloud Functions: no extra cost necessary

22. Overall FaaS Recommendations ● Check out Azure Functions ● AWS Lambda and IBM Cloud are a mess

23. Further Reading ● My Blog: ○ bit.ly/mongodb-azure ○ bit.ly/mongodb-ibm-cloud

24. Thanks for Listening!

A Gentle Introduction to Functions-as-a-Service

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