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Serverless - When to FaaS?
This document discusses serverless computing and function as a service (FaaS). It provides an overview of what serverless and FaaS are, how they work, common use cases, limitations, and the future impact. Key points include that FaaS provides fully managed compute with no servers to provision and pays only for actual usage, common triggers are HTTP requests and events, and use cases span web backends, mobile apps, file processing, bots, and more. The document also outlines limitations like statelessness and cold starts, as well as emerging practices around business models, architectures, operations, and tooling.
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Introductory remarks on the rise of serverless computing, mentioning FaaS and presenting Benny Bauer.
A timeline showcasing the evolution of cloud computing from data centers to serverless architecture.
Definition of serverless computing, focusing on FaaS benefits like managed services, scaling, and cost-efficiency.
List of various event triggers for serverless functions illustrating its asynchronous capabilities.
Comparison between monolithic, microservices, and serverless architectures highlighting pros and cons.
Introduction to applying serverless architecture through various use cases.
Use of serverless for web backend systems, enhancing efficiency and performance.
Application of serverless architecture for mobile backend technology.
Serverless use cases focusing on file processing tasks in applications.
Serverless architecture examples for bot implementations.
Using serverless for distributed computing with example code.”
Application of serverless in stream processing for tasks like log analytics.
How serverless enables efficient scheduled tasks such as health checks and monitoring.
Using serverless for operations, including policy enforcement and instance management.
Implementing serverless in Continuous Integration processes using LambCI as an example.
Application of serverless architecture in IoT solutions, including garden monitoring.
Leveraging serverless for Content Delivery Networks, focusing on UX improvements and backend load reduction.
Examples of using serverless for device-specific applications.
Discussion on limitations of serverless architecture, including statelessness, latency issues, cost factors, and vendor lock-in.
Exploration of new practices, business models and changes in DevOps related to serverless technologies.
Summary of serverless computing, future predictions, takeaways on efficiency, limitations, and adaptation.
Closing the presentation with an invitation for questions.
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Serverless - When to FaaS?
- 1. The Rise ofServerless - When to FaaS? Photo by Shane Perry Icon by Serverless
- 2. ◉ Cloud Architecture& Development Consulting ◉ Serverless Enthusiast ◉ Ex- Find me at @benikbauer I am Benny Bauer Shalom!
- 3. EvolutionGenesis Custom BuiltProduct (+ rental) Commodity (+ utility) Cloud evolution in 60 sec Data center Hosting Virtualization IaaS Icons made by freepik from www.flaticon.com & unlimicon from Noun Project On Premise Compute Platform PaaS Serverless
- 4. What is Serverless FaaSBaaS B2D SaaS
- 5. What is FaaS- Function as a Service Fully-managed compute Provisioning, patching, scaling, monitoring, logging are provided out-of-the- box Deploy your code Just package and upload the code Pay for actual usage Getting charged only upon code execution, per 100ms 100% UTILIZATION LESS OPS
- 6. How it works Deployyour code Define triggers Code execution (ephemeral instance) EVENT-DRIVEN AUTO SCALING + AVAILABILITY
- 7. Event-driven on steroids ◉HTTP requests ◉ Storage (e.g. file upload) ◉ DB (e.g. row insert) ◉ Events stream ◉ Queue/Messaging ◉ Scheduled job ◉ Monitoring ◉ Infrastructure events ◉ Code build events ◉ Many more...
- 8. Distributed architecture onsteroids Monolith Microservices Serverless Source: http://ryanjbaxter.com/2015/07/15/using-microservices-to-build-cloud-native-applications-part-1/
- 9. Bad ◉ Monitoring ◉ Debugging ◉Deployment ◉ Security Distributed architecture on steroids Good ◉ Scaling ◉ Fault tolerance ◉ Ownership ◉ Cost (better utilization)
- 10. Let’s combine thesebuilding blocks to something useful Use Cases
- 12. Use case: Webbackend
- 13. Use case: Webbackend Source: https://www.linkedin.com/pulse/serverless-architecture-cloud-guru-ryan-kroonenburg
- 15. Use case: Mobilebackend
- 16. Use case: Mobilebackend Async request
- 18. Use case: Fileprocessing
- 19. Use case: Fileprocessing
- 21.
- 22.
- 24. Use case: Distributedcompute import pywren def my_function(x): return x + 7 wrenexec = pywren.default_executor() futures = wrenexec.map(my_function, range(10)) pywren.get_all_results(futures) pywren
- 26. Use case: Streamprocessing ◉ Log processing ◉ Analytics ◉ etc.
- 28. Use case: Scheduledtasks ◉ Health checks ◉ Monitoring ◉ Periodical digest ◉ etc.
- 30. Use case: Operations Policyenforcement on AWS resources. Examples: ● Unmanaged instances handling ● Low utilized instances resizing Triggered by: ● CloudWatch events ● Scheduled
- 32. Use case: CI Source:https://github.com/lambci/lambci
- 33. Use case: CI Source:https://github.com/lambci/lambci LambCI (Travis alternative)
- 35. Use case: IoTbackend Source: https://www.hackster.io/jose-troche/alexa-drone-pilot-7f2deb
- 36. Use case: IoTbackend Source: https://medium.com/serverless-stories/building-a-serverless-garden-monitoring-system-with-lambda-c72c54113df2 Garden Monitoring System
- 38. Use case: CDN Source:https://www.slideshare.net/AmazonWebServices/new-launch-bringing-aws-lambda-to-the-edge ◉ Purpose: ○ Better UX ○ Reduce load from backend ◉ Use cases: ○ Request validation ○ A/B testing ○ Content customizations according to user-agent
- 39. Use case: CDN Source:https://www.slideshare.net/AmazonWebServices/new-launch-bringing-aws-lambda-to-the-edge
- 41.
- 42. Use case: @Device- example Source: https://www.slideshare.net/AmazonWebServices/aws-welcome-to-reinvent-recap-20161214
- 44.
- 45. But isn’t itlimitationless?? Mind The Limitations
- 46. Limitations: Stateless ◉ Instancesare ephemeral (memory, storage) but not necessarily disposable ◉ No sticky sessions ◉ Workarounds: ○ Websockets through IoT (MQTT) ○ Manage state yourself: ■ Pass on request ■ Store in cache/db
- 47.
- 48. ◉ Ephemeral =>cold start on first or infrequent calls ◉ Inconsistent Limitations: Latency Source: http://www.yusp.com/blog/cold-start-problem-recommender-systems/
- 49. Limitations: Latency Source: https://blog.newrelic.com/2017/01/11/aws-lambda-cold-start-optimization/ Frequency: 1minute 10 minutes 30 minutes 60 minutes
- 50.
- 51. Limitations: Costs AWS LambdaEC2 Duration Per 100 ms Per 1 hour Reduced cost for RI Cost of ownership Low High Additional costs Requests Redundancy Storage Cost effective For low or changing load For high utilization
- 52.
- 53. Limitations: Vendor lock-in ◉The real lock-in is the integrated services ◉ A tradeoff: control vs. convenience Source: https://www.slideshare.net/AmazonWebServices/reinvent-recap-session-1-whats-new-with-aws-lambda
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- 56. Know the challenges ◉Development ○ Local development ○ Integration tests ○ Debugging ◉ Granularity ○ Deployment ○ Monitoring ○ Logging ○ Security ○ Service discovery
- 57.
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- 59. The FaaS effect Newemerging practices Photo by TimOve (https://flic.kr/p/4aTMMx)
- 60. Business model ◉ WorthBased Development (“FinDev”) https://hackernoon.com/why-the-fuss-about-serverless-4370b1596da0#.yct5knd7h by Simon Wardley
- 61. Business model ◉ APIMarketplace
- 62. Architecture ◉ More distributedand pluggable ◉ More event-driven ◉ Frameworks are changing
- 63. Operations DevOps is changing ◉Less about provisioning, capacity planning ◉ More about distributed systems: ○ Monitoring & visibility ○ Debuggability ○ Graceful degradation & Resiliency ○ CI/CD ○ Costs optimisations
- 64. Summary What was itall about?
- 65. Predicting the future ◉Lower costs ◉ Less limitations ◉ More use cases ◉ More tooling
- 66. Takeaways ◉ Deliver fasterwith lower costs for many use cases ◉ Consider limitations ◉ Get ready for new emerging practices
- 67. Any questions? Thanks! Slides templateby SlidesCarnival You can find me at ◉ @benikbauer ◉ bennybauer@gmail.com This work is licensed under a CC Attribution 4.0 International License.