Serverless Apps on Google Cloud: more dev, less ops
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From mabl Software Engineer Joseph Lust. Serverless on GCP is a perfect match to do more dev and less ops. We discuss the many GCP serverless services used @ mabl and how they reduce both time to market and operating expenses. We focus on the nuances of Google Cloud Functions and many way to optimize your serverless apps.
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Serverless Apps on Google Cloud: more dev, less ops
- 1. Serverless Apps on GCP more dev, less ops Joseph Lust mabl engineer @lustcoder
- 2. About Me: Joseph Lust Engineer ■ Building the web for two decades ■ Cloud native since 2011 ■ Currently building mabl ML cloud on GCP ■ Co-organizer GDG Cloud Boston Meetup me@joelust.com
- 3. overview ■ Our serverless future ■ Serverless solutions GCP ■ Serverless demos ■ Taming serverless @ mabl 3
- 4. startups must push or perish 4
- 5. serverless just works ■ No Provisioning ■ Transparent Scaling ■ Event Driven ■ Pay only for Use 5
- 6. it’s all about opportunity cost ■ Provisioning takes time ■ Boilerplate takes time ■ You’re not running a hosting company 6
- 7. how developers deploy code 2014 2007 2013 VPS Machine Image Docker Containers war File AWS Lambda 7 2000 Container Era Serverless Era Firebase CF Serverless functions GCF 2016 2017 AF
- 8. exports.myService = (req, res) => res.send(‘hello world’); mvf es6+
- 9. other serverlessish GCP services ■ Serverless ▲ Scaling Clusters - Kubernetes Engine ▲ Kafka - Pub/Sub ▲ Mongo/EventSource - Firebase ▲ File Server - Cloud Storage ■ Not purely serverless, but close ▲ Tomcat/Jetty - App Engine ▲ Spark Streaming - Dataflow 9 Cloud Pub/Sub Cloud Dataflow Kubernetes Engine ML Engine
- 10. event driven all the way ■ Only run code on events ▲ Cloud Storage blob changes ▲ Pubsub message arrival ▲ HTTP endpoint requests ▲ DB/Auth/Conversion changes ■ No machines consuming 2% CPU all day ■ Very low latency operations ■ No more corn jobs! 10
- 11. exports.imageToJPG = functions.storage.object().onFinalize( async (object) => processImage() ); example: image processor es6+
- 12. but what do functions cost? 12
- 13. gcf is the cheapest function provider Vendor FREE req/mo req/$ Google Cloud Functions 2M 5M Firebase Cloud Functions 2M 2.5M AWS Lambda 1M 5M Azure Functions 1M 5M 13 See full details in Google Spreadsheet calculator * Also see execution time, bandwidth, and memory costs
- 14. gcf cheapest counting free monthly allowances 14 * Also see execution time, bandwidth, and memory costs
- 15. gcf differentiators ■ Guaranteed CPU per memory allotment ■ Easy to use UI and tools ■ Stackdriver Logging & Error Reporting Source: GCP Pricing, FB Pricing, AWS Lambda Pricing, Azure Pricing 15
- 17. but, what about Microservices? 17
- 18. but, what about Micro Nanoservices? 18
- 19. microservices solve many pains ■ Minimize code size ▲ Can scale servers, not developers’ minds ■ Minimize deploy speed/code ■ Minimize blast radius ■ Decoupling, Coherence, Singleness of Purpose 19
- 20. how do you decouple services and handle discovery ■ We Don’t Do Discovery ■ Event Driven Queues ▲ HTTP endpoints for external services ▲ Blob change events for files ▲ Message queue events for everything else ■ No Daemons ▲ Don’t waste time spinning 20
- 21. decoupled async functions pattern 21
- 22. how do you handle changing microservice/models? ■ Versioned Payloads over the wire ▲ New service can handle older versions ■ Add Consumers, then Suppliers ■ Upgrade, don’t replace ■ Lazy read repair ▲ Pessimistic data upgrade and transform ▲ Upgrade path from old version 22
- 23. how do make slow deploys fast? ■ Multi-repo git layout ■ File change exclusion masks ■ Deploy functions in parallel ■ Harness CI & CD (e.g. Cloud Build) 23
- 24. how do you handle GCP outages? ■ Durable Pubsub subscriptions ■ No microservices on fast path ▲ Backend processing ▲ Keep the UI and lights on via Firebase 24
- 25. request costs round up ■ Requests billed per 100ms ■ Increments round up ■ Faster functions are not always cheaper ▲ 17ms → 100ms ▲ 101ms → 200ms 25 Run Time: 17ms Billed Time: 100ms Wasted Time
- 26. minimizing your request costs ■ Batch multiple fast work units to fill the time (e.g. 100ms chunks) 26 Work Unit: 17ms Billed Time: 100ms Work Unit: 17ms Work Unit: 17ms Work Unit: 17ms Work Unit: 17ms Wasted Time
- 27. minimizing your request costs 27 ■ Use a middle man to shield file events from high memory loads ▲ Filter/light weight checks in middle man ▲ Send heavy lifting to larger function ■ Different inputs to same service have different resource needs ▲ e.g. 90% requests need 128MB ram, 10% need 512GB ▲ e.g. 80% requests complete in 30s, 20s take 2min
- 28. 28
- 29. maximizing performance ■ Tune your CPU & Memory to the job ▲ Profile your microservices - CPU or memory bound? ■ More memory runs faster ▲ Greater CPU dedicated to larger memory allocation functions ▲ 128MB → 200 MHz ▲ 2048MB → 2.4GHz ▲ CPU/Memory costs increase linearly ■ Cache expensive objects between requests ▲ PubSub connections ▲ Firebase Admin instances ▲ Login tokens 29
- 30. but seriously, what’s this cost you? 30
- 31. track everything, from bits to cents ■ Metrics for every execution ▲ Every Byte of memory use ▲ Every Processor Cycle of runtime ▲ Every Byte of egress ▲ Every Invocation ■ Direct Billing to BigQuery export ▲ Easy to explore and query ▲ Easy to visualize with Data Studio 31
- 32. Real Production Numbers @ mabl 32
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- 35. ■ scaling to zero no longer important ■ you have a constant load ▲ Dedicated instance when to move from Serverless to Servers 35 $ Load (rps) Cloud Function Dedicated n1-standard-1
- 36. ■ scaling to zero no longer important ■ you have dynamic load ▲ Kubernetes Deployment ▲ Knative function ▲ App Engine Service when to move from Serverless to Servers 36 $ Load (rps) Cloud FunctionKubernetes Deployment
- 37. billing tips ■ Label functions on deploy ▲ Labels propagated to billing ▲ Can track Memory, CPU, Invocation, Ingress, Egress costs per function ■ Don’t forget the egress bandwidth ▲ Keep your data stores in the same region (Iowa) ▲ GCF only deployable to Iowa 37 gcloud beta functions deploy <your_fn> --labels=”app_name=<your_fn>” ...
- 39. embrace serverless for ■ For low latency, event driven demands ■ For decoupled, cohesive, independent services ■ For painless deployment and auto-scaling ■ For reduced opex and oppex 39
- 40. (TL;DR) embrace serverless to 40
- 41. gcp serverless resources ■ FB CF Examples Repo: github.com/firebase/functions-samples ■ GCF Examples: github.com/GoogleCloudPlatform/nodejs-docs-samples ■ Jason Polites (great) Examples: github.com/jasonpolites/gcf-recipes ■ I/O 2018 CF Presentations ▲ Get Started Building Serverless Applications: youtu.be/JenJQ6gc14U ▲ Serverless on Google Cloud: youtu.be/iPQUdb0kssE ▲ Serverless Compute on Google Cloud: youtu.be/Y1sRy0Q2qig ▲ CI/CD in a Serverless World: youtu.be/iyGHW4UQ_Ts ▲ Building and Deploying Microservices: youtu.be/oALEthV9z_U 41 @lustcoder
- 42. Questions?