The burden of a successful feature: Scaling our real time logging platform
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It’s impossible to understand the health of your system without real-time logging. Our logging platform is one of our favorite and most popular features, and currently handles millions of requests and gigabytes per second of traffic. It’s stateless, real-time, and can provide insight and ship data to a multitude of destinations. Fastly has consistently iterated to keep up with the growth of the platform, and we’ve learned many lessons along the way. In this talk, you’ll get a peek into the system, and how we’ve developed it.
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The burden of a successful feature: Scaling our real time logging platform
- 1. Ines Sombra Director of Engineering The burden of a successful feature: Scaling our real time logging platform presents
- 2. Today’s Agenda A delightful demo & context A deep dive into logging Challenges & future
- 3. But first… A bit of context
- 5. https://vimeo.com/267641392 Fresh from Altitude NYC —Peter Bourgon, Altitude NYC Observability is an umbrella term. There are different techniques to achieve observability in a system.
- 6. Peter’s classification of Observability TECHNIQUES SYSTEMS * Lovingly stolen from Peter Bourgon
- 7. SYSTEMS * Lovingly stolen from Peter Bourgon TODAY 👉 Peter’s classification of Observability TECHNIQUES
- 12. But Why? This pipeline is one of the oldest systems at Fastly Born out of our dissatisfaction w the status quo We wanted something that would send you logs extremely fast (stream them near realtime) to anywhere you want (many endpoints)
- 13. Log Streaming at Fastly
- 14. Logging @ Fastly Caches Aggregators Endpoints s3 syslog gcs sumologic bigquery ftp papertrail …
- 15. s3 syslog gcs sumologic bigquery ftp papertrail … Logging @ Fastly Caches Aggregators Endpoints
- 16. s3 syslog gcs sumologic bigquery ftp papertrail … Logging @ Fastly Caches Aggregators Endpoints
- 17. s3 syslog gcs sumologic bigquery ftp papertrail … Logging @ Fastly Caches Aggregators Endpoints
- 18. s3 syslog gcs sumologic bigquery ftp papertrail … Logging @ Fastly Caches Aggregators Endpoints
- 19. s3 syslog gcs sumologic bigquery ftp papertrail … Logging @ Fastly Caches Aggregators Endpoints
- 20. s3 syslog gcs sumologic bigquery ftp papertrail … Logging @ Fastly Caches Aggregators Endpoints
- 21. s3 syslog gcs sumologic bigquery ftp papertrail … Logging @ Fastly Caches Aggregators Endpoints
- 22. Logging pipeline is Stateless We don’t batch your logs We don’t store your logs We stream your logs in near real-time to your defined endpoints We really don’t want your logs on disk
- 23. Logging @ Fastly Caches + Senders Aggregators Varnish Varnish Varnish Varnish
- 24. Varnish Varnish Varnish Varnish Logging @ Fastly Caches + Senders Aggregators
- 25. Varnish Varnish Varnish Varnish Logging @ Fastly Caches + Senders Aggregators
- 26. Varnish Varnish Varnish Logging @ Fastly Caches + Senders Aggregators Varnish
- 27. Logging pipeline is Best Effort We try our best to send logs to your defined endpoint Your endpoint must be up & healthy in order for us to be able to send data to it We have minimal buffering Pipeline optimized for log streaming speed
- 28. Logging Endpoints We don’t limit the number of endpoints or log lines per request ~8.6K active endpoints Ecosystem of endpoints in different stages of evolution Aggregators Endpoints s3 syslog gcs sumologic bigquery ftp papertrail …
- 29. Logging Streams data File-based endpoints (time ranged) Streaming endpoints (protocol or http-requests) s3 gcs ftp sftp syslog sumologic bigquery logentries papertrail splunk scalyr honeycomb
- 30. Logging Growth (2014-2015) 😳 ~430K LPS ~1.2K endpoints ~ 2GBps
- 31. Logging Growth (2014-2015) 😳 ~430K LPS ~1.2K endpoints ~ 2GBps
- 32. Logging Growth (2017-2018) ~3M LPS ~8.6K endpoints ~4GBps
- 33. Logging Growth (2017-2018) ~3M LPS ~8.6K endpoints ~4GBps
- 34. Logging Growth (8X!!) ~3M LPS ~8.6K endpoints ~4GBps
- 36. We send a lot of data continuously to our supported endpoints Syslog continues to be our most popular endpoint but S3 & GCS have the highest volume The 70's are still alive with a very respectable 13 MBps to ftp and 74 kBps to sftp* * for the non-millennials Logging Endpoints
- 37. Challenges & Lessons learned
- 38. s3 syslog gcs sumologic bigquery ftp papertrail … Logging @ Fastly Caches Aggregators Endpoints
- 39. Volume Challenges No hard limits to what you can log, this can be challenging System is multi-tenant. Noisy neighbors can affect delivery Consider sampling for high volume logging
- 40. Burden of many endpoints Classic integrations challenges (each endpoint is a downstream dependency) Standard endpoint clients often don’t meet our needs Having our own clients affords us extra optimizations
- 41. Endpoints & Health Some endpoints have known limitations (infamous examples: S3, BigQuery, GCS) Difficult to infer if an endpoint is working or not (Hard to test setup too) Structured logging (JSON via VCL) is challenging
- 42. Service Isolation Prioritize delivery of content over log retention An aggregator discards the oldest logs it has when it can’t deliver them fast enough In a cache node we are our own customers so senders do the same when they can’t reach aggregators fast enough
- 43. Expectation Mismatch Burden of a system that works so well is that it makes you believe you have strong guarantees Design constraints determine the SLA of the pipeline General advice: Understand the design choices of the systems you use because they limit what is possible to guarantee *
- 45. The team have been Busy bees H2 H1 Platform performance & addressing the challenges of individual endpoints We are getting fancy!
- 46. Platform Performance Reducing lock contention & CPU usage Smarter memory allocation & management Overhauling all endpoints Halving the time it takes for a log line to be processed (from sender read to aggregator line preparation)
- 47. Getting fancy BigQuery improvements New endpoints: Kafka More integrations with cloud services Make endpoints easier to debug
- 49. Want More?
- 50. Want more endpoints? Want metrics? Want easier structured logging? Want VCL counters + secondly aggregation + a higher SLA? Want More?
- 51. Want more endpoints? Want metrics? Want easier structured logging? Want VCL counters + secondly aggregation + a higher SLA? Dom Fee Want More?
- 52. Want more endpoints? Want metrics? Want easier structured logging? Want VCL counters + secondly aggregation + a higher SLA? Dom Fee Want More?
- 53. tl;dr LOGGING Fastly lets you extend the visibility of your system to the edge & gain meaningful insights in near real-time Is a pipeline with very specific constraints & guarantees Exciting things are coming!