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Multi-arch from the ground up
- 1. Cheryl Hung, @oicheryl Sr Director, Infra Ecosystem, Arm Multi-Arch Infrastructure from the Ground up KubeCon CloudNativeCon EU 2023 Amsterdam, 19 Apr 2023
- 2. About me @oicheryl 2010 ● C++ engineer 2016 ● Infra ● Dev Adv 2017 ● Cloud Native London 2018 ● CNCF
- 3. Cheryl, Sr Director Infra Ecosystem, Arm @oicheryl
- 4. Arm Infra Ecosystem: Cloud, 5G, Telco, Networking @oicheryl 1. Developer Outreach 2. SW/HW support 3. Standards
- 5. Objectives 1. Why is Multi-Architecture infrastructure tricky? 2. How do I do Multi-Arch with Kubernetes? 3. Case studies: FusionAuth, Honeycomb, Arm @oicheryl
- 6. Why is Multi-Architecture infrastructure tricky?
- 7. @oicheryl Does your infrastructure support Multi-Arch? 1. Completely 2. Partially 3. Experimenting 4. No, but interested 5. No, not yet
- 9. Better price-performance Global Cloud IT spending
- 10. Fruit computers ARM v1 ARM v7 ARM v6 ARM v8.6 ARM v8.4A Arm’s RISC architecture targets power efficiency and performance and can be licensed for different use cases
- 11. @oicheryl Goals of Multi-Arch infrastructure Workloads should run on the best hardware for their price/performance needs Without developers being concerned with the underlying architecture
- 12. But Multi-Arch touches everything… ● Infra As Code ● CI/CD, reproducible builds ● Packaging, binaries, images, registries ● Testing, scheduling, rollout, performance testing ● Kubernetes upgrades ● …
- 13. How do I do Multi-Arch with Kubernetes?
- 14. @oicheryl Assumption 1: cloud native infra
- 16. @oicheryl
- 17. 1. Inform Inventory your software stack ● OS ● Container images ● Libraries, frameworks and runtimes ● Tools used to build, deploy and test ● Tools used to monitor and manage and check each for Arm support (AArch64 in GCC, arm64 in Linux kernel) Identify hotspots @oicheryl
- 18. 2. Optimize Provision test Arm64 environment Upgrade container images and test Performance testing Update CI/CD for reproducible Arm64 builds @oicheryl
- 19. 3. Operate Build K8s cluster ● Mixed control plane and worker nodes ● Cluster creation ● Daemonsets Canary or blue-green deployment ● Node affinity, taints, tolerations ● Different limits and requests per architecture @oicheryl
- 20. Case studies
- 21. “48 of the top 50 Amazon EC2 customers use AWS Graviton processors for their workloads” Danilo Poccia, Chief Evangelist (EMEA) AWS, Aug 2022 @oicheryl
- 22. Summer 2020 Community member investigates running on Raspberry Pi Load tests on Graviton Official support; rolled out to SaaS in June Summer 2021 March 2022 >70% of SaaS instances run on Arm March 2023 A developer-focused API-first auth provider deployable anywhere @oicheryl
- 23. technical timeline 1. Finding the JVM that supported ARM, especially Mac ARM chips (Java 17 was the first one to do so). Added Java 17/ARM support to the code base Dec 2021 - Feb 2022 2. Updating and testing install scripts to use the correct JVM 3. Updating docker to target the ARM architecture with jlink and multi-arch builds 4. Checking for ARM support in public cloud regions when spinning up SaaS 5. Update the application to expose the underlying architecture Logins are especially CPU intensive due to password hashing, so the team load tested 50k logins. Arm handled 26-49% more logins per second and cost 8-10% less than Intel on EC2 @oicheryl
- 24. “Because we run on Java, our lift was pretty small. We just had to find a JVM built for ARM, and then work out any remaining kinks” - Daniel DeGroff, FusionAuth CTO “I just switched a FusionAuth instance to arm64 and the transition was so smooth I couldn't even tell whether it's actually running the arm64 version” - Hendy Irawan, BandungPermaculture.com CIO and FusionAuth user @oicheryl
- 25. Full stack observability enabling engineers to deeply understand and debug production software @oicheryl March 2020 First experiments with Graviton2 Ingest workers in production Virtually all workloads and envs on Arm 92% of vCPUs on Arm May 2021 Nov 2021 Turned off last x86 EC2 instances 99% Arm on Lambda April 2022
- 26. 1. Chose to migrate ingest workers first as they are stateless, performance critical and scales out horizontally. Written in Golang, so compiling for Arm was easy. 2. Deployed in dogfood environment and observed positive results. 3. Initially not Kubernetes or container orchestration, everything in Terraform and Chef so could switch Arm Amazon Machine Images (AMIs) by enumerating all the dependencies to update. 4. Next up were own workloads (easiest to re-compile and highest compute spend), Kafka. The last were ad-hoc one-off services and those difficult to migrate. honeycomb.io/blog/present-future-arm-aws-graviton-honeycomb
- 27. “Graviton has enabled Honeycomb to scale up our product without increased operational toil, spend less on compute, and have a smaller environmental footprint.” - Ian Smith, Engineering Manager, Honeycomb.io “I personally approached it as an idle experiment with a few spare afternoons, and was surprised by how compelling the results were. Saving 40% on the EC2 instance bill for this service […] is well worth the investment” - Liz Fong Jones, Field CTO, Honeycomb.io @oicheryl
- 29. Dogfooding on Arm @oicheryl 2019 Arm moved EDA tools from on-prem x86 to Graviton ✅ 60% better performance ✅ 50% reduced cost ✅ >1MW power saved/day
- 31. Thanks! Slides at oicheryl.com Takeaways ● Why multi-arch? @oicheryl Sched feedback
- 32. Thanks! Slides at oicheryl.com Takeaways ● Why multi-arch? ● How? @oicheryl Sched feedback
- 33. Thanks! Slides at oicheryl.com Takeaways ● Why multi-arch? ● How? ● Talk to me! ○ Technical assistance from Arm ○ Credits for CI/CD ○ Success stories @oicheryl Sched feedback
- 34. Thanks! Slides at oicheryl.com Takeaways ● Why multi-arch? ● How? ● Talk to me! ○ Technical support from Arm ○ Credits for CI/CD ○ Success stories @oicheryl Sched feedback