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ScyllaDB Cloud Goes Serverless

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ScyllaDB Cloud Goes Serverless

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Learn how ScyllaDB Cloud is moving to serverless, transforming its single tenant deployment model into a multi-tenant architecture based on Kubernetes. Discover the engineering innovation required, and the user value of the new architecture, including use of encryption (both at flight and at rest), performance isolation, and the capability to scale elastically.

Learn how ScyllaDB Cloud is moving to serverless, transforming its single tenant deployment model into a multi-tenant architecture based on Kubernetes. Discover the engineering innovation required, and the user value of the new architecture, including use of encryption (both at flight and at rest), performance isolation, and the capability to scale elastically.

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ScyllaDB Cloud Goes Serverless

  1. 1. ScyllaDB Cloud Goes Serverless Yaniv Kaul, VP R&D, ScyllaDB
  2. 2. Yaniv Kaul ■ Joined ScyllaDB in October 2022 ■ Previously, at Red Hat, managed ■ Storage (Ceph, cloud storage), ■ Virtualization (OpenStack) ■ Performance and Scale. ■ Years ago, worked with ScyllaDB founders on the KVM hypervisor
  3. 3. ■ Introduction ■ Tour ■ Architecture Presentation Agenda
  4. 4. Introduction
  5. 5. ScyllaDB Cloud ■ Our managed ScyllaDB clusters offering ■ Provides clusters running on AWS or GCP clouds ■ Uses whole virtual machine(s) per tenant ■ Use our infrastructure or ‘bring-your-own-account’ nodes ■ Lifecycle, monitoring, logging, alerting - overall management by our DevOps and Support teams ■ Free trial also available! cloud.scylladb.com
  6. 6. ScyllaDB Cloud - K8S based The next generation ScyllaDB Cloud is moving to run ScyllaDB workloads on Kubernetes (K8S). ■ Infrastructure components (storage, network, security, monitoring, logging and more) deployment, management are handled by Kubernetes ■ Provides seamless integration with cloud services ■ Based on the open source ScyllaDB K8S operator
  7. 7. ScyllaDB Cloud - K8S based Cluster Creation Phase
  8. 8. ScyllaDB Cloud - K8S based Cluster Is Up
  9. 9. ScyllaDB Cloud - K8S based General Tab
  10. 10. ScyllaDB Cloud - K8S based Connection Bundle
  11. 11. ScyllaDB Cloud - K8S based cqlsh Connection
  12. 12. docker run -it --entrypoint cqlsh -v /file/downloaded/from/cloud/connect-bundle-ScyllaSummit2023.yaml :/connect-bundle-ScyllaSummit2023.yaml:Z scylladb/scylla-nightly:5.2.0-dev-0.20221215.16c50bed5eb8 --cloudconf connect-bundle-ScyllaSummit2023.yaml
  13. 13. Python Example
  14. 14. ScyllaDB Cloud - K8S based Monitoring
  15. 15. Architecture
  16. 16. Challenges With K8S ScyllaDB on K8S has some of the ‘usual’ challenges and some ‘unusual’ ones: ■ Stateful application (a database) ■ Strict requirements from the operating system ■ Deployment requirements
  17. 17. The control plane is mostly running on a separate system ■ ScyllaDB Cloud management system was extended to treat serverless as yet another cloud provider ■ Monitoring and logging are kept outside the operational K8S cluster running the workloads Management
  18. 18. First, need to provision a K8S node (worker), that will be used to run tenants’ ScyllaDB nodes: ■ RAID(0) configuration, OS tuning, etc. ■ Disk IO benchmarking, to get the baseline performance numbers. ■ Avoid ‘lemons’ ■ Distribute baseline IO performance between tenants (per tenant CPU shares) Data Plane / Workers
  19. 19. The ScyllaDB K8S operator deploys a complete ScyllaDB cluster: ■ No. of nodes, size (CPU, memory, disk) , distribution, replication factor (RF=3 for the time being), and other configuration items. ■ Configure / initialize node, wait for cluster formation ■ Manager (agent) & configuration ■ Monitoring ■ Drivers proxy (‘SNI proxy’) Tenant Deployment
  20. 20. ■ Virtual machines forces a fixed cores/memory/disk relationship ■ Scaling can only be performed by adding or removing nodes ■ With K8S, we abstract underlying hardware and provide much more flexibility. Breaking the Fixed Compute Storage Relationship
  21. 21. ■ Memory - each tenant (Pod) get their own (request/limit) ■ CPU - each tenant (Pod) get their own (request/limit) ■ Disk - each tenant get their own XFS mount point, with quota assigned ■ Scylla’s IO scheduler knows how much IOPS to give to each tenant ■ KMS is used to encrypt each tenant’s data Tenant Isolation
  22. 22. /mnt/md0 Tenant Isolation - Storage (quota) Instance disks Host path XFS Quota /mnt/md0/local-pv-1 50G /mnt/md0/local-pv-2 100G kind: ScyllaCluster spec: datacenter: racks: - storage: capacity: 50G kind: ScyllaCluster spec: datacenter: racks: - storage: capacity: 100G Dynamic storage provisioner RAID 0 XFS
  23. 23. Tenant Isolation - Storage (performance) i3en.*xlarge disks: - mountpoint: /var/lib/scylla read_iops: 125000 read_bandwidth: 1000000000 write_iops: 80000 write_bandwidth: 500000000 disks: - mountpoint: /var/lib/scylla read_iops: 125000 read_bandwidth: 1000000000 write_iops: 80000 write_bandwidth: 500000000 disks: - mountpoint: /var/lib/scylla read_iops: 250000 read_bandwidth: 2000000000 write_iops: 160000 write_bandwidth: 1000000000
  24. 24. Performance Example of workload testing: ■ 4 loaders ■ 7 tenants ■ 4 OLTP, 3 OLAP workloads ■ Mixed stress workload Workload OLTP OLTP OLTP OLTP OLAP OLAP OLAP CPU cores per scylla node 2 / 16 2 / 16 2 / 16 2 / 16 2 / 16 2 / 16 2 / 16 Cassandra-stress stats Latency [ms] THROUGHPUT - OP/S loader 1 - latency p99 read 2.2 2.2 2.4 2.2 5,729 6,263 6,033 loader 2 - latency p99 read 2.2 2.2 2.2 2.1 5,629 6,294 5,979 loader 3 - latency p99 read 2.2 2.2 2.3 2.2 5,690 6,291 5,986 loader 4 - latency p99 read 2.2 2.5 2.2 2.2 5,685 6,283 5,986 loader 1 - latency p99 write 3.8 4 4.1 4.1 8,735 9,076 9,149 loader 2 - latency p99 write 3.9 4 4 3.9 8,325 8,898 8,809 loader 3 - latency p99 write 3.9 4 4 4.2 8,455 8,905 8,819 loader 4 - latency p99 write 3.8 4.2 4 4.2 8,450 8,893 8,836 loader 1 - latency p99 mixed 4.1 4 4.3 4.1 4,815 5,005 5,127 loader 2 - latency p99 mixed 4.1 4 4.2 4.1 4,552 4,835 4,899 loader 3 - latency p99 mixed 4.1 4 4.2 4.1 4,589 4,835 4,906 loader 4 - latency p99 mixed 4.1 4.2 4.2 4.1 4,587 4,819 4,903
  25. 25. The different CQL drivers connect to the cluster via a proxy, known as the SNI (Server Name Indication) proxy: ■ Cluster data is stored in a YAML file, that clients use to connect to the cluster. ■ Using TLS, the clients use the SNI field to indicate to which ScyllaDB node they will connect to. ■ They still connect to all shards (shard-aware) Connection to the Cluster
  26. 26. TLS protocol extension, enables connecting to a specific hostname What is SNI?
  27. 27. As part of the ‘S301: ScyllaDB Operations’ course you can learn more about our K8S operator and get some hands-on experience working with it. ScyllaDB University Content
  28. 28. Thank You Stay in Touch Yaniv Kaul yaniv.kaul@scylladb.com @YanivKaul github.com/mykaul www.linkedin.com/in/ykaul/

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