How To Build A Scalable Storage System with OSS at TLUG Meeting 2008/09/13

Sep 13, 2008Download as PPT, PDF9 likes2,071 views

The document discusses Gosuke Miyashita's goal of building a scalable storage system for his company's web hosting service. He is exploring the use of several open source technologies including cman, CLVM, GFS2, GNBD, DRBD, and DM-MP to create a storage system that provides high availability, flexible I/O distribution, and easy extensibility without expensive hardware. He outlines how each technology works and shows some example configurations, but notes that integrating many components may introduce issues around complexity, overhead, performance, stability and compatibility with non-Red Hat Linux.

TLUG Meeting 2008/09/13 Gosuke Miyashita

My company paperboy&co. Web hosting, blog, ec hosting and so on for indivisuals About 1,000 Linux servers Many single servers ...

My goal of a scalable storage system Storage system for a web hosting service High resource availability Flexible I/O distribution Easy to extend Mountable by multiple hosts No SPoF With OSS Without expensive hardwares Now I’m trying technologies for these purposes

cman CLVM GFS2 GNBD DRBD DM-MP Technologies

cman Cluster Manager A component of Red Hat Cluster Suit Membership management Messaging among cluster nodes Needed for CLVM and GFS2

CLVM Cluster Logical Volume Manager Cluster-wide version of LVM2 Automatically share LVM2 metadata among all cluster nodes So logical volumes with CLVM available to all cluster nodes

CLVM clvmd distributes metadata among cluster nodes Logical volumes presented to each cluster node Logical volume on shared storage LVM2 Metadata clvmd LVM2 Metadata clvmd LVM2 Metadata clvmd

GNBD Global Network Block Device Provides block-device access over TCP/IP Similar to iSCSI Advantage over iSCSI is built-in fencing

GNBD TCP/IP network GNBD client GNBD client GNBD client GNBD Server Exported block device

GFS2 Global File System 2 One of cluster-aware file systems Multiple nodes can simultaneously access this filesystem Uses DLM(Distributed Lock Manager) of cman to maintain file system integrity OCFS is another cluster-aware file system

GFS2 These nodes can access to the GFS2 file system simultaneously GNBD Server GFS2 GNBD client cman GNBD client cman GNBD client cman

DRBD Distributed Replicated Block Device RAID1 over a network Mirrors a whole block device over TCP/IP Available Active/Active with cluster file systems

DRBD Replication Server Block Device Server Block Device

DM-MP Device-Mapper Multipath Bundles I/O paths to one virtual I/O path Can choose active/passive or active/active

DM-MP with SAN storage /dev/sda1 /dev/sdb1 Seen as one device /dev/mapper/mpath0 active/passive or active/active Node HBA1 HBA2 SAN swtich 1 SAN swtich 2 Storage CNTRLR1 CNTRLR2

A scalable storage system /dev/VG0/LV0 (CLVM) mount /dev/VG0/LV0 /mnt cman GNBD cman GNBD GNBD Server GFS2 GNBD Server GFS2 Replication (DRBD) /dev/mapper/mpath0 (DM-MP) /dev/gnbd0 /dev/gnbd1 GNBD Server GFS2 GNBD Server GFS2 Replication (DRBD) /dev/mapper/mpath1 (DM-MP) /dev/gnbd2 /dev/gnbd3

How to extend /dev/VG0/LV0 (CLVM) mount /dev/VG0/LV0 /mnt cman GNBD cman GNBD GNBD Server GFS2 GNBD Server GFS2 /dev/mapper/mpath0 /dev/gnbd0 /dev/gnbd1 GNBD Server GFS2 GNBD Server GFS2 /dev/mapper/mpath1 /dev/gnbd2 /dev/gnbd3 GNBD Server GFS2 GNBD Server GFS2 /dev/mapper/mpath2 /dev/gnbd4 /dev/gnbd5

I wonder ... Many components cause troubles? How about overhead and performance? How about stability? More better way? How about other than Red Hat Linux?

Vijayendra Shamanna from SanDisk presented on optimizing the Ceph distributed storage system for all-flash architectures. Some key points: 1) Ceph is an open-source distributed storage system that provides file, block, and object storage interfaces. It operates by spreading data across multiple commodity servers and disks for high performance and reliability. 2) SanDisk has optimized various aspects of Ceph's software architecture and components like the messenger layer, OSD request processing, and filestore to improve performance on all-flash systems. 3) Testing showed the optimized Ceph configuration delivering over 200,000 IOPS and low latency with random 8K reads on an all-flash setup.

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This document summarizes test results of Ceph QoS throttling mechanisms. It finds that: 1) BlueStore adaptive throttling can achieve a desired 1:1:10:10:10 weight distribution but reduces performance by 57%. Lower throttling reduces performance less but harms weight quality. 2) Outstanding IO adaptive throttling reduces performance by 80% to achieve the desired weights. It can also guarantee reservations with an 89% performance reduction. 3) The per-pool QoS with dmClock faces failures when workload queue depths are low or multiple threads access the queue simultaneously, breaking the weight phase. Larger block sizes also impact consistency.

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The document compares the performance of Ceph storage cluster using TCP and RDMA (XIO) as the transport mechanisms. It finds that XIO provides around 30-50% higher IOPS and bandwidth compared to TCP with the same hardware setup. However, TCP performance is improving and catching up to XIO as the number of OSDs increases. While XIO provides better CPU utilization, it requires over 2x more memory usage than TCP. Scaling out to multiple nodes shows TCP scaling better than XIO. XIO performance is also unstable and connection startup times are longer compared to TCP.

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Using Recently Published Ceph Reference Architectures to Select Your Ceph Con...Patrick McGarry

This document discusses using recently published Ceph reference architectures to select a Ceph configuration. It provides an inventory of existing reference architectures from Red Hat and SUSE. It previews highlights from an upcoming Intel and Red Hat Ceph reference architecture paper, including recommended configurations and hardware. It also describes an Intel all-NVMe Ceph benchmark configuration for MySQL workloads. In summary, reference architectures provide guidelines for building optimized Ceph solutions based on specific workloads and use cases.

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QCT Fact Sheet-EnglishPeggy Ho

QCT is a global provider of hyperscale datacenter solutions including servers, storage, networking equipment, and integrated rack systems. It aims to deliver the efficiency, scalability, and reliability of hyperscale designs to all datacenter customers using standard open hardware. QCT is a subsidiary of Quanta Computer, a Fortune 500 company, allowing it to leverage over 14 years of experience in datacenter engineering and manufacturing.

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This document outlines an agenda for a presentation on running MySQL on Ceph storage. It includes a comparison of MySQL on Ceph versus AWS, results from a head-to-head performance lab test between the two platforms, and considerations for hardware architectures and configurations optimized for MySQL workloads on Ceph. The lab tests showed that Ceph could match or exceed AWS on both performance metrics like IOPS/GB and price/performance metrics like storage cost per IOP.

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Après la petite intro sur le stockage distribué et la description de Ceph, Jian Zhang réalise dans cette présentation quelques benchmarks intéressants : tests séquentiels, tests random et surtout comparaison des résultats avant et après optimisations. Les paramètres de configuration touchés et optimisations (Large page numbers, Omap data sur un disque séparé, ...) apportent au minimum 2x de perf en plus.

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HKG15-401: Ceph and Software Defined Storage on ARM servers --------------------------------------------------- Speaker: Yazen Ghannam Steve Capper Date: February 12, 2015 --------------------------------------------------- ★ Session Summary ★ Running Ceph in the colocation, ongoing optimizations -------------------------------------------------- ★ Resources ★ Pathable: https://hkg15.pathable.com/meetings/250828 Video: https://www.youtube.com/watch?v=RdZojLL7ttk Etherpad: http://pad.linaro.org/p/hkg15-401 --------------------------------------------------- ★ Event Details ★ Linaro Connect Hong Kong 2015 - #HKG15 February 9-13th, 2015 Regal Airport Hotel Hong Kong Airport --------------------------------------------------- http://www.linaro.org http://connect.linaro.org

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Ceph is designed around the assumption that all components of the system (disks, hosts, networks) can fail, and has traditionally leveraged replication to provide data durability and reliability. The CRUSH placement algorithm is used to allow failure domains to be defined across hosts, racks, rows, or datacenters, depending on the deployment scale and requirements. Recent releases have added support for erasure coding, which can provide much higher data durability and lower storage overheads. However, in practice erasure codes have different performance characteristics than traditional replication and, under some workloads, come at some expense. At the same time, we have introduced a storage tiering infrastructure and cache pools that allow alternate hardware backends (like high-end flash) to be leveraged for active data sets while cold data are transparently migrated to slower backends. The combination of these two features enables a surprisingly broad range of new applications and deployment configurations. This talk will cover a few Ceph fundamentals, discuss the new tiering and erasure coding features, and then discuss a variety of ways that the new capabilities can be leveraged.

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Accelerating Ceph with RDMA and NVMe-oFinside-BigData.com

Haodong Tang from Intel gave this talk at the 2018 Open Fabrics Workshop. "Efficient network messenger is critical for today’s scale-out storage systems. Ceph is one of the most popular distributed storage system providing a scalable and reliable object, block and file storage services. As the explosive growth of Big Data continues, there're strong demands leveraging Ceph build high performance & ultra-low latency storage solution in the cloud and bigdata environment. The traditional TCP/IP cannot satisfy this requirement, but Remote Direct Memory Access (RDMA) can. "In this session, we'll present the challenges in today's distributed storage system posed by network messenger with the profiling results of Ceph All Flash Array system showing the networking already become the bottleneck and introduce how we achieved 8% performance benefit with Ethernet RDMA protocol iWARP. We'll first present the design of integrating iWARP to Ceph networking module together with performance characterization results with iWARP enabled IO intensive workload. The send part, we will explore the proof-of-concept solution of Ceph on NVMe over iWARP to build high-performance and high-density storage solution. Finally, we will showcase how these solutions can improve OSD scalability, and what’s the next optimization opportunities based on current analysis." Watch the video: https://wp.me/p3RLHQ-ikV Learn more: http://intel.com and https://insidehpc.com/2018/04/amazon-libfabric-case-study-flexible-hpc-infrastructure/ Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter

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1. TLUG Meeting 2008/09/13 Gosuke Miyashita

2. My company paperboy&co. Web hosting, blog, ec hosting and so on for indivisuals About 1,000 Linux servers Many single servers ...

3. My goal of a scalable storage system Storage system for a web hosting service High resource availability Flexible I/O distribution Easy to extend Mountable by multiple hosts No SPoF With OSS Without expensive hardwares Now I’m trying technologies for these purposes

5. cman CLVM GFS2 GNBD DRBD DM-MP Technologies

6. cman Cluster Manager A component of Red Hat Cluster Suit Membership management Messaging among cluster nodes Needed for CLVM and GFS2

7. CLVM Cluster Logical Volume Manager Cluster-wide version of LVM2 Automatically share LVM2 metadata among all cluster nodes So logical volumes with CLVM available to all cluster nodes

8. CLVM clvmd distributes metadata among cluster nodes Logical volumes presented to each cluster node Logical volume on shared storage LVM2 Metadata clvmd LVM2 Metadata clvmd LVM2 Metadata clvmd

9. GNBD Global Network Block Device Provides block-device access over TCP/IP Similar to iSCSI Advantage over iSCSI is built-in fencing

10. GNBD TCP/IP network GNBD client GNBD client GNBD client GNBD Server Exported block device

11. GFS2 Global File System 2 One of cluster-aware file systems Multiple nodes can simultaneously access this filesystem Uses DLM(Distributed Lock Manager) of cman to maintain file system integrity OCFS is another cluster-aware file system

12. GFS2 These nodes can access to the GFS2 file system simultaneously GNBD Server GFS2 GNBD client cman GNBD client cman GNBD client cman

13. DRBD Distributed Replicated Block Device RAID1 over a network Mirrors a whole block device over TCP/IP Available Active/Active with cluster file systems

14. DRBD Replication Server Block Device Server Block Device

15. DM-MP Device-Mapper Multipath Bundles I/O paths to one virtual I/O path Can choose active/passive or active/active

16. DM-MP with SAN storage /dev/sda1 /dev/sdb1 Seen as one device /dev/mapper/mpath0 active/passive or active/active Node HBA1 HBA2 SAN swtich 1 SAN swtich 2 Storage CNTRLR1 CNTRLR2

17.

18. A scalable storage system /dev/VG0/LV0 (CLVM) mount /dev/VG0/LV0 /mnt cman GNBD cman GNBD GNBD Server GFS2 GNBD Server GFS2 Replication (DRBD) /dev/mapper/mpath0 (DM-MP) /dev/gnbd0 /dev/gnbd1 GNBD Server GFS2 GNBD Server GFS2 Replication (DRBD) /dev/mapper/mpath1 (DM-MP) /dev/gnbd2 /dev/gnbd3

19. How to extend /dev/VG0/LV0 (CLVM) mount /dev/VG0/LV0 /mnt cman GNBD cman GNBD GNBD Server GFS2 GNBD Server GFS2 /dev/mapper/mpath0 /dev/gnbd0 /dev/gnbd1 GNBD Server GFS2 GNBD Server GFS2 /dev/mapper/mpath1 /dev/gnbd2 /dev/gnbd3 GNBD Server GFS2 GNBD Server GFS2 /dev/mapper/mpath2 /dev/gnbd4 /dev/gnbd5

20.

21. I wonder ... Many components cause troubles? How about overhead and performance? How about stability? More better way? How about other than Red Hat Linux?

22.

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