HPE és SUSE alapú megoldások –gépteremtől a felhőig

Sept 2019

Molnár Zoltán (zoltan.molnar@hpe.com)Wahl László (laszlo.wahl@hpe.com)

SUSE products offered by HPE

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Product For…

SUSE Linux Enterprise Server General purpose

SLES for SAP Applications Any SAP applications

SLES for HPC HPC environments

SLE High Availability Extension High availability cluster add-on to SLES

SUSE Manager Comprehensive Linux Server Management

SUSE Enterprise Storage Highly scalable data storage built on CEPH

To learn more, visit SUSE website

Object Storage solutions from HPE

HPE Apollo for Ceph block/object

− Ceph is preferred by open-source users for

OpenStack deployments, esp. virtual machine

boot (block access)

− Ceph can be deployed in production for object

stores up to 1PB,using Swift and S3 access

− Ceph can do full-site asynchronous replication

for disaster recovery

Apollo 4200 Gen10 serverDrive bays and rack depth

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12+12 LFF or 24+24 SFFfront drive bays

2U standard rack depth

HPE Apollo 4510 Gen10 chassis

HDD drawer 1 extended

(HDD 1-30)

HDD drawer 2 (HDD 31-60)

Fits in HPE standard 1075 mm rack

Apollo 4510 Gen10 systemChassis

5HPE ProLiant XL450 Gen10 server

− New form factor

− Fits in smaller rack

− More processing cores

HPE Composable Fabric attach to ProLiant DL servers Perfect for machine-to-machine workloads

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HPE Composable Fabric

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Modern SDDC workloads are

100% machine-to-machinescale-out

Ceph Use Cases - SUSE Storage Solution for Disk-Based Backup

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Ceph Use Cases - High-Performance Computing (HPC) Storage

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HPE Persistent Memory Portfolio

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HPE Persistent Memory

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Processor CPU

CPU cache

SD-RAM/DDR-SDRAM

Physical memory

HPE Smart Memory

Solid-State Drives HPE Optane™ SSDHPE SSD

Solid-state memory

Mechanical Hard Drives

Virtual memory HPE Hard Drives

HPE Persistent Memory

Redefining the memory/storage hierarchy

HPE Persistent Memory What is phase-change memory?

11Memory bus connects main memory to the CPU memory controller

Phase-ChangeMemory Media

DDR4 Memory Bus

ApplicationsHPE Persistent

Memory

Intel Next-Generation Xeon

Processor

– Transistor-less

technology

– Higher density and

capacity

– Fast access time due

to low latency of the

media

– Inherently persistent

– Fast access to

memory in dim form

requires use of fast

DDR memory bus

– However, memory

bus not designed for

larger capacities or

persistent data

– Legacy app

pathways cannot

recognize persistent

quality of memory or

additional option to

place data

– App improvements

allow visibility to this

tier and ability to

send data in blocks,

meaning it can act as

small but super fast

storage device

Two configuration

options:

– Super-large

capacity memory

– Super-fast storage

device

– Integrated memory

controller needed

modifications in

order to handle

different types of

data and

communicate with

the DIMM

– Platinum, Gold (and

one Silver) CPUs

only

HPE Persistent MemoryWorkloads and applicable modes

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Cloud & VMS

Extended VMMemory Capacity

More VMs and Containers per

System

OS MemoryExtension

Storage

Super-fast Storage

Meta-data Management

Write Buffers

Caching Layers

Database

In-memory Database

DB Caching Tiers with higher Capacity

Logging

RDMA Replication

HPC

Larger Memory

Check-pointing

PMem over Fabric

File System Swap

AI/Analytics

Off-heap Memory

Real-time Analytics

Emerging Analytics Platforms

Machine Learning Analytics

Memory mode Memory or App Direct mode App Direct mode

Comms

Network Function Virtualization Infrastructure

CognitiveNetworking

Content Delivery Network (CDN)

Memory mode Memory or App Direct mode App Direct mode

Holds running programs and information the processor is currently using

Preserves data and programs for future uses

Highest PMM Affinity

HPE Persistent MemoryMemory mode

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1. “Fast performance comparable to DRAM” -Intel persistent memory is expected to perform at latencies near DDR4 DRAM. Benchmarks and proof points forthcoming. “low latencies” -Data transferred

across the memory bus causes latencies to be orders of magnitude lower when compared to transferring data across PCIeor I/O bus’to NAND/Hard Disk. Benchmarks and proof points forthcoming.

2. HPE persistent memory offers 3 different capacities –128GB, 256GB, 512GB. Individual DIMMs of DDR4 DRAM max out at 128GB.

3. A BIOS update will be required before using HPE DC Persistent Memory

Large memory capacity

– Up to 4x largest available DRAM

capacity

Easy deployment

– No software / application changes

required

Performance comparable to

DRAM at low latencies1

– Same as DRAM for cache hit

Data is volatile

– Volatile mode key cleared and

regenerated with each power cycle

DRAM used as persistent

memory cache

– Managed by memory controller

– Within same memory controller, not

across

2933 MT/s DRAM runs at slower

2666 MT/s speed

HPE Persistent MemoryApp Direct mode

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Persistent memory is used as

storage

– Resides on the memory sub-system

– Low latency, native persistence

– Recognized by OS as storage

Byte addressable like memory

– Up to 4x largest available DRAM

capacity

Significantly faster storage

– High availability, less downtime

– Move, store, and process larger data

sets closer to the processor

Higher cost storage relative

to NAND

– Better performance as a result of

residing on memory subsystem

DRAM used as main memory

– No additional memory benefits provided

by persistent memory

Occupies high value (and limited)

DIMM slots

Requires application

modifications to take full

advantage of persistent memory

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Use Case – Enterprise Storage PM development

- Now not need a flush call- Transactional- DK library handles of all- Multi platform support (C++,c#, Java, ect)

Use Case - SAP HANA Persistent Memory

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• SAP HANA focus is on leveraging memorymapping in NVM.PM.FILE mode whichenables direct access to persistent memoryusing CPU instructions

• Primary data store is data volume (in SAN or localstorage)

• Main is in 3D XPoint™ PM instead of DRAM and is nowpersistent On Restart: Main already in 3D XPoint™ PM,no need to load data from SAN

On HW failure: Backup server loads data from data volume

• Significant improvements in the database restart time• >5X improvement measured

The power of software-defined datacenter managementEnabling a broad ecosystem

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DevOps engine IT Ops engine

Facilities engineCloud engine

Developer toolkitsSoftware Defined Intelligence

Unified API

Fluid Resource Pools

Consume Hybrid to Edge - HPE GreenLakeConsume IT across your infrastructure, workloads, and multi-cloud environment

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– Pay per use consumption models,

across public and private clouds

– Services to operate your AWS or Azure

public cloud program

– Azure Stack private cloud, designed,

built, run, pay per use on-premises

HPE GreenLakeFlex Capacity

– Pay per use integrated solutions e.g.

Backup, Big Data, SAP and EDB

Postgres

– On premises solutions including

hardware, software, services with

simple outcome-based payment

– Designed, integrated and operated

for you

HPE GreenLake Workload Solutions

– Pay per use model on premises,

metered using

HPE IP

– Consumption of hardware

infrastructure or by Virtual Machines

– Enterprise grade support, active

capacity management

HPE GreenLake Hybrid Cloud

Hybrid Cloud

Private cloud

WorkloadAWS Azure

Infrastructure

Thank you

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