The Cloud promises.
Keynote of the Global Azure Bootcamp 2019 in Paris on April 27th.
The cloud promises of lot of benefit (AI everywhere, IAAS replacement with PAAS) but also some side effects (IT jobs at risk). I took a look back and gave some perspectives.
6. Developer Growth
By industry (US), 2006-2016
-2.0%
-1.0%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
Developer Non-Developer
Education
RealEstate&
Construction
Entertainment
&Hospitality
Healthcare
FinancialServices
Government
Manufacturing
Retail&Wholesale
Nearly every industry is being affected…
7. Role of SW in Auto
Developers as a % of Overall Headcount
1.0%
6.6%
Average American
Car Company
Role of software in Automotive
12. Azure is Microsoft’s cloud computing platform
YouManage
Managedbyvendor
Azure Microsoft 365
13. Azure server generations
Gen 2
Processor 2 x 6 Core 2.1 GHz
Memory 32 GiB
Hard Drive 6 x 500 GB
SSD None
NIC 1 Gb/s
Gen 3
Processor 2 x 8 Core 2.1 GHz
Memory 128 GiB
Hard Drive 1 x 4 TB
SSD 5 x 480 GB
NIC 10 Gb/s
HPC
Processor 2 x 12 Core 2.4 GHz
Memory 128 GiB
Hard Drive 5 x 1 TB
SSD None
NIC 10 Gb/s IP, 40 Gb/s IB
Gen 4
Processor 2 x 12 Core 2.4 GHz
Memory 192 GiB
Hard Drive 4 x 2 TB
SSD 4 x 480 GB
NIC 40 Gb/s
Godzilla
Processor 2 x 16 Core 2.0 GHz
Memory 512 GiB
Hard Drive None
SSD 9 x 800 GB
NIC 40 Gb/s
Gen 5.1
Processor 2 x 20 Core 2.3 GHz
Memory 256 GiB
Hard Drive None
SSD
6 x 960 GB PCIe Flash
and 1 x 960 GB SATA
NIC 40 Gb/s + FPGA
GPU Gen 5
Processor 2 x 8 Core 2.6 GHz
Memory 256 GiB
Hard Drive 1 x 2 TB
SSD 1 x 960 GB SATA
NIC 40 Gb/s
GPU 2 x 2 Compute GPU
Beast
Processor 4 x 18 Core 2.5 GHz
Memory 4096 GiB
Hard Drive None
SSD
4 x 1920 GB NVMe and 1
x 960 GB SATA
NIC 40 Gb/s
Gen 6
Processor
2 x Skylake 24 Core
2.7GHz
Memory 768GiB DDR4
Hard Drive None
SSD
4 x 960 GB M.2 SSDs and
1 x 960 GB SATA
NIC 40 Gb/s
FPGA Yes
Mega Beast
Processor 4 x 18 Core 2.5 GHz
Memory 12,288 GiB
Hard Drive None
SSD
4 x 1920 GB NVMe and 1
x 960 GB SATA
NIC 40 Gb/s
14. Azure provides best in class performance
Compute
performance
Largest in public cloud
Memory
Largest in public cloud
Remote Storage
(single disk)
Fastest in public cloud
Local
storage
Fastest in public cloud
File storage
Fastest in public cloud
VM-VM Networking
Fastest in public cloud
Hybrid Networking
Fastest in public cloud
15. Joint Announcement between SAP and Microsoft
Nov. 28th
• Microsoft runs SAP S/4HANA on Azure
• SAP migrates their internal applications to
Azure
• Microsoft and SAP will jointly offer SAP
HANA Enterprise Cloud (HEC) on Azure
17. Basic General Purpose Memory Optimized
Intended use case
Built for workloads with light compute and
variable I/O performance.
Ideal for most business workloads offering balanced compute
and memory with scalable I/O throughput.
Built for high-performance database workloads
requiring in-memory performance for faster
transaction processing and
higher concurrency.
vCore 1 2 2 4 8 16 32 64 2 4 8 16 32
Compute Generation Gen 4, Gen 5 Gen 4, Gen 5 Gen 5 only
Memory 2 GB per vCore 5 GB per vCore 10 GB per vCore
Storage
5 GB – 1 TB
Magnetic Media
5 GB – 4 TB
Remote SSD
5 GB – 4 TB
Remote SSD
IOPS Variable 100 – 6000 IOPS 100 – 6000 IOPS
Backup retention 7 – 35 days 7 – 35 days 7 – 35 days
Backup storage Locally redundant Locally or geographically redundant Locally or geographically redundant
Ser vice tiers for Azure Database Ser vices for MySQL,
PostgreSQL, and MariaDB
18. Control access
• Secure SSL connectivity
• Server firewall rules
• Virtual Network (SE)
Protect data
• Built-in encryption at-rest
for data and backups
Security built in
Identity
• Native authentication
• Threat detection
19. Secure and compliant
• Protect your data with up-to-date security and
compliance features with the Azure IP Advantage.
SOC1 – Compliant
SOC2 – Compliant
SOC3 – Compliant
ISO 27001:2013 – Compliant
ISO 27018:2014 – Compliant
CSA STAR Certification – Compliant
HIPAA / HITECH Act – Compliant
PCI DSS Level 1 – Compliant
ISO 27017:2015 – Compliant
ISO 27018:2014 – Compliant
ISO 9001:2015 – Compliant
ISO/IEC 20000-1:2011 – Compliant
ISO 22301:2012 – Pending
SOC 2
Type 2
CSA STAR
Certification
Level 1
20. Built-in High Availability
Server provisioning and
management
Retry
Elastically scale your compute up or down
Independently scale up storage as needed seamlessly
Use replicas only if you need to!
MySQL IP:3306
PGSQL IP:5432
US West
Azure Storage
MySQL or
PostgreSQL
Server
MySQL or
PostgreSQL
Server
27. Machine learning
Sophisticated pretrained models
To simplify solution development
Popular frameworks
To build advanced deep learning solutions
Productive services
To empower data science and development teams
Powerful infrastructure
To accelerate deep learning
Flexible deployment
To deploy, manage models on intelligent cloud & edge
34. Who’s that guy
Alex Danvy
Technical Evangelist, Microsoft
@danvy
danvy.tv
#iot de #cloud #ai #quantum #geek #cooking
Editor's Notes
Today, the world is reaching another inflection point.
Software is being infused in every part of business, making every company a software company.
As you can see, this is happening across every industry where even in areas where there are less non-developer roles, the need for developers is increasing.
Even in the automotive industry, you can see the role of software where developers make up 1% of the overall headcount in the average America Car Company.
At Tesla, 6.6% of overall headcount is comprised of developer roles.
Azure is Microsoft’s cloud computing platform. Simply put, cloud computing is the delivery of computing services—servers, storage, databases, networking, software, analytics, intelligence and more—over the Internet (“the cloud”) to offer faster innovation, flexible resources, and economies of scale. You typically pay only for cloud services you use, helping lower your operating costs, run your infrastructure more efficiently, and scale as your business needs change.
When we talk about Microsoft Azure, we’re really talking about Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) .
IaaS in Azure is where the infrastructure like Networking, Storage, etc. is managed by Microsoft and the rest is managed by you.
PaaS in Azure is where you let Microsoft manage everything except your applications and your data.
And finally, Software as a Service (SaaS) are things like Microsoft 365 or Office 365 running in the cloud.
13
Max CPU on AWS – U-metal offering they have 8 sockets x 28 cores x 2(HT) = 448
Max Memory on AWS – 12 TB
Max Remote Storage on AWS – 40K IOPs / ~160K IOPs for entire VM
Max Local Disk – 3.3M on i3.metal on AWS (Gartner hit 5.5M IOPs on Oracle)
File Storage – 18K on AWS (based upon Gartner testing)
VM networking – 20 Gbps Ethernet on AWS
Hybrid networking – 10 Gbps on AWS
- Virtual Network Service Endpoints
SOC2 - Service Organization Controls standards for operational security
ISO 27001 - Information Security Management Standards
ISO 27018 - Code of Practice for Protecting Personal Data in the Cloud
CSA STAR - Cloud Security Alliance: Security, Trust & Assurance Registry (STAR)
PCI DSS Level 1 - Payment Card Industry (PCI) Data Security Standard (DSS) Level 1 Service Provider
HIPAA / HITECH Act - Health Insurance Portability and Accountability Act / Health Information Technology for Economic and Clinical Health Act
ISO 27017:2015 - Code of Practice for Information Security Controls
ISO 27018:2014 – assesses control environment to protect of personal data in the cloud.
ISO 9001:2015 Quality Management Systems Standards
ISO 22301:2012 Business Continuity Management Standard
ISO/IEC 20000-1:2011 Information Technology Service Management
Setting-up high availability for database servers is hard, requiring either custom code to manage detection/failover, or expensive 3rd party solutions to make it a bit easier. Worse yet, it’s expensive as typically a second database server (replica) is necessary in order to fail-over in a matter of seconds. A second server = 2x the cost for HA. For AWS customers, you cannot receive a SLA from Amazon on your database server unless you have deployed in a multi-AZ, again meaning 2x the cost.
Azure Database Services is built upon the SQL Database platform which is a Service Fabric-based PaaS solution. As such, rather than having to boot-up an entire OS stack to bring up a new server (such as in IaaS), Azure Database Services run the database engine in a custom container technology which you can think of as a secure “pico process”. The time it takes to bring-up a new server in this custom container is a matter of seconds. This means that in the event that your database server has hung, or “gone away”, the Azure Database Management Service” detects the failure, brings-up a new server in this lightweight container, maps the new IP address to the DNS name of your instance and maps to your storage. This entire process takes between 30-45 seconds. This is built-in to all performance tiers of Azure Database Services and since a replica instance isn’t needed, there is no additional cost to the customers. In contrast, an AWS RDS server that is deployed in a single AZ would take minutes to start – and that does not account for how you would detect the failure and switch-over.
We think about Machine Learning on Azure into these layers.
At the top, we have the sophisticated pre-trained models, built by MS Research for products like Bing and Office.
They’ve been made available to you for use in your apps, and for customization, as needed.
Then we have Popular frameworks.
We support all of the major frameworks that you want to use, and we have a commitment to openness so you’re not locked into a particular model or framework.
We then built services that the frameworks can run on.
These services enable you to be come productive and to manage your workflow as you’re doing ML, to figure out run histories, and hyper parameter tuning, and all the things that a data scientist needs to do, we deliver in the services layer.
These run on a powerful infrastructure.
We’ve made a lot of investments in the hardware layer to differentiate ourselves.
We have the most comprehensive GPU fleet, so customers can choose the right mix of performance and price. This is important because GPU’s normally cost a lot.
With regards to FPGA, we are unique in HW accelerated models.
Google is restrictive with TPUs (it can only run Tensorflow models). AWS just has vanilla FPGAs machines.
So we are ahead today, and our strategy to allow any framework to run on FPGAs in future is differentiated. It gets more differentiated when FPGAs will be available in Azure Stack.
And finally, there’s flexible deployment.
Not only do you need the tools, framework and platform to build these AI models, but you need to be able to deploy these models where you need them, whether it’s in the cloud, on-premises or even at the edge.