Slides presented during HomeGen by CloudGen Verona, about how to properly size an Azure IaaS VM, with an additional focus on high availability and cost-saving topics.
Session recording: https://youtu.be/C8v6c6EkJ9A
Demo: https://github.com/OmegaMadLab/SqlIaasVmPlayground
Global Azure Virtual 2020 What's new on Azure IaaS for SQL VMsMarco Obinu
Come dimensionare una VM per SQL Server in Azure IaaS, alla luce delle ultime novità della piattaforma.Sessione erogata il 24 Aprile 2020, nell'ambito del Global Azure Virtual 2020.
Video sessione: https://youtu.be/7o80CJUtnh4
Demo: https://github.com/OmegaMadLab/SqlIaasVmPlayground
ARM Template ottimizzato per SQL Server: https://github.com/OmegaMadLab/OptimizedSqlVm-v2
This tutorial will guide you how to experiment with XAP 10 MemoryXtend
We will use EC2 to start a VM with a Flash Drive.
You may use any other machine running Linux 6.x with SSD Flash Drive with this tutorial.
Global Azure Virtual 2020 What's new on Azure IaaS for SQL VMsMarco Obinu
Come dimensionare una VM per SQL Server in Azure IaaS, alla luce delle ultime novità della piattaforma.Sessione erogata il 24 Aprile 2020, nell'ambito del Global Azure Virtual 2020.
Video sessione: https://youtu.be/7o80CJUtnh4
Demo: https://github.com/OmegaMadLab/SqlIaasVmPlayground
ARM Template ottimizzato per SQL Server: https://github.com/OmegaMadLab/OptimizedSqlVm-v2
This tutorial will guide you how to experiment with XAP 10 MemoryXtend
We will use EC2 to start a VM with a Flash Drive.
You may use any other machine running Linux 6.x with SSD Flash Drive with this tutorial.
Databases are a key part of any application. The storage subsystem contributes most to performance of the database. In recent days, new storage technologies like Solid State Storage (SSD) and high performance drives are becoming cheaper and more accessible, but it takes a lot of planning to use these technologies in a cost effective way for best price-performance.
Cassandra Day SV 2014: Designing Commodity Storage in Apache CassandraDataStax Academy
As we move into the world of Big Data and the Internet of Things, the systems architectures and data models we've relied on for decades are becoming a hindrance. At the core of the problem is the read-modify-write cycle. In this session, Al will talk about how to build systems that don't rely on RMW, with a focus on Cassandra. Finally, for those times when RMW is unavoidable, he will cover how and when to use Cassandra's lightweight transactions and collections.
By using Cloud Storage Ceph you can start building your cloud foundation or big data storage backend with an affordable small pc. Even using really cheap cloud storage to learn and use 40TB storage cost over 3400$ USD a year.
Let's take a look how can we build a cloud storage of your own.
Databases are a key part of any application. The storage subsystem contributes most to performance of the database. In recent days, new storage technologies like Solid State Storage (SSD) and high performance drives are becoming cheaper and more accessible, but it takes a lot of planning to use these technologies in a cost effective way for best price-performance.
Cassandra Day SV 2014: Designing Commodity Storage in Apache CassandraDataStax Academy
As we move into the world of Big Data and the Internet of Things, the systems architectures and data models we've relied on for decades are becoming a hindrance. At the core of the problem is the read-modify-write cycle. In this session, Al will talk about how to build systems that don't rely on RMW, with a focus on Cassandra. Finally, for those times when RMW is unavoidable, he will cover how and when to use Cassandra's lightweight transactions and collections.
By using Cloud Storage Ceph you can start building your cloud foundation or big data storage backend with an affordable small pc. Even using really cheap cloud storage to learn and use 40TB storage cost over 3400$ USD a year.
Let's take a look how can we build a cloud storage of your own.
Sql Start! 2020 - SQL Server Lift & Shift su AzureMarco Obinu
Slide of the session delivered during SQL Start! 2020, where I illustrate different approaches to determine the best landing zone for you SQL Server workloads.
Video (ITA): https://youtu.be/1hqT_xHs0Qs
Liberati dal sovraccarico e dalle limitazioni dell’infrastruttura locale. Sfrutta risorse illimitate per ottenere scalabilità per i processi HPC (High Performance Computing), per analizzare dati su vasta scala, eseguire simulazioni e modelli finanziari e sperimentare riducendo il tempo di immissione sul mercato.
This presentation is for those of you who are interested in moving your on-prem SQL Server databases and servers to Azure virtual machines (VM’s) in the cloud so you can take advantage of all the benefits of being in the cloud. This is commonly referred to as a “lift and shift” as part of an Infrastructure-as-a-service (IaaS) solution. I will discuss the various Azure VM sizes and options, migration strategies, storage options, high availability (HA) and disaster recovery (DR) solutions, and best practices.
Can we leverage the resource of public cloud for gaming, streaming, transcoding, machine learning and visualized CAD application on demand? Yes if it provides the capability and infrastructure to utilize GPUs. Can we get high performance networking in the cloud as what I have in the bare metal environment? Yes with SR-IOV. How to achieve them? In this presentation we describe Discrete Device Assignment (also known as PCI Pass-through) support for GPU and network adapter in Linux guest and SR-IOV architectures of Linux guest with near-native performance profile running on Hyper-V. We also will share how to integrate accelerated graphics and networking capabilities in Microsoft Azure infrastructure.
Webinar: Untethering Compute from StorageAvere Systems
Enterprise storage infrastructures are gradually sprawling across the globe and consumers of data increasingly require access to remote storage resources. Solutions for mitigating the pain associated with this growth are out there, but performance varies. This Webinar will take a look at these challenges, review available solutions, and compare tests of performance.
Similar to Azure VM 101 - HomeGen by CloudGen Verona - Marco Obinu (20)
Implement a disaster recovery solution for your on-prem SQL with Azure? Easy!Marco Obinu
Slides presented at SQL Saturday 980 Plovdiv, talking about the different architectures you can implement to protect your on-premises SQL Server workloads on Azure for DR purposes.
Infrastructure as Code on Azure - Show your Bicep! v0.2 - .NetConf 2020 by Do...Marco Obinu
Slides of the presentation about Infrastructure as Code on Azure, ARM Templates, and Project Bicep I presented @ .Net Conf 2020 by DotNetToscana.
Video: https://youtu.be/IcDP2GQvs7w
Demo: https://github.com/OmegaMadLab/StartingWithProjectBicep
SQL Server Lift & Shift on Azure - SQL Saturday 921Marco Obinu
Slides presented at SQL Saturday 921, while talking about how to plan a Lift & Shift migration for SQL Server workloads, depicting the pros & cons of using different Azure services as landing zones.
Sql Saturday 895 - SQL Server e PowerShell: from Zero to HeroMarco Obinu
Slides of the session held at SQL Saturday 895 - Parma 2019 about the use of PowerShell in conjunction with SQL Server.
Demo scripts available at https://github.com/OmegaMadLab/SqlPowerShell-FromZeroToHero
Session recording available at https://youtu.be/yR3TfZfzHss
Automazione serverless con Azure Functions e PowerShell - Marco Obinu - DevOp...Marco Obinu
Slide of the session held @ DevOps Heroes 2019 in Parma.
Session video is available here: https://youtu.be/0ZK1SQ6zkiU
Demo scripts are available here: https://github.com/OmegaMadLab/StartingWithPoshAzureFunctions
Azure Saturday Pordenone 2019 - Reagire agli eventi di infrastruttura con Azu...Marco Obinu
Introduzione al servizio Azure Monitor, e a come può essere utilizzato eseguire automazione serverless scatenate dalle alert.
Demo: https://github.com/OmegaMadLab/AzureMonitorDemo
Video: https://www.youtube.com/watch?v=ifHJATNmC9k
SQL Saturday 871 - Sardegna 2019 - SQL Server DR on AzureMarco Obinu
Slides presented at SQL Saturday 871, regarding DR technologies for SQL Server using Azure as a secondary datacenter. Slides includes demo videos on how to extend an existing SQL FCI to Azure with Basic Availabity Groups.
Demo scripts available at https://github.com/OmegaMadLab/FCI_and_AG
Full session recording available at https://www.youtube.com/watch?v=s8TmM-0E9sQ
SQL Start! 2019 - Ancona - Distribuisci ed amministra le tue istanze SQL Serv...Marco Obinu
Sessione tenuta al SQL Start! 2019 di Ancona, in cui introduco i concetti base di PowerShell e PowerShell DSC nel contesto di SQL Server.
Demo: https://github.com/OmegaMadLab/DeployAndManageSqlInstancesWithPowerShell
Global Azure BootCamp 2019 - Verona - Ottimizzazione delle VM SQL Server su A...Marco Obinu
Sessione tenuta al Global Azure BootCamp 2019, organizzato dalla community CloudGen a Verona, in cui parlo di come dimensionare ed ottimizzare le VM SQL Server su Azure IaaS come da best practices di riferimento Microsoft.
Video: https://youtu.be/Bg9aJAXvoZI
Demo: https://github.com/OmegaMadLab/GAB2019VR-Demo
Breve sessione di introduzione ad Azure Cloud Shell, tenuta nel corso del Global Azure BootCamp 2019, organizzato dalla community CloudGen a Verona
Video: https://youtu.be/30df2Rj-mOo
Demo: https://github.com/OmegaMadLab/GAB2019VR-Demo
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
2. Who I am
@OmegaMadLab
https://github.com/OmegaMadLab
Marco Obinu
@OmegaMadLab
marco.obinu@omegamadlab.com
http://www.omegamadlab.com
https://github.com/OmegaMadLab
https://www.linkedin.com/in/marco-obinu-omegamadlab/
https://www.youtube.com/channel/UCpkBeQSscC1iBvpNP4VNTKQ
• Geek to the bone 🤓
• Advisory Engineer @ SoftJam S.p.A.
• Azure Solution Architect Expert
3. Planning for an Azure VM
What do you need to define before starting the deployment?
5. What do you need to define before starting the deployment?
1. Logical grouping of resources
• Will the VM be part of a system?
2. Network requirements
• In which network do we have to place the VM?
• Does it need a public IP?
3. Application requirements
• Do we need high availability?
• Does the VM need any special feature?
• How many CPUs, RAM, disks and NIC do we need?
6. What do you need to define before starting the deployment?
1. Logical grouping of resources
• Will the VM be part of a system?
2. Network requirements
• In which network do we have to place the VM?
• Does it need a public IP?
3. Application requirements
• Do we need high availability?
• Does the VM need any special feature?
• How many CPUs, RAM, disks and NIC do we need?
7. What do you need to define before starting the deployment?
1. Logical grouping of resources
• Will the VM be part of a system?
2. Network requirements
• In which network do we have to place the VM? *
• Does it need a public IP?
3. Application requirements
• Do we need high availability? *
• Does the VM need any special feature?
• How many CPUs, RAM, disks and NIC do we need?
* it can be a mess to change this later
9. Operating systems
Operating System Version
Microsoft
Windows Server 2003 - 2019
Windows 7, 8.1, 10
Open Source
CentOS 6.3+, 7.0+, 8.0+
CoreOS 494.4.0+
Debian Debian 7.9+, 8.2+, 9, 10
Oracle Linux 6.4+, 7.0+
Red Hat Enterprise Linux 7.1+, 8.0+
SUSE Linux Enterprise
SLES/SLES for SAP
11 SP4
12 SP1+
15
openSUSE openSUSE Leap 42.2+
Ubuntu Ubuntu 12.04+
• Marketplace
• Custom images
• Azure Site Recovery
10. Families and series
Family Series Optimized for
General purpose B, Dsv3, Dv3, Dasv4,
Dav4, DSv2, Dv2, Av2,
DC, DCv2
Balanced CPU-to-memory ratio. Ideal for testing and development, small to medium
databases, and low to medium traffic web servers.
Compute
optimized
Fsv2 High CPU-to-memory ratio. Good for medium traffic web servers, network
appliances, batch processes, and application servers.
Memory
optimized
Esv3, Ev3, Easv4, Eav4,
Mv2, M, DSv2, Dv2
High memory-to-CPU ratio. Great for relational database servers, medium to large
caches, and in-memory analytics.
Storage optimized Lsv2 High disk throughput and IO ideal for Big Data, SQL, NoSQL databases, data
warehousing and large transactional databases.
GPU NC, NCv2, NCv3, ND,
NDv2 (Preview), NV,
NVv3, NVv4
Specialized virtual machines targeted for heavy graphic rendering and video editing,
as well as model training and inferencing (ND) with deep learning. Available with
single or multiple GPUs.
High performance
compute
HB, HBv2, HC, H Our fastest and most powerful CPU virtual machines with optional high-throughput
network interfaces (RDMA).
11. Azure Storage
(remote storage)
A complex object
Virtualization host
OsDisk DataDisk DataDisk
VM
VM NIC vSwitch Host NIC
BlobCache (local storage)
TempDisk
RAM cache
SSD cache
12. Size matters
Family, series and size of the VM also affects:
• Access to Premium Storage
• Computing power
• Disk throughput & number of data disks
• Cache and Temporary disk size & throughput
• Network bandwidth & Accelerated Network
DS12v2 – 4 core 28 GB
ACU 210-250
Cached tp. 16000/128 (144)
Uncached tp. 12800/192
NIC/Mbps 4/3000
DS13v2 – 8 core 56 GB
ACU 210-250
Cached tp. 32000/256 (288)
Uncached tp. 25600/384
NIC/Mbps 8/6000
Esv3 – 8 core 64 GB
ACU 160-180
Cached tp. 16000/128 (200)
Uncached tp. 12800/192
NIC/Mbps 4/4000
Azure Storage
(remote storage)
Virtualization host
OsDisk DataDisk DataDisk
VM
VM NIC vSwitch Host NIC
BlobCache (local storage)
TempDisk
RAM cache
SSD cache
13. Size matters
Family, series and size of the VM also affects:
• Access to Premium Storage
• Computing power
• Disk throughput & number of data disks
• Cache and Temporary disk size & throughput
• Network bandwidth & Accelerated Network
DS12v2 – 4 core 28 GB
ACU 210-250
Cached tp. 16000/128 (144)
Uncached tp. 12800/192
NIC/Mbps 4/3000
DS13v2 – 8 core 56 GB
ACU 210-250
Cached tp. 32000/256 (288)
Uncached tp. 25600/384
NIC/Mbps 8/6000
Esv3 – 8 core 64 GB
ACU 160-180
Cached tp. 16000/128 (200)
Uncached tp. 12800/192
NIC/Mbps 4/4000
Azure Storage
(remote storage)
Virtualization host
OsDisk DataDisk DataDisk
VM
VM NIC vSwitch Host NIC
BlobCache (local storage)
TempDisk
RAM cache
SSD cache
14. Families and series
Family Series Optimized for
General purpose B, Dsv3, Dv3, Dasv4,
Dav4, DSv2, Dv2, Av2,
DC, DCv2
Balanced CPU-to-memory ratio. Ideal for testing and development, small to medium
databases, and low to medium traffic web servers.
Compute
optimized
Fsv2 High CPU-to-memory ratio. Good for medium traffic web servers, network
appliances, batch processes, and application servers.
Memory
optimized
Esv3, Ev3, Easv4, Eav4,
Mv2, M, DSv2, Dv2
High memory-to-CPU ratio. Great for relational database servers, medium to large
caches, and in-memory analytics.
Storage optimized Lsv2 High disk throughput and IO ideal for Big Data, SQL, NoSQL databases, data
warehousing and large transactional databases.
GPU NC, NCv2, NCv3, ND,
NDv2 (Preview), NV,
NVv3, NVv4
Specialized virtual machines targeted for heavy graphic rendering and video editing,
as well as model training and inferencing (ND) with deep learning. Available with
single or multiple GPUs.
High performance
compute
HB, HBv2, HC, H Our fastest and most powerful CPU virtual machines with optional high-throughput
network interfaces (RDMA).
15. Support for Premium storage
D13 v2 Ds13 v2
CPU 8 8
RAM 56 56
Temporary Disk 400 112
Storage Premium No Yes
€ / hour 0,6401 0,6401
16. Size matters
Family, series and size of the VM also affects:
• Access to Premium Storage
• Computing power
• Disk throughput & number of data disks
• Cache and Temporary disk size & throughput
• Network bandwidth & Accelerated Network
DS12v2 – 4 core 28 GB
ACU 210-250
Cached tp. 16000/128 (144)
Uncached tp. 12800/192
NIC/Mbps 4/3000
DS13v2 – 8 core 56 GB
ACU 210-250
Cached tp. 32000/256 (288)
Uncached tp. 25600/384
NIC/Mbps 8/6000
Esv3 – 8 core 64 GB
ACU 160-180
Cached tp. 16000/128 (200)
Uncached tp. 12800/192
NIC/Mbps 4/4000
Azure Storage
(remote storage)
Virtualization host
OsDisk DataDisk DataDisk
VM
VM NIC vSwitch Host NIC
BlobCache (local storage)
TempDisk
RAM cache
SSD cache
17. Size matters
Family, series and size of the VM also affects:
• Access to Premium Storage
• Computing power
• Disk throughput & number of data disks
• Cache and Temporary disk size & throughput
• Network bandwidth & Accelerated Network
DS12v2 – 4 core 28 GB
ACU 210-250
Cached tp. 16000/128 (144)
Uncached tp. 12800/192
NIC/Mbps 4/3000
DS13v2 – 8 core 56 GB
ACU 210-250
Cached tp. 32000/256 (288)
Uncached tp. 25600/384
NIC/Mbps 8/6000
Esv3 – 8 core 64 GB
ACU 160-180
Cached tp. 16000/128 (200)
Uncached tp. 12800/192
NIC/Mbps 4/4000
Azure Storage
(remote storage)
Virtualization host
OsDisk DataDisk DataDisk
VM
VM NIC vSwitch Host NIC
BlobCache (local storage)
TempDisk
RAM cache
SSD cache
18. Azure Compute Unit
SKU Family ACU vCPU vCPU: Core
A0 50 1:1
A1 - A4 100 1:1
A5 - A7 100 1:1
A1_v2 - A8_v2 100 1:1
A2m_v2 - A8m_v2 100 1:1
A8 - A11 225* 1:1
D1 - D14 160 - 250 1:1
D1_v2 - D15_v2 210 - 250* 1:1
DS1 - DS14 160 - 250 1:1
DS1_v2 - DS15_v2 210 - 250* 1:1
D_v3 160 - 190* 2:1***
Ds_v3 160 - 190* 2:1***
E_v3 160 - 190* 2:1***
Es_v3 160 - 190* 2:1***
F2s_v2 - F72s_v2 195 - 210* 2:1***
F1 - F16 210 - 250* 1:1
F1s - F16s 210 - 250* 1:1
G1 - G5 180 - 240* 1:1
GS1 - GS5 180 - 240* 1:1
H 290 - 300* 1:1
HB 199 - 216** 1:1
HC 297 - 315* 1:1
L4s - L32s 180 - 240* 1:1
L8s_v2 - L80s_v2 150 - 175** 2:1
M 160 - 180 2:1***
https://docs.microsoft.com/en-us/azure/virtual-machines/acu
*ACUs use Intel® Turbo technology to increase CPU frequency and provide a
performance increase. The amount of the performance increase can vary
based on the VM size, workload, and other workloads running on the same
host.
**ACUs use AMD® Boost technology to increase CPU frequency and provide a
performance increase. The amount of the performance increase can vary
based on the VM size, workload, and other workloads running on the same
host.
***Hyper-threaded and capable of running nested virtualization
Exception: series
https://docs.microsoft.com/en-us/azure/virtual-machines/sizes-b-series-burstable
Suitable for fluctuating workloads
Offer a baseline
performance
Earn credits
Spend credits
to achieve top
performance
19. Size matters
Family, series and size of the VM also affects:
• Access to Premium Storage
• Computing power
• Disk throughput & number of data disks
• Cache and Temporary disk size & throughput
• Network bandwidth & Accelerated Network
DS12v2 – 4 core 28 GB
ACU 210-250
Cached tp. 16000/128 (144)
Uncached tp. 12800/192
NIC/Mbps 4/3000
DS13v2 – 8 core 56 GB
ACU 210-250
Cached tp. 32000/256 (288)
Uncached tp. 25600/384
NIC/Mbps 8/6000
Esv3 – 8 core 64 GB
ACU 160-180
Cached tp. 16000/128 (200)
Uncached tp. 12800/192
NIC/Mbps 4/4000
Azure Storage
(remote storage)
Virtualization host
OsDisk DataDisk DataDisk
VM
VM NIC vSwitch Host NIC
BlobCache (local storage)
TempDisk
RAM cache
SSD cache
20. Size matters
Family, series and size of the VM also affects:
• Access to Premium Storage
• Computing power
• Disk throughput & number of data disks
• Cache and Temporary disk size & throughput
• Network bandwidth & Accelerated Network
DS12v2 – 4 core 28 GB
ACU 210-250
Cached tp. 16000/128 (144)
Uncached tp. 12800/192
NIC/Mbps 4/3000
DS13v2 – 8 core 56 GB
ACU 210-250
Cached tp. 32000/256 (288)
Uncached tp. 25600/384
NIC/Mbps 8/6000
Esv3 – 8 core 64 GB
ACU 160-180
Cached tp. 16000/128 (200)
Uncached tp. 12800/192
NIC/Mbps 4/4000
Azure Storage
(remote storage)
Virtualization host
OsDisk DataDisk DataDisk
VM
VM NIC vSwitch Host NIC
BlobCache (local storage)
TempDisk
RAM cache
SSD cache
21. Size matters
Family, series and size of the VM also affects:
• Access to Premium Storage
• Computing power
• Disk throughput & number of data disks
• Cache and Temporary disk size & throughput
• Network bandwidth & Accelerated Network
DS12v2 – 4 core 28 GB
ACU 210-250
Cached tp. 16000/128 (144)
Uncached tp. 12800/192
NIC/Mbps 4/3000
DS13v2 – 8 core 56 GB
ACU 210-250
Cached tp. 32000/256 (288)
Uncached tp. 25600/384
NIC/Mbps 8/6000
Esv3 – 8 core 64 GB
ACU 160-180
Cached tp. 16000/128 (200)
Uncached tp. 12800/192
NIC/Mbps 4/4000
Azure Storage
(remote storage)
Virtualization host
OsDisk DataDisk DataDisk
VM
VM NIC vSwitch Host NIC
BlobCache (local storage)
TempDisk
RAM cache
SSD cache
22. Size matters
Family, series and size of the VM also affects:
• Access to Premium Storage
• Computing power
• Disk throughput & number of data disks
• Cache and Temporary disk size & throughput
• Network bandwidth & Accelerated Network
DS12v2 – 4 core 28 GB
ACU 210-250
Cached tp. 16000/128 (144)
Uncached tp. 12800/192
NIC/Mbps 4/3000
DS13v2 – 8 core 56 GB
ACU 210-250
Cached tp. 32000/256 (288)
Uncached tp. 25600/384
NIC/Mbps 8/6000
Esv3 – 8 core 64 GB
ACU 160-180
Cached tp. 16000/128 (200)
Uncached tp. 12800/192
NIC/Mbps 4/4000
Azure Storage
(remote storage)
Virtualization host
OsDisk DataDisk DataDisk
VM
VM NIC vSwitch Host NIC
BlobCache (local storage)
TempDisk
RAM cache
SSD cache
23. Size matters
Family, series and size of the VM also affects:
• Access to Premium Storage
• Computing power
• Disk throughput & number of data disks
• Cache and Temporary disk size & throughput
• Network bandwidth & Accelerated Network
DS12v2 – 4 core 28 GB
ACU 210-250
Cached tp. 16000/128 (144)
Uncached tp. 12800/192
NIC/Mbps 4/3000
DS13v2 – 8 core 56 GB
ACU 210-250
Cached tp. 32000/256 (288)
Uncached tp. 25600/384
NIC/Mbps 8/6000
Esv3 – 8 core 64 GB
ACU 160-180
Cached tp. 16000/128 (200)
Uncached tp. 12800/192
NIC/Mbps 4/4000
Azure Storage
(remote storage)
Virtualization host
OsDisk DataDisk DataDisk
VM
VM NIC vSwitch Host NIC
BlobCache (local storage)
TempDisk
RAM cache
SSD cache
24. Choosing the right VM
Family, series and size of the VM also affects:
• Access to Premium Storage
• Computing power
• Disk throughput & number of data disks
• Cache and Temporary disk size & throughput
• Network bandwidth & Accelerated Network
DS13-2v2 – 2 core 56 GB
Cached tp. 32000/256 (288)
Uncached tp. 25600/384
NIC/Mbps 8/6000
DS13-4v2 – 4 core 56 GB
Cached tp. 32000/256 (288)
Uncached tp. 25600/384
NIC/Mbps 8/6000
DS13v2 – 8 core 56 GB
Cached tp. 32000/256 (288)
Uncached tp. 25600/384
NIC/Mbps 8/6000
Need more of these, but have to contain
licensing costs???
Go for Constrained vCPU!
https://docs.microsoft.com/en-us/azure/virtual-machines/windows/constrained-vcpu
Azure Storage
(remote storage)
Virtualization host
OsDisk DataDisk DataDisk
VM
VM NIC vSwitch Host NIC
BlobCache (local storage)
TempDisk
RAM cache
SSD cache
25. Managed disks offering
0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000
4
8
16
32
64
128
256
512
1024
2048
4096
8192
16384
32767
IOPS
ProvisionedGB
IOPS per disk
0 100 200 300 400 500 600 700 800 900
4
8
16
32
64
128
256
512
1024
2048
4096
8192
16384
32767
MiB/sec
ProvisionedGB
Throughtput per disk Premium SSD Standard SSD Standard HDD
Standard Storage
• Standard HDD (Sxx)
• Standard SSD (Exx)
• Low-end workloads
• Best-effort performance
Premium Storage
• Premium SSD (Pxx)
• Hi-end workloads
• Provisioned performance
• Bursting when size ≤ 512 GB
• 5-10 ms avg. latency
Use appropriate cache
settings
• Read-Write
• Read-Only
• None
Stripe disks to achieve more
26. Managed disks offering
0 100 200 300 400 500 600 700 800 900
4
8
16
32
64
128
256
512
1024
2048
4096
8192
16384
32767
MiB/sec
ProvisionedGB
Throughtput per disk Premium SSD Standard SSD Standard HDD
0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000
4
8
16
32
64
128
256
512
1024
2048
4096
8192
16384
32767
IOPS
ProvisionedGB
IOPS per disk
Premium SSD Standard SSD Standard HDD
Standard Storage
• Standard HDD (Sxx)
• Standard SSD (Exx)
• Low-end workloads
• Best-effort performance
Premium Storage
• Premium SSD (Pxx)
• Hi-end workloads
• Provisioned performance
• Bursting when size ≤ 512 GB
• 5-10 ms avg. latency
Use appropriate cache
settings
• Read-Write
• Read-Only
• None
Stripe disks to achieve more
27. Managed disks offering
0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000
4
8
16
32
64
128
256
512
1024
2048
4096
8192
16384
32767
IOPS
ProvisionedGB
IOPS per disk
0 100 200 300 400 500 600 700 800 900
4
8
16
32
64
128
256
512
1024
2048
4096
8192
16384
32767
MiB/sec
ProvisionedGB
Throughtput per disk
Premium SSD Standard SSD Standard HDD
Standard Storage
• Standard HDD (Sxx)
• Standard SSD (Exx)
• Low-end workloads
• Best-effort performance
Premium Storage
• Premium SSD (Pxx)
• Hi-end workloads
• Provisioned performance
• Bursting when size ≤ 512 GB
• 5-10 ms avg. latency
Use appropriate cache
settings
• Read-Write
• Read-Only
• None
Stripe disks to achieve more
28. Managed disks offering
0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000
4
8
16
32
64
128
256
512
1024
2048
4096
8192
16384
32767
IOPS
ProvisionedGB
IOPS per disk
0 100 200 300 400 500 600 700 800 900
4
8
16
32
64
128
256
512
1024
2048
4096
8192
16384
32767
MiB/sec
ProvisionedGB
Throughtput per disk Premium SSD Standard SSD Standard HDD
Standard Storage
• Standard HDD (Sxx)
• Standard SSD (Exx)
• Low-end workloads
• Best-effort performance
Premium Storage
• Premium SSD (Pxx)
• Hi-end workloads
• Provisioned performance
• Bursting when size ≤ 512 GB
• 5-10 ms avg. latency
Use appropriate cache
settings
• Read-Write
• Read-Only
• None
Stripe disks to achieve more
29. Managed disks offering
0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000
4
8
16
32
64
128
256
512
1024
2048
4096
8192
16384
32767
IOPS
ProvisionedGB
IOPS per disk
0 100 200 300 400 500 600 700 800 900
4
8
16
32
64
128
256
512
1024
2048
4096
8192
16384
32767
MiB/sec
ProvisionedGB
Throughtput per disk Premium SSD Standard SSD Standard HDD
Standard Storage
• Standard HDD (Sxx)
• Standard SSD (Exx)
• Low-end workloads
• Best-effort performance
Use appropriate cache
settings
• Read-Write
• Read-Only
• None
Stripe disks to achieve more
Premium Storage
• Premium SSD (Pxx)
• Hi-end workloads
• Provisioned performance
• Bursting when size ≤ 512 GB
• 5-10 ms avg. latency
30. Managed disks offering
0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000
4
8
16
32
64
128
256
512
1024
2048
4096
8192
16384
32767
IOPS
ProvisionedGB
IOPS per disk
0 100 200 300 400 500 600 700 800 900
4
8
16
32
64
128
256
512
1024
2048
4096
8192
16384
32767
MiB/sec
ProvisionedGB
Throughtput per disk
Premium SSD Standard SSD Standard HDD
Standard Storage
• Standard HDD (Sxx)
• Standard SSD (Exx)
• Low-end workloads
• Best-effort performance
Premium Storage
• Premium SSD (Pxx)
• Hi-end workloads
• Provisioned performance
• Bursting when size ≤ 512 GB
• 5-10 ms avg. latency
Use appropriate cache
settings
• Read-Write
• Read-Only
• None
Stripe disks to achieve more
31. Managed disks offering
0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000
4
8
16
32
64
128
256
512
1024
2048
4096
8192
16384
32767
IOPS
ProvisionedGB
IOPS per disk
0 100 200 300 400 500 600 700 800 900
4
8
16
32
64
128
256
512
1024
2048
4096
8192
16384
32767
MiB/sec
ProvisionedGB
Throughtput per disk
Premium SSD Standard SSD Standard HDD
Standard Storage
• Standard HDD (Sxx)
• Standard SSD (Exx)
• Low-end workloads
• Best-effort performance
Premium Storage
• Premium SSD (Pxx)
• Hi-end workloads
• Provisioned performance
• Bursting when size ≤ 512 GB
• 5-10 ms avg. latency
Use appropriate cache
settings
• Read-Write
• Read-Only
• None
Stripe disks to achieve more
32. Ultra SSD
Disk Size (GiB) IOPS Cap Throughput Cap (MBps)
4 1,200 300
8 2,400 600
16 4,800 1,200
32 9,600 2,000
64 19,200 2,000
128 38,400 2,000
256 76,800 2,000
512 80,000 2,000
1,024-65,536
(sizes in this range increasing in increments of 1 TiB)
160,000 2,000
• Size, IOPS and MBps can be sized indipendently
• Less than 1 ms avg. Latency
• Performance can be modified dinamically
33. Azure Networking 101
Virtual Network
Private address space (RFC 1918)
10.0.0.0/16
Subnet 10.0.2.0/24
Subnet 10.0.1.0/24
NSG
NSG
UDR
UDR
VM NIC Public IP
37. High Availability
Zone 2
Zone 1
Zone 3
Frontend 2
Backend 2
Frontend 1
Backend 1
Availability zones SLA 99,99%
FD 1
UD 2
UD 0
UD 1
FD 0
UD 0
UD 1
UD 2
Frontend
AvSet
Backend
AvSet
Availability set SLA 99,95%
Frontend tier
Backend tier
47. Cost-saving tips
• Right-size your VM and storage
• Burstable?
• CPU-constrained VM?
• Leverage disk bursting on Premium SSD ≤ 512 GB
• Spot VM?
• Ephimeral OS disk?
• Save on licensing with Hybrid Benefit
• Acquire a reservation for long-running systems
• VM reserved instances
• Storage reservation
• Deallocate VMs when not needed
• Look for an equivalent PaaS service 🤣
48. Spot VMs
• Leverage Azure unused capacity at low rates
• VMs can be evicted when:
• Azure needs capacity
• The actual price is higher than your price cap
SPOT PRICE
49. Cost-saving tips
• Right-size your VM and storage
• Burstable?
• CPU-constrained VM?
• Leverage disk bursting on Premium SSD ≤ 512 GB
• Spot VM?
• Ephimeral OS disk?
• Save on licensing with Hybrid Benefit
• Acquire a reservation for long-running systems
• VM reserved instances
• Storage reservation
• Deallocate VMs when not needed
• Look for an equivalent PaaS service 🤣