Cosmos DB is Microsoft's flagship Serverless database service in the Azure cloud. This slide-deck, presented at the Nashville Azure Meetup event on 09/20/2018 covers the why and what of Cosmos DB was is meant to be a good segue into further detailed and advanced topics. The slide-deck presents 3 use-cases for using Cosmos DB in E-Commerce, Healthcare, and IoT. Stay Tuned!
In this technical overview of Azure Cosmos DB you will learn how easy it is to get started building planet-scale applications with Azure Cosmos DB. We’ll then take a closer look at important design aspects around global distribution, consistency, and server-side partitioning. How to model your data to fit your app’s needs using tools and APIs you love.
Presented at AI NEXTCon Seattle 1/17-20, 2018
http://aisea18.xnextcon.com
join our free online AI group with 50,000+ tech engineers to learn and practice AI technology, including: latest AI news, tech articles/blogs, tech talks, tutorial videos, and hands-on workshop/codelabs, on machine learning, deep learning, data science, etc..
Achieving Lakehouse Models with Spark 3.0Databricks
It’s very easy to be distracted by the latest and greatest approaches with technology, but sometimes there’s a reason old approaches stand the test of time. Star Schemas & Kimball is one of those things that isn’t going anywhere, but as we move towards the “Data Lakehouse” paradigm – how appropriate is this modelling technique, and how can we harness the Delta Engine & Spark 3.0 to maximise it’s performance?
Want to see a high-level overview of the products in the Microsoft data platform portfolio in Azure? I’ll cover products in the categories of OLTP, OLAP, data warehouse, storage, data transport, data prep, data lake, IaaS, PaaS, SMP/MPP, NoSQL, Hadoop, open source, reporting, machine learning, and AI. It’s a lot to digest but I’ll categorize the products and discuss their use cases to help you narrow down the best products for the solution you want to build.
In this technical overview of Azure Cosmos DB you will learn how easy it is to get started building planet-scale applications with Azure Cosmos DB. We’ll then take a closer look at important design aspects around global distribution, consistency, and server-side partitioning. How to model your data to fit your app’s needs using tools and APIs you love.
Presented at AI NEXTCon Seattle 1/17-20, 2018
http://aisea18.xnextcon.com
join our free online AI group with 50,000+ tech engineers to learn and practice AI technology, including: latest AI news, tech articles/blogs, tech talks, tutorial videos, and hands-on workshop/codelabs, on machine learning, deep learning, data science, etc..
Achieving Lakehouse Models with Spark 3.0Databricks
It’s very easy to be distracted by the latest and greatest approaches with technology, but sometimes there’s a reason old approaches stand the test of time. Star Schemas & Kimball is one of those things that isn’t going anywhere, but as we move towards the “Data Lakehouse” paradigm – how appropriate is this modelling technique, and how can we harness the Delta Engine & Spark 3.0 to maximise it’s performance?
Want to see a high-level overview of the products in the Microsoft data platform portfolio in Azure? I’ll cover products in the categories of OLTP, OLAP, data warehouse, storage, data transport, data prep, data lake, IaaS, PaaS, SMP/MPP, NoSQL, Hadoop, open source, reporting, machine learning, and AI. It’s a lot to digest but I’ll categorize the products and discuss their use cases to help you narrow down the best products for the solution you want to build.
Build Data Lakes & Analytics on AWS: Patterns & Best PracticesAmazon Web Services
With over 90% of today’s data generated in the last two years, the rate of data growth is showing no sign of slowing down. In this session, we step through the challenges and best practices for capturing data, understanding what data you own, driving insights, and predicting the future using AWS services. We frame the session and demonstrations around common pitfalls of building data lakes and how to successfully drive analytics and insights from data. We also discuss the architecture patterns brought together key AWS services, including Amazon S3, AWS Glue, Amazon Athena, Amazon Kinesis, and Amazon Machine Learning. Discover the real-world application of data lakes for roles including data scientists and business users.
Stephen Moon, Sr. Solutions Architect, Amazon Web Services
James Juniper, Solution Architect for the Geo-Community Cloud, Natural Resources Canada
This session will begin with an introduction to non-relational (NoSQL) databases and compare them with relational (SQL) databases. Learn the fundamentals of Amazon DynamoDB, a fully managed NoSQL database service, and see the DynamoDB console first-hand. See a walk-through demo of building a serverless web application using this high-performance key-value and JSON document store.
In this presentation, we will do assess the on-premises environment and determining what workloads and databases are ready to make the move and what can you do to improve their Azure readiness while reducing downtime during the migration. Planning and assessment plays a critical role in moving to the cloud. We would see wide range of resources and tools to get an assessment completed with ease while identifying workload dependencies with practical tips and tricks focusing on sizing and costs. And finally, we’ll assess the SQL instances and identify their readiness for Azure as well.
This is part 1 of the Azure storage series, where we will build our understanding of Azure Storage, and will also learn about the storage data services, and the types of Azure Storage. Last but not least, we will also touch base on securing storage accounts
In the second part, we will continue with our demo on creating and utilizing the Azure Storage.
Azure SQL Database Managed Instance is a new flavor of Azure SQL Database that is a game changer. It offers near-complete SQL Server compatibility and network isolation to easily lift and shift databases to Azure (you can literally backup an on-premise database and restore it into a Azure SQL Database Managed Instance). Think of it as an enhancement to Azure SQL Database that is built on the same PaaS infrastructure and maintains all it's features (i.e. active geo-replication, high availability, automatic backups, database advisor, threat detection, intelligent insights, vulnerability assessment, etc) but adds support for databases up to 35TB, VNET, SQL Agent, cross-database querying, replication, etc. So, you can migrate your databases from on-prem to Azure with very little migration effort which is a big improvement from the current Singleton or Elastic Pool flavors which can require substantial changes.
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. I’ll include use cases so you can see what approach will work best for your big data needs.
ACID ORC, Iceberg, and Delta Lake—An Overview of Table Formats for Large Scal...Databricks
The reality of most large scale data deployments includes storage decoupled from computation, pipelines operating directly on files and metadata services with no locking mechanisms or transaction tracking. For this reason attempts at achieving transactional behavior, snapshot isolation, safe schema evolution or performant support for CRUD operations has always been marred with tradeoffs.
This talk will focus on technical aspects, practical capabilities and the potential future of three table formats that have emerged in recent years as solutions to the issues mentioned above – ACID ORC (in Hive 3.x), Iceberg and Delta Lake. To provide a richer context, a comparison between traditional databases and big data tools as well as an overview of the reasons for the current state of affairs will be included.
After the talk, the audience is expected to have a clear understanding of the current development trends in large scale table formats, on the conceptual and practical level. This should allow the attendees to make better informed assessments about which approaches to data warehousing, metadata management and data pipelining they should adapt in their organizations.
More and more organizations are moving their ETL workloads to a Hadoop based ELT grid architecture. Hadoop`s inherit capabilities, especially it`s ability to do late binding addresses some of the key challenges with traditional ETL platforms. In this presentation, attendees will learn the key factors, considerations and lessons around ETL for Hadoop. Areas such as pros and cons for different extract and load strategies, best ways to batch data, buffering and compression considerations, leveraging HCatalog, data transformation, integration with existing data transformations, advantages of different ways of exchanging data and leveraging Hadoop as a data integration layer. This is an extremely popular presentation around ETL and Hadoop.
Globally Distributed Modern Apps using Azure Cosmos DB and Azure FunctionsMohammad Asif
In this session we discussed ,how we can develop modern applications using Cosmos DB & Azure Functions. Cosmos DB’s capabilities and Azure Function’s ability to trigger logic in real time without the need to manage any servers.
Modeling data and best practices for the Azure Cosmos DB.Mohammad Asif
Azure Cosmos DB is Microsoft's globally distributed, multi-model database service. In this session we covered ,modeling of data using NOSQL cosmos database and how it's helpful for distributed application to maintain high availability ,scaling in multiple region and throughput.
Build Data Lakes & Analytics on AWS: Patterns & Best PracticesAmazon Web Services
With over 90% of today’s data generated in the last two years, the rate of data growth is showing no sign of slowing down. In this session, we step through the challenges and best practices for capturing data, understanding what data you own, driving insights, and predicting the future using AWS services. We frame the session and demonstrations around common pitfalls of building data lakes and how to successfully drive analytics and insights from data. We also discuss the architecture patterns brought together key AWS services, including Amazon S3, AWS Glue, Amazon Athena, Amazon Kinesis, and Amazon Machine Learning. Discover the real-world application of data lakes for roles including data scientists and business users.
Stephen Moon, Sr. Solutions Architect, Amazon Web Services
James Juniper, Solution Architect for the Geo-Community Cloud, Natural Resources Canada
This session will begin with an introduction to non-relational (NoSQL) databases and compare them with relational (SQL) databases. Learn the fundamentals of Amazon DynamoDB, a fully managed NoSQL database service, and see the DynamoDB console first-hand. See a walk-through demo of building a serverless web application using this high-performance key-value and JSON document store.
In this presentation, we will do assess the on-premises environment and determining what workloads and databases are ready to make the move and what can you do to improve their Azure readiness while reducing downtime during the migration. Planning and assessment plays a critical role in moving to the cloud. We would see wide range of resources and tools to get an assessment completed with ease while identifying workload dependencies with practical tips and tricks focusing on sizing and costs. And finally, we’ll assess the SQL instances and identify their readiness for Azure as well.
This is part 1 of the Azure storage series, where we will build our understanding of Azure Storage, and will also learn about the storage data services, and the types of Azure Storage. Last but not least, we will also touch base on securing storage accounts
In the second part, we will continue with our demo on creating and utilizing the Azure Storage.
Azure SQL Database Managed Instance is a new flavor of Azure SQL Database that is a game changer. It offers near-complete SQL Server compatibility and network isolation to easily lift and shift databases to Azure (you can literally backup an on-premise database and restore it into a Azure SQL Database Managed Instance). Think of it as an enhancement to Azure SQL Database that is built on the same PaaS infrastructure and maintains all it's features (i.e. active geo-replication, high availability, automatic backups, database advisor, threat detection, intelligent insights, vulnerability assessment, etc) but adds support for databases up to 35TB, VNET, SQL Agent, cross-database querying, replication, etc. So, you can migrate your databases from on-prem to Azure with very little migration effort which is a big improvement from the current Singleton or Elastic Pool flavors which can require substantial changes.
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. I’ll include use cases so you can see what approach will work best for your big data needs.
ACID ORC, Iceberg, and Delta Lake—An Overview of Table Formats for Large Scal...Databricks
The reality of most large scale data deployments includes storage decoupled from computation, pipelines operating directly on files and metadata services with no locking mechanisms or transaction tracking. For this reason attempts at achieving transactional behavior, snapshot isolation, safe schema evolution or performant support for CRUD operations has always been marred with tradeoffs.
This talk will focus on technical aspects, practical capabilities and the potential future of three table formats that have emerged in recent years as solutions to the issues mentioned above – ACID ORC (in Hive 3.x), Iceberg and Delta Lake. To provide a richer context, a comparison between traditional databases and big data tools as well as an overview of the reasons for the current state of affairs will be included.
After the talk, the audience is expected to have a clear understanding of the current development trends in large scale table formats, on the conceptual and practical level. This should allow the attendees to make better informed assessments about which approaches to data warehousing, metadata management and data pipelining they should adapt in their organizations.
More and more organizations are moving their ETL workloads to a Hadoop based ELT grid architecture. Hadoop`s inherit capabilities, especially it`s ability to do late binding addresses some of the key challenges with traditional ETL platforms. In this presentation, attendees will learn the key factors, considerations and lessons around ETL for Hadoop. Areas such as pros and cons for different extract and load strategies, best ways to batch data, buffering and compression considerations, leveraging HCatalog, data transformation, integration with existing data transformations, advantages of different ways of exchanging data and leveraging Hadoop as a data integration layer. This is an extremely popular presentation around ETL and Hadoop.
Globally Distributed Modern Apps using Azure Cosmos DB and Azure FunctionsMohammad Asif
In this session we discussed ,how we can develop modern applications using Cosmos DB & Azure Functions. Cosmos DB’s capabilities and Azure Function’s ability to trigger logic in real time without the need to manage any servers.
Modeling data and best practices for the Azure Cosmos DB.Mohammad Asif
Azure Cosmos DB is Microsoft's globally distributed, multi-model database service. In this session we covered ,modeling of data using NOSQL cosmos database and how it's helpful for distributed application to maintain high availability ,scaling in multiple region and throughput.
Solved: Your Most Dreaded Test Environment Management ChallengesDevOps.com
Modern application delivery pipelines rely on series of increasingly complex test environments. Manual processes and ad-hoc management typically lead to misconfigured environments, scheduling conflicts, and project delays. You know automation and transitioning resources to the cloud can help, but don’t know where to start and unclear how to prove the value.
Join Amazon Web Services (AWS) and Plutora in this joint presentation on managing test environments and transitioning them to the cloud. Learn secrets about
Why you need a single source of truth to smooth out scheduling kinks.
How to improve configuration tracking and management to enhance validation efforts.
The best way to manage the complexity of large-scale test environments.
How to reduce costs and eliminate conflicts by identifying and moving environments to the cloud.
Serverless Analytics with Amazon Redshift Spectrum, AWS Glue, and Amazon Quic...Amazon Web Services
Learning Objectives:
- Understand how to build a serverless big data solution quickly and easily
- Learn how to discover and prepare all your data for analytics
- Learn how to query and visualize analytics on all your data to create actionable insights
Join this workshop to understand the core concepts of “Cloud Computing” and how businesses around the world are running the infrastructure that supports their websites to lower costs, improve time-to-market, and enable rapid scalability matching resource to demands of users. Whether you are an enterprise looking for IT innovation, agility and resiliency or small and medium business who wants to accelerate growth without a big upfront investment in cash or time for technology, the AWS Cloud provides a complete set of services at zero upfront costs which are available with a few clicks and within minutes.
Best Practices Scaling Web Application Up to Your First 10 Million UsersAmazon Web Services
If you have a new web application and want to use cloud computing, you might be asking yourself, "Where do I start?" Cloud computing gives you a number of advantages, such as the ability to scale your web application on demand. Join us in this webinar to understand best practices for scaling your resources from zero to millions of users. We show you how to best combine different AWS services, how to make smarter decisions for architecting your application, and how to scale your infrastructure in the cloud.
Samedi SQL Québec - La plateforme data de AzureMSDEVMTL
6 juin 2015
Samedi SQL à Québec
Session 3 - Data (SQL Azure, Table et Blob Storage) (Eric Moreau)
SQL Azure est une base de données relationnelle en tant que service, Azure Storage permet de stocker et d'extraire de gros volumes de données non structurées (par exemple, des documents et fichiers multimédias) avec les objets blob Azure ; de données NoSql structurées avec les tables Azure ; de messages fiables avec les files d'attente Azure.
Aplicaciones a gran escala: Cómo servir a millones de usuariosAmazon Web Services
(Diapositivas de presentación son en inglés.)
¿Cómo podemos hacer escalar nuestras aplicaciones? Escalar aplicaciones no es un tarea sencilla ya que existen múltiples variables a analizar (red, servidores, almacenamiento, aplicación, arquitectura, cdn, etc.), así como diferentes alternativas para construir y operar plataformas a gran escala. En esta sesión se cubrirá el recorrido de una plataforma que pueda dar cobertura desde un usuario hasta millones de usuarios.
This is a presentation I delivered at CodeMash 2.0.1.0 dealing with lessons learned while building an application for handling the post-processing of scientific data using the Windows Azure platform.
Azure Cosmos DB - NoSQL Strikes Back (An introduction to the dark side of you...Andre Essing
A long time ago in a database far, far away...
SQL was the only option to save vast amounts of application data for a long period of time. There were always some rebellion activities, to overcome the SQL Empire, which brought a new hope, but all other ways of storing data were never more than a phantom menace.
Now Cosmos DB awakens and is ready for the revenge of the NoSQL.
During this talk, we will have a look at what Azure Cosmos DB is, what you can achieve with its possibilities and how to use it in a galactic environment of data and applications.
Join me and find your way to the right solution for your application.
May the data be with you!
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
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/
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
11. Azure Cosmos DB: WHAT?
Microsoft’s PaaS
Database Service
NOSQL
NoSQL
Data Store
Serverless
On-Premise
Cloud
Relational
Data
{}
JSON
Server
Infrastructure
Service
Endpoint
12. Azure Cosmos DB: WHAT?
Multi-Model
Database
Support for
multiple
database APIs
51. Cosmos DB Resource Model
Account
https://woodgrove.documents.azure.com
- R e pr esent s t h e C o s mo s D B I n s t anc e
- E x po s es A c c o u nt -lev el S e t t in gs
o G l o b a l d i s t r i b u t i o n
o C o n s i s t e n c y L e v e l s
o F i r e w a l l
o K e y s
52. Cosmos DB Resource Model
Account
https://woodgrove.documents.azure.com
Database
USA
Database
EUR
Database
AUS
- O n e o r m o r e d a t abas es i n e a c h a c c o u nt
- A c c o u nt -lev el S e t t in gs a p p lied t o e a c h a c c o u nt
o G l o b a l d i s t r i b u t i o n
o C o n s i s t e n c y L e v e l s
o F i r e w a l l
o K e y s
53. Cosmos DB Resource Model
Account
https://woodgrove.documents.azure.com
Database
USA
Database
EUR
Database
AUS
Collection
Customer
Collection
Account
Collection
Transaction
- S i m il ar t o a t ab l e
- R e pr esent s a l o g ic al e n t it y
54. Cosmos DB Resource Model
Account
https://woodgrove.documents.azure.com
Database
USA
Database
EUR
Database
AUS
Collection
Customer
Collection
Account
Collection
Transaction
Items
} E a c h i t em r e pr esent s
a J S O N r e c o r d
55. Cosmos DB Partitioning & Throughput
Account
https://woodgrove.documents.azure.com
Database
USA
Throughput
60. Cosmos DB Throughput
Example Item Size: 1 kb
Reads per sec: 500
Writes per sec: 500
Request Units:
(500 x 1) + (500 x 5) = 3,000 RUs
Request Unit Calculator: https://www.documentdb.com/capacityplanner
64. Cosmos DB Consistency Levels
One writer; multiple readers
Read Latency is acceptable, but data
staleness is NOT.
One version of the truth required for
all readers
65. Cosmos DB Consistency Levels
A certain known degree of staleness
is acceptable
Writes are fast, reads slightly slower
66. Cosmos DB Consistency Levels
Reads lag behind writes by most
k prefixes or t interval
78. Cosmos DB Change Feed
Cosmos DB
Change Feed
Consumer 1
Consumer 2
Consumer 3
79. Cosmos DB Gremlin API
Enables use of graph data model
Allows storage of Vertices, Edges, and Properties
Ideal for highly-connected data
Data queried using Gremlin queries
80. Cosmos DB Use Cases
E-Commerce
Healthcare
IoT
Operational
Analytical
Streaming
82. Use Case: E-Commerce
Region A Region B
Azure
Traffic Manager
App hosted
in Region B
App hosted
in Region A
Cosmos DB
in Region B
Cosmos DB
in Region A
Geo-Distribution