For our next ArcReady, we will explore a topic on everyone’s mind: Cloud computing. Several industry companies have announced cloud computing services . In October 2008 at the Professional Developers Conference, Microsoft announced the next phase of our Software + Services vision: the Azure Services Platform. The Azure Services Platforms provides a wide range of internet services that can be consumed from both on premises environments or the internet.
Session 1: Cloud Services
In our first session we will explore the current state of cloud services. We will then look at how applications should be architected for the cloud and explore a reference application deployed on Windows Azure. We will also look at the services that can be built for on premise application, using .NET Services. We will also address some of the concerns that enterprises have about cloud services, such as regulatory and compliance issues.
Session 2: The Azure Platform
In our second session we will take a slightly different look at cloud based services by exploring Live Mesh and Live Services. Live Mesh is a data synchronization client that has a rich API to build applications on. Live services are a collection of APIs that can be used to create rich applications for your customers. Live Services are based on internet standard protocols and data formats.
For our next ArcReady, we will explore a topic on everyone’s mind: Cloud computing. Several industry companies have announced cloud computing services . In October 2008 at the Professional Developers Conference, Microsoft announced the next phase of our Software + Services vision: the Azure Services Platform. The Azure Services Platforms provides a wide range of internet services that can be consumed from both on premises environments or the internet.
Session 1: Cloud Services
In our first session we will explore the current state of cloud services. We will then look at how applications should be architected for the cloud and explore a reference application deployed on Windows Azure. We will also look at the services that can be built for on premise application, using .NET Services. We will also address some of the concerns that enterprises have about cloud services, such as regulatory and compliance issues.
Session 2: The Azure Platform
In our second session we will take a slightly different look at cloud based services by exploring Live Mesh and Live Services. Live Mesh is a data synchronization client that has a rich API to build applications on. Live services are a collection of APIs that can be used to create rich applications for your customers. Live Services are based on internet standard protocols and data formats.
--session donnée lors du SQL Saturday Lisbon 2015--
Data Management Gateway (and also AS Connector) is what make modern Microsoft BI stack hybrid. Power BI and Azure Data Factory use that component to interact with On-Prem Data assets.
That session is a Deep dive into the DMG and the hybrid architecture involved by Power BI and ADF. How does it work ? Security, Firewall, Certificates, Multiple gateways, Admin delegation, Scale out, Disaster Recovery…. All that topics will be covered during that technical session.
Join us for a deep dive into Windows Azure. We’ll start with a developer-focused overview of this brave new platform and the cloud computing services that can be used either together or independently to build amazing applications. As the day unfolds, we’ll explore data storage, SQL Azure™, and the basics of deployment with Windows Azure. Register today for these free, live sessions in your local area.
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.
Web Cast sobre SQL Server Data Services.
Saludos,
Eduardo Castro – Microsoft SQL Server MVP
http://mswindowscr.org
http://comunidadwindows.org
Costa Rica
This slide deck was provided by Microsoft for a crash course on Microsoft Azure at the Saint Louis Cloud Camp.
If you need a quick high level introduction to Azure and/or the cloud in general, this presentation would serve as a good template.
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.
McGraw-Hill Optimizes Analytics Workloads with DatabricksAmazon Web Services
Using Databricks, McGraw-Hill securely transformed itself from a collection of data silos with limited access to data and minimal collaboration to an organization with democratized access to data and machine learning. This ultimately enables its data teams to rapidly identify usage patterns predicting student performance, so they can make timely enhancements to the software that proactively guide at-risk students through the course material.
Join our webinar to learn:
- How a cloud-based unified analytics platform can help your company perform analytics faster, at lower cost.
- How to mitigate challenges presented by data silos so data science teams can collaborate effectively.
- How to implement data analytics infrastructure to put models into production quickly
(ARC311) Decoding The Genetic Blueprint Of Life On A Cloud EcosystemAmazon Web Services
Thermo Fisher Scientific, a world leader in biotechnology, has built a new polymerase chain reaction (PCR) system for DNA sequencing. Designed for low- to midlevel throughput laboratories that conduct real time PCR experiments, the system runs on individual QuantStudio devices. These devices are connected to Thermo Fisher’s cloud computing platform, which is built on AWS using Amazon EC2, Amazon DynamoDB, and Amazon S3. With this single platform, applied and clinical researchers can learn, analyze, share, collaborate, and obtain support. Researchers worldwide can now collaborate online in real time and access their data wherever and whenever necessary. Laboratories can also share experimental conditions and results with their partners while providing a uniform experience for every user and helping to minimize training and errors. The net result is increased collaboration, faster time to market, fewer errors, and lower cost. We have architected a solution that uses Amazon EMR, DynamoDB, Amazon Elasticache, and S3. In this presentation, we share our architecture, lessons learned, best design patterns for NoSQL, strategies for leveraging EMR with DynamoDB, and a flexible solution that our scientist use. We also share our next step in architecture evolution.
--session donnée lors du SQL Saturday Lisbon 2015--
Data Management Gateway (and also AS Connector) is what make modern Microsoft BI stack hybrid. Power BI and Azure Data Factory use that component to interact with On-Prem Data assets.
That session is a Deep dive into the DMG and the hybrid architecture involved by Power BI and ADF. How does it work ? Security, Firewall, Certificates, Multiple gateways, Admin delegation, Scale out, Disaster Recovery…. All that topics will be covered during that technical session.
Join us for a deep dive into Windows Azure. We’ll start with a developer-focused overview of this brave new platform and the cloud computing services that can be used either together or independently to build amazing applications. As the day unfolds, we’ll explore data storage, SQL Azure™, and the basics of deployment with Windows Azure. Register today for these free, live sessions in your local area.
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.
Web Cast sobre SQL Server Data Services.
Saludos,
Eduardo Castro – Microsoft SQL Server MVP
http://mswindowscr.org
http://comunidadwindows.org
Costa Rica
This slide deck was provided by Microsoft for a crash course on Microsoft Azure at the Saint Louis Cloud Camp.
If you need a quick high level introduction to Azure and/or the cloud in general, this presentation would serve as a good template.
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.
McGraw-Hill Optimizes Analytics Workloads with DatabricksAmazon Web Services
Using Databricks, McGraw-Hill securely transformed itself from a collection of data silos with limited access to data and minimal collaboration to an organization with democratized access to data and machine learning. This ultimately enables its data teams to rapidly identify usage patterns predicting student performance, so they can make timely enhancements to the software that proactively guide at-risk students through the course material.
Join our webinar to learn:
- How a cloud-based unified analytics platform can help your company perform analytics faster, at lower cost.
- How to mitigate challenges presented by data silos so data science teams can collaborate effectively.
- How to implement data analytics infrastructure to put models into production quickly
(ARC311) Decoding The Genetic Blueprint Of Life On A Cloud EcosystemAmazon Web Services
Thermo Fisher Scientific, a world leader in biotechnology, has built a new polymerase chain reaction (PCR) system for DNA sequencing. Designed for low- to midlevel throughput laboratories that conduct real time PCR experiments, the system runs on individual QuantStudio devices. These devices are connected to Thermo Fisher’s cloud computing platform, which is built on AWS using Amazon EC2, Amazon DynamoDB, and Amazon S3. With this single platform, applied and clinical researchers can learn, analyze, share, collaborate, and obtain support. Researchers worldwide can now collaborate online in real time and access their data wherever and whenever necessary. Laboratories can also share experimental conditions and results with their partners while providing a uniform experience for every user and helping to minimize training and errors. The net result is increased collaboration, faster time to market, fewer errors, and lower cost. We have architected a solution that uses Amazon EMR, DynamoDB, Amazon Elasticache, and S3. In this presentation, we share our architecture, lessons learned, best design patterns for NoSQL, strategies for leveraging EMR with DynamoDB, and a flexible solution that our scientist use. We also share our next step in architecture evolution.
There are several points which architects and engineers should take into account when building new applications (or redesigning existing) in order to archive high elasticity on AWS. The presentation will reveal some best practices related to elasticity, redundancy and cost-effectiveness of AWS learned from the past.
Architecting Web Applications for the Cloud - Design Principles and Practical...Adnene Guabtni
This presentation provides an overview of the best practice and design principles for architecting highly scalable and highly available web applications on Amazon Web Services (AWS) cloud. Architecting web applications for the cloud requires a deep understanding of the true benefits of cloud computing and the implementation of 8 design principles for AWS.
AWS June 2016 Webinar Series - Best Practices for Architecting Cloud Backup a...Amazon Web Services
Cloud backup is an ideal application for taking advantage of the low cost and extreme scale of cloud storage. Traditional tape and disk solutions require up-front purchase, regular capacity management and ongoing maintenance. This webinar will help you understand cloud backup options, and how they fit into your organizations. We will also share some overall design considerations.
Learning Objectives:
Learn how to choose a storage platform (object, block or file)
Learn how to optimize your storage tier (S3, SIA or Glacier)
Learn how to ingest data into AWS storage (Direct Connect et al)
Understand the AWS storage partner options
Learn about the design lifecycle management policies, and archive and compliance considerations
This presentation shows how Nirmata's multi-cloud container management solution can manage application SLAs across across AWS Spot and On-Demand instances.
Microservice are elastic and resilient by design. Application containers provide AWS Spot Instances provide market pricing on infrastructure at up to 90% cost savings. So, why not combine these trends, and using Nirmata's scheduling and application orchestration, and get DevOps agility and cost savings!
State, Local and Education customers are using the AWS cloud to enable faster disaster recovery of their mission critical IT systems without incurring the infrastructure expense of a second physical site. Join us for an informative webinar on how AWS cloud supports many popular disaster recovery (DR) architectures from “pilot light” environments that are ready to scale up at a moment’s notice to “hot standby” environments that enable rapid failover. With infrastructure centers in 10 regions around the world, AWS provides a set of cloud-based DR services that enable rapid recovery of your IT infrastructure and data.
AWS Webcast - High Availability SQL Server with Amazon RDSAmazon Web Services
Amazon RDS for Microsoft SQL Server makes it easy to set up, operate, and scale SQL Server deployments in the cloud. Amazon RDS Multi-AZ deployments provide enhanced availability and durability, making them a natural fit for production database workloads.
Review this webinar to learn more about this easy way to achieve highly available operation of SQL Server. When you provision a Multi-AZ DB Instance, Amazon RDS automatically creates a primary DB Instance and synchronously replicates the data to a standby instance in a different Availability Zone (AZ). Each AZ runs on its own physically distinct, independent infrastructure, and is engineered to be highly reliable. Amazon RDS performs an automatic failover to the standby, with no administrator intervention required, so that your application can resume database operations as soon as the failover is complete.
AWS Solutions Architect Matt Tavis reviews high availability features for Microsoft Windows Server and SQL Server running on the AWS cloud. Windows Server Failover Clustering (WSFC) and SQL AlwaysOn Availability Groups are part of the underpinnings for many enterprise-class solutions, including Microsoft SharePoint and .NET applications. We will walk through an example implementation and share templates and sample code to help you deploy high availability architectures. Please review this virtual event geared for a technical audience.
Best Practices for Architecting Cloud Backup and Recovery Solutions - AWS Mar...Amazon Web Services
Cloud backup is an ideal application for taking advantage of the low cost and extreme scale of cloud storage. Traditional tape and disk solutions require up-front purchase, regular capacity management and ongoing maintenance.
This webinar will help you understand cloud backup options, and how they fit into your organizations. We will also share some overall design considerations.
Learning Objectives:
• Learn how to choose a storage platform (object, block or file)
• Learn how to optimize your storage tier (S3, SIA or Glacier)
• Learn how to ingest data into AWS storage (Direct Connect et al)
• Understand the AWS storage partner options
• Learn about the design lifecycle management policies, and archive and compliance considerations
Who Should Attend:
• Developers, architects, storage and backup managers
AWS provides a platform that is ideally suited for building highly available systems, enabling you to build reliable, affordable, fault-tolerant systems that operate with a minimal amount of human interaction. This session covers many of the high-availability and fault-tolerance concepts and features of the various services that you can use to build highly reliable and highly available applications in the AWS Cloud: architectures involving multiple Availability Zones, including EC2 best practices and RDS Multi-AZ deployments; loosely coupled and self-healing systems involving SQS and Auto Scaling; networking best practices for high availability, including Elastic IP addresses, load balancing, and DNS; leveraging services that inherently are built with high-availability and fault tolerance in mind, including S3, Elastic Beanstalk and more.
Designing a Scalable Twitter - Patterns for Designing Scalable Real-Time Web ...Nati Shalom
Twitter is a good example for next generation real-time web applications, but building such an application imposes challenges such as handling an every growing volume of tweets and responses, as well as a large number of concurrent users, who continually *listen* for tweets from users (or topics) they follow. During this session we will review some of the key design principles addressing these challenges, including alternatives *NoSQL* alternatives and blackboard patterns. We will be using Twitter as a use case, while learning how to apply these to any real-time we application
Running a Megasite on Microsoft Technologiesgoodfriday
MySpace and Microsoft.com are two of the most-visited Web sites on the planet. Come to this session to hear about lessons learned using Microsoft technologies to run Web applications on a massive scale. Representatives from Microsoft.com talk about lessons learned using an all-Microsoft datacenter. Representatives from MySpace talk about the realities of using Microsoft technologies in a scalable, federated environment using SQL Server 2005, .NET 2.0 and IIS 6 on Windows Server 2003 64-bit editions. This session features an open Q&A with a panel of technical managers and engineers from MySpace and Microsoft.com.
Solving enterprise challenges through scale out storage & big compute finalAvere Systems
Google Cloud Platform, Avere Systems, and Cycle Computing experts will share best practices for advancing solutions to big challenges faced by enterprises with growing compute and storage needs. In this “best practices” webinar, you’ll hear how these companies are working to improve results that drive businesses forward through scalability, performance, and ease of management.
The slides were from a webinar presented January 24, 2017. The audience learned:
- How enterprises are using Google Cloud Platform to gain compute and storage capacity on-demand
- Best practices for efficient use of cloud compute and storage resources
- Overcoming the need for file systems within a hybrid cloud environment
- Understand how to eliminate latency between cloud and data center architectures
- Learn how to best manage simulation, analytics, and big data workloads in dynamic environments
- Look at market dynamics drawing companies to new storage models over the next several years
Presenters communicated a foundation to build infrastructure to support ongoing demand growth.
Building Analytic Apps for SaaS: “Analytics as a Service”Amazon Web Services
TIBCO Jaspersoft® for AWS is a business intelligence suite that helps you deliver stunning interactive reports and dashboards inside your app that make it easy for your customers to get answers. Purpose-built for AWS, our reporting and analytics server quickly and easily connects to Amazon Relational Database Service (RDS), Amazon Redshift, and Amazon EMR. It includes ad-hoc reporting, dashboards, data analysis, data visualization, and data blending. In less than 10 minutes, you can be analyzing and reporting on your data. You get a full Cloud BI server starting at less than $1/hour, with no user or data limits and no additional fees.
This webinar deck shows how embeddable analytics with TIBCO Jaspersoft for AWS gives you the power to create the experience your end users demand and how to scale and manage that experience across your customer base with AWS.
DM Radio Webinar: Adopting a Streaming-Enabled ArchitectureDATAVERSITY
Architecture matters. That's why today's innovators are taking a hard look at streaming data, an increasingly attractive option that can transform business in several ways: replacing aging data ingestion techniques like ETL; solving long-standing data quality challenges; improving business processes ranging from sales and marketing to logistics and procurement; or any number of activities related to accelerating data warehousing, business intelligence and analytics.
Register for this DM Radio Deep Dive Webinar to learn how streaming data can rejuvenate or supplant traditional data management practices. Host Eric Kavanagh will explain how streaming-first architectures can relieve data engineers from time-consuming, error-prone processes, ideally bidding farewell to those unpleasant batch windows. He'll be joined by Kevin Petrie of Attunity, who will explain why (with real-world story successes) streaming data solutions can keep the business fueled with trusted data in a timely, efficient manner for improved business outcomes.
Deep-dive into Microservices Patterns with Replication and Stream Analytics
Target Audience: Microservices and Data Architects
This is an informational presentation about microservices event patterns, GoldenGate event replication, and event stream processing with Oracle Stream Analytics. This session will discuss some of the challenges of working with data in a microservices architecture (MA), and how the emerging concept of a “Data Mesh” can go hand-in-hand to improve microservices-based data management patterns. You may have already heard about common microservices patterns like CQRS, Saga, Event Sourcing and Transaction Outbox; we’ll share how GoldenGate can simplify these patterns while also bringing stronger data consistency to your microservice integrations. We will also discuss how complex event processing (CEP) and stream processing can be used with event-driven MA for operational and analytical use cases.
Business pressures for modernization and digital transformation drive demand for rapid, flexible DevOps, which microservices address, but also for data-driven Analytics, Machine Learning and Data Lakes which is where data management tech really shines. Join us for this presentation where we take a deep look at the intersection of microservice design patterns and modern data integration tech.
Deck delivered at the Underground event at PDC09; with a 2-minute overview on Azure, and then demo on some parts of the KBB Azure project that was highlighted during the keynote presentation at PDC09
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
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.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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
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.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
2. > Introduction Size matters Facebook (2009) +200B pageviews /month >3.9T feed actions /day +300M active users >1B chat mesgs /day 100M search queries /day >6B minutes spent /day (ranked #2 on Internet) +20B photos, +2B/month growth 600,000 photos served /sec 25TB log data /day processed thru Scribe 120M queries /sec on memcache Twitter (2009) 600 requests /sec avg 200-300 connections /sec; peak at 800 MySQL handles 2,400 requests /sec 30+ processes for handling odd jobs process a request in 200 milliseconds in Rails average time spent in the database is 50-100 milliseconds +16 GB of memcached Google (2007) +20 petabytes of data processed /day by +100K MapReduce jobs 1 petabyte sort took ~6 hours on ~4K servers replicated onto ~48K disks +200 GFS clusters, each at 1-5K nodes, handling +5 petabytes of storage ~40 GB /sec aggregate read/write throughput across the cluster +500 servers for each search query < 500ms >1B views / day on Youtube (2009) Myspace(2007) 115B pageviews /month 5M concurrent users @ peak +3B images, mp3, videos +10M new images/day 160 Gbit/sec peak bandwidth Flickr (2007) +4B queries /day +2B photos served ~35M photos in squid cache ~2M photos in squid’s RAM 38k req/sec to memcached (12M objects) 2 PB raw storage +400K photos added /day Source: multiple articles, High Scalability http://highscalability.com/
3. > Introduction Cloud levels the playing field 2007 founded by 6 people 2008 $29M funding from VC 2009 revenue - $270M $180M funding from Digital Sky Technologies 2010 1,000+ employees $300M funding from Google and Softbank Active unique players 75M monthly 60M daily 1M daily 4 days after launch 10M after 60 days Hosted in Amazon Web Services 12,000 EC2 nodes 3 Gigabits/sec of traffic between FarmVille and Facebook (at peak) caching cluster serves another 1.5 Gigabits/sec to the application Source: “How FarmVille Scales to Harvest 75 Million Players a Month”, 2010.02.08, Tedd Hoff http://highscalability.com/blog/2010/2/8/how-farmville-scales-to-harvest-75-million-players-a-month.html
4. > Introduction Cloud computing Characteristics On-demand self-service Broad network access Resource pooling Rapid elasticity Measured service Service models Software as a service Platform as a service Infrastructure as a service Deployment models Private cloud Community cloud Public cloud Hybrid cloud “Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model promotes availability and is composed of five essential characteristics, three service models, and four deployment models.” Source: The NIST Definition of Cloud Computing, Version 15, 2009.10.07, Peter Mell and Tim Grance http://csrc.nist.gov/groups/SNS/cloud-computing/cloud-def-v15.doc
5. > Introduction Service delivery models (On-Premise) Infrastructure (as a Service) Platform (as a Service) Software (as a Service) You manage Applications Applications Applications Applications You manage Data Data Data Data Runtime Runtime Runtime Runtime Managed by vendor Middleware Middleware Middleware Middleware You manage Managed by vendor O/S O/S O/S O/S Managed by vendor Virtualization Virtualization Virtualization Virtualization Servers Servers Servers Servers Storage Storage Storage Storage Networking Networking Networking Networking
6. > Architecting for Scale > Vertical Scaling Traditional scale-up architecture Common characteristics synchronous processes sequential units of work tight coupling stateful pessimistic concurrency clustering for HA vertical scaling units of work app server web data store app server web data store
7. > Architecting for Scale >Vertical Scaling Traditional scale-up architecture To scale, get bigger servers expensive has scaling limits inefficient use of resources app server web data store app server web
8. > Architecting for Scale >Vertical Scaling Traditional scale-up architecture When problems occur bigger failure impact data store app server web app server web
9. > Architecting for Scale >Vertical Scaling Traditional scale-up architecture When problems occur bigger failure impact more complex recovery app server web data store web
19. > Architecting for Scale > Horizontal scaling Scale-out architecture To scale, add more servers not bigger servers app server web data store app server web data store app server web data store app server web data store app server web data store app server web data store
20. > Architecting for Scale > Horizontal scaling Scale-out architecture When problems occur smaller failure impact higher perceived availability app server web data store app server web data store app server web data store app server web data store app server web data store app server web data store
21. > Architecting for Scale > Horizontal scaling Scale-out architecture When problems occur smaller failure impact higher perceived availability simpler recovery app server web data store app server web data store web app server data store web data store app server web data store app server web data store
22. > Architecting for Scale > Horizontal scaling Scale-out architecture + distributed computing parallel tasks Scalable performance at extreme scale asynchronous processes parallelization smaller footprint optimized resource usage reduced response time improved throughput app server web data store app server web data store web app server data store app server web data store perceived response time app server web data store app server web data store async tasks
23. > Architecting for Scale > Horizontal scaling Scale-out architecture + distributed computing When problems occur smaller units of work decoupling shields impact app server web data store app server web data store web app server data store app server web data store app server web data store app server web data store
24. > Architecting for Scale > Horizontal scaling Scale-out architecture + distributed computing When problems occur smaller units of work decoupling shields impact even simpler recovery app server web data store app server web data store web app server data store app server web data store app server web data store web data store
25. > Architecting for Scale >Cloud Architecture Patterns Live Journal (from Brad Fitzpatrick, then Founder at Live Journal, 2007) Web Frontend Apps & Services Partitioned Data Distributed Cache Distributed Storage
26. > Architecting for Scale >Cloud Architecture Patterns Flickr (from Cal Henderson, then Director of Engineering at Yahoo, 2007) Web Frontend Apps & Services Distributed Storage Distributed Cache Partitioned Data
27. > Architecting for Scale >Cloud Architecture Patterns SlideShare(from John Boutelle, CTO at Slideshare, 2008) Web Frontend Apps & Services Distributed Cache Partitioned Data Distributed Storage
28. > Architecting for Scale >Cloud Architecture Patterns Twitter (from John Adams, Ops Engineer at Twitter, 2010) Web Frontend Apps & Services Partitioned Data Queues Async Processes Distributed Cache Distributed Storage
29. > Architecting for Scale >Cloud Architecture Patterns Distributed Storage Facebook (from Jeff Rothschild, VP Technology at Facebook, 2009) 2010 stats (Source: http://www.facebook.com/press/info.php?statistics) People +500M active users 50% of active users log on in any given day people spend +700B minutes /month Activity on Facebook +900M objects that people interact with +30B pieces of content shared /month Global Reach +70 translations available on the site ~70% of users outside the US +300K users helped translate the site through the translations application Platform +1M developers from +180 countries +70% of users engage with applications /month +550K active applications +1M websites have integrated with Facebook Platform +150M people engage with Facebook on external websites /month Web Frontend Apps & Services Distributed Cache Parallel Processes Partitioned Data Async Processes
31. >Architecting for Scale Fundamental concepts Horizontal scaling for cloud computing Small pieces, loosely coupled Distributed computing best practices asynchronous processes (event-driven design) parallelization idempotent operations (handle duplicity) de-normalized, partitioned data (sharding) shared nothing architecture optimistic concurrency fault-tolerance by redundancy and replication etc.
32. > Architecting for Scale >Fundamental Concepts Asynchronous processes & parallelization Defer work as late as possible return to user as quickly as possible event-driven design (instead of request-driven) Cloud computing friendly distributes work to more servers (divide & conquer) smaller resource usage/footprint smaller failure surface decouples process dependencies Windows Azure platform services Queue Service AppFabric Service Bus inter-node communication Worker Role Web Role Queues Service Bus Web Role Web Role Web Role Worker Role Worker Role Worker Role
33. > Architecting for Scale >Fundamental Concepts Partitioned data Shared nothing architecture transaction locality (partition based on an entity that is the “atomic” target of majority of transactional processing) loosened referential integrity (avoid distributed transactions across shard and entity boundaries) design for dynamic redistribution and growth of data (elasticity) Cloud computing friendly divide & conquer size growth with virtually no limits smaller failure surface Windows Azure platform services Table Storage Service SQL Azure read Web Role Queues Web Role Web Role Worker Role Relational Database Relational Database Relational Database Web Role write
34. > Architecting for Scale >Fundamental Concepts Idempotent operations Repeatable processes allow duplicates (additive) allow re-tries (overwrite) reject duplicates (optimistic locking) stateless design Cloud computing friendly resiliency Windows Azure platform services Queue Service AppFabric Service Bus Worker Role Service Bus Worker Role Worker Role
35. > Architecting for Scale >Fundamental Concepts Hybrid architectures Scale-out (horizontal) BASE: Basically Available, Soft state, Eventually consistent focus on “commit” conservative (pessimistic) shared nothing favor extreme size e.g., user requests, data collection & processing, etc. Scale-up (vertical) ACID: Atomicity, Consistency, Isolation, Durability availability first; best effort aggressive (optimistic) transactional favor accuracy/consistency e.g., BI & analytics, financial processing, etc. Most distributed systems employ both approaches
Microsoft's Windows Azure platform is a virtualized and abstracted application platform that can be used to build highly scalable and reliable applications, with Java. The environment consists of a set of services such as NoSQL table storage, blob storage, queues, relational database service, internet service bus, access control, and more. Java applications can be built using these services via Web services APIs, and your own Java Virtual Machine, without worrying about the underlying server OS and infrastructure. Highlights of this session will include: • An overview of the Windows Azure environment • How to develop and deploy Java applications in Windows Azure • How to architect horizontally scalable applications in Windows Azure