2nd video of AWS Solution Architect Associate Exam series by SaMtheCloudGuy.
https://aws.amazon.com/certification/certified-solutions-architect-associate/
https://www.facebook.com/samthecloudguy/ https://www.slideshare.net/samthecloudguy/
https://www.youtube.com/c/SaMtheCloudGuy
More videos coming soon.
AWS SSA Webinar 21 - Getting Started with Data lakes on AWSCobus Bernard
In this session, we will take you through getting started with a Data Lake by looking at how you can ingest data to Amazon S3, query it with Amazon Athena and perform ETL operations on it using AWS Glue. We will be using the Redshift cluster from the previous session to export data to S3 to query.
Amazon Web Services (AWS) began offering IT infrastructure services to businesses in the form of web services -- now commonly known as cloud computing. One of the key benefits of cloud computing is the opportunity to replace up-front capital infrastructure expenses with low variable costs that scale with your business. With the Cloud, businesses no longer need to plan for and procure servers and other IT infrastructure weeks or months in advance. Instead, they can instantly spin up hundreds or thousands of servers in minutes and deliver results faster.
Cost and Performance Optimisation in Amazon RDS - AWS Summit Sydney 2018Amazon Web Services
Cost and Performance Optimisation in Amazon RDS
This session is for database administrators and other technical users looking to learn the top techniques for optimising the performance and cost of operating Amazon RDS. You will leave with a toolkit of best-practices that can be applied to your deployments for achieving optimal performance, flexibility, and cost-savings.
Brad Staszcuk, Solutions Architect, Amazon Web Services
2nd video of AWS Solution Architect Associate Exam series by SaMtheCloudGuy.
https://aws.amazon.com/certification/certified-solutions-architect-associate/
https://www.facebook.com/samthecloudguy/ https://www.slideshare.net/samthecloudguy/
https://www.youtube.com/c/SaMtheCloudGuy
More videos coming soon.
AWS SSA Webinar 21 - Getting Started with Data lakes on AWSCobus Bernard
In this session, we will take you through getting started with a Data Lake by looking at how you can ingest data to Amazon S3, query it with Amazon Athena and perform ETL operations on it using AWS Glue. We will be using the Redshift cluster from the previous session to export data to S3 to query.
Amazon Web Services (AWS) began offering IT infrastructure services to businesses in the form of web services -- now commonly known as cloud computing. One of the key benefits of cloud computing is the opportunity to replace up-front capital infrastructure expenses with low variable costs that scale with your business. With the Cloud, businesses no longer need to plan for and procure servers and other IT infrastructure weeks or months in advance. Instead, they can instantly spin up hundreds or thousands of servers in minutes and deliver results faster.
Cost and Performance Optimisation in Amazon RDS - AWS Summit Sydney 2018Amazon Web Services
Cost and Performance Optimisation in Amazon RDS
This session is for database administrators and other technical users looking to learn the top techniques for optimising the performance and cost of operating Amazon RDS. You will leave with a toolkit of best-practices that can be applied to your deployments for achieving optimal performance, flexibility, and cost-savings.
Brad Staszcuk, Solutions Architect, Amazon Web Services
Amazon Relational Database Service (Amazon RDS) is a web service that makes it easier to set up, operate, and scale a relational database in the cloud. It provides cost-efficient, re-sizable capacity for an industry-standard relational database and manages common database administration tasks
Overview on Amazon EMR and its benefits for a wide variety of use cases and how to get started alongside Apache Zeppelin for interactive data analytics and document collaboration.
AWS CloudFormation is a service that helps you model and set up your Amazon Web Services resources so you can spend less time managing those resources, and more time focusing on your applications.
This slide will guide you, how to write JSON templet.
In the first Webinar of the 2014 Masterclass Series AWS Technical Evangelist Ian Massingham dives deep into the Amazon Simple Storage Service, S3. He starts by providing an overview of the high level architecture of S3 and the fundamental characteristics of the service before moving on to take a tour through the various features of S3 including storage classes, namespaces, encryption, access controls, transitions and lifecycle management. He also covers related AWS services such as Glacier and the AWS content distribution network, CloudFront, as well as explaining how you can use Amazon S3 to serve static web content.
O Amazon Redshift é um data warehouse rápido, gerenciado e em escala de petabytes que torna mais simples e econômica a análise de todos os seus dados usando as ferramentas de inteligência de negócios de que você já dispõe. Comece aos poucos, por apenas 0,25 USD por hora, sem compromissos, e aumente a escala até petabytes por 1.000 USD por terabyte por ano, menos de um décimo do custo das soluções tradicionais. Normalmente, os clientes relatam uma compactação de 3x, que reduz seus custos para 333 USD por terabyte não compactado por ano.
Scientists, developers, and many other technologists from many different industries are taking advantage of Amazon Web Services to meet the challenges of the increasing volume, variety, and velocity of digital information. Amazon Web Services offers an end-to-end portfolio of cloud computing resources to help you manage big data by reducing costs, gaining a competitive advantage and increasing the speed of innovation.
In this presentation from a webinar focusing on running Data Analytics on AWS, AWS Technical Evangelist, Ian Massingham, discusses the role that AWS services can play in helping you to derive value from your data. Topics include stream processing with Amazon Kinesis, processing data with Amazon Elastic MapReduce (EMR)and its ecosystem of tools and running large scale data warehouses on AWS with Redshift.
Topics covered in this session:
• Discover how AWS customers are extracting value from Big Data
• Understand the role that AWS services could play in helping you to manage your data
• Learn about running Hadoop on AWS Amazon EMR and its ecosystem of tools for data processing and analysis
See a recording of this webinar on YouTube here: http://youtu.be/ueRarqsCbJM
See past and future webinars in the Journey Through the Cloud series here: http://aws.amazon.com/campaigns/emea/journey/
For a deep dive into specific AWS services, you might also be interested in the Masterclass webinar series, which you can find here: http://aws.amazon.com/campaigns/emea/masterclass/
Amazon Aurora is a MySQL and PostgreSQL compatible relational database built for the cloud, that combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. AWS Database Migration Service helps you migrate databases to AWS quickly and securely. The source database remains fully operational during the migration, minimizing downtime to applications that rely on the database. In this session, we explore features of Amazon Aurora and demonstrate database migration using the AWS Database Migration Service.
Consolidate MySQL Shards Into Amazon Aurora Using AWS Database Migration Serv...Amazon Web Services
If you’re running a MySQL database at scale, there’s a good chance you’re sharding your database deployment. Sharding is a useful way to increase the scale of your deployment, but it has drawbacks like higher costs, high administration overheard and lower elasticity. It’s harder to grow or shrink a sharded database deployment to match your traffic patterns. In this session, we will discuss and demonstrate how to use AWS Database Migration Service to consolidate multiple MySQL shards into an Amazon Aurora cluster to reduce cost, improve elasticity and make it easier to manage your database.
Learning Objectives:
Learn how to scale your MySQL database at reduced cost and higher elasticity, by consolidating multiple shards into one Amazon Aurora cluster.
El almacenamiento en la nube es un componente crítico de la informática en la nube, que guarda la información que utilizan las aplicaciones. El análisis de big data, los almacenes de datos, el Internet de las cosas, las bases de datos y las aplicaciones de backup y archivado dependen de algún tipo de arquitectura de almacenamiento de datos. El almacenamiento en la nube, por lo general, es más fiable, escalable y seguro que los sistemas de almacenamiento en las instalaciones tradicionales.
AWS ofrece una gama completa de servicios de almacenamiento en la nube para respaldar los requisitos de conformidad de las aplicaciones y el archivado. Seleccione entre servicios de almacenamiento de objetos, archivos y por bloques, así como opciones de migración de datos a la nube para comenzar a diseñar las bases de su entorno de TI en la nube.
YouTube Link: https://youtu.be/9HsEMyKrlnw
**AWS Certification Training: https://www.edureka.co/cloudcomputing **
This "AWS S3 Tutorial for Beginners" PPT by Edureka will help you understand one of the most popular storage service, Amazon S3, and related concepts in detail. Following are the offerings of this PPT:
1. AWS Storage Services
2. What is AWS S3?
3. Buckets & Objects
4. Versioning & Cross Region Replication
5. Transfer Acceleration
6. S3 Demo and Use Case
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Organizations need to perform increasingly complex analysis on data — streaming analytics, ad-hoc querying, and predictive analytics — in order to get better customer insights and actionable business intelligence. Apache Spark has recently emerged as the framework of choice to address many of these challenges. In this session, we show you how to use Apache Spark on AWS to implement and scale common big data use cases such as real-time data processing, interactive data science, predictive analytics, and more. We will talk about common architectures, best practices to quickly create Spark clusters using Amazon EMR, and ways to integrate Spark with other big data services in AWS.
Learning Objectives:
• Learn why Spark is great for ad-hoc interactive analysis and real-time stream processing.
• How to deploy and tune scalable clusters running Spark on Amazon EMR.
• How to use EMR File System (EMRFS) with Spark to query data directly in Amazon S3.
• Common architectures to leverage Spark with Amazon DynamoDB, Amazon Redshift, Amazon Kinesis, and more.
If you are interested to know more about AWS Chicago Summit, please use the following to register: http://amzn.to/1RooPPL
Many AWS customers store vast amounts of data in Amazon S3, a low cost, scalable, and durable object store; Amazon DynamoDB, a NoSQL database; or Amazon Kinesis, a real time data stream processing service. With large datasets in various AWS services, how do you derive value from this information in a cost-effective way? Using Amazon Elastic MapReduce (Amazon EMR) with applications in the Apache Hadoop ecosystem, you can directly interact with data in each of these storage services for scalable analytics workloads or ad hoc queries. You can quickly and easily launch an Amazon EMR cluster from the AWS Management Console, and scale your cluster to match the compute and memory resources needed for your workflow, independent from the storage capacity used in your AWS storage services. The webinar will accelerate your use of Amazon EMR by showing you how to create and monitor Amazon EMR clusters, and provide several use cases and architectures for using Amazon EMR with different AWS data stores.
Learning Objectives: • Recognize when to use Amazon EMR • Understand the steps required to set up and monitor an Amazon EMR cluster • Architect applications that effectively use Amazon EMR • Understand how to use HUE for ad hoc query of data in Amazon S3
Who Should Attend: • Developers, LOB owners, Continuous Integration & Continuous Delivery (CICD) practitioners
Organizations often need to quickly analyze large amounts of data, such as logs generated from a wide variety of sources and formats. However, traditional approaches require a lot of time and effort designing complex data transformation and loading processes; and configuring data warehouses. Using AWS, you can start querying your datasets within minutes. In this session you will learn how you can deploy a managed Presto environment in minutes to interactively query log data using standard ANSI SQL. Presto is a popular open source SQL engine for running interactive analytic queries against data sources of all sizes. We will talk about common use cases and best practices for running Presto on Amazon EMR.
Spark and the Hadoop Ecosystem: Best Practices for Amazon EMRAmazon Web Services
Amazon EMR is a managed service that lets you process and analyze extremely large data sets using the latest versions of over 15 open-source frameworks in the Apache Hadoop and Spark ecosystems. In this session, we introduce you to Amazon EMR design patterns such as using Amazon S3 instead of HDFS, taking advantage of both long and short-lived clusters, and other Amazon EMR architectural best practices. We talk about how to scale your cluster up or down dynamically and introduce you to ways you can fine-tune your cluster. We also share best practices to keep your Amazon EMR cluster cost-efficient. Finally, we dive into some of our recent launches to keep you current on our latest features. This session will feature Asurion, a provider of device protection and support services for over 280 million smartphones and other consumer electronics devices.
Training for AWS Solutions Architect at http://zekelabs.com/courses/amazon-web-services-training-bangalore/.This slide describes about database offering, Relational Database services (RDS), Read Replica, Multi-AZ, DynamoDB, Elasticache, Redshift, Aurora and Neptune
___________________________________________________
zekeLabs is a Technology training platform. We provide instructor led corporate training and classroom training on Industry relevant Cutting Edge Technologies like Big Data, Machine Learning, Natural Language Processing, Artificial Intelligence, Data Science, Amazon Web Services, DevOps, Cloud Computing and Frameworks like Django,Spring, Ruby on Rails, Angular 2 and many more to Professionals.
Reach out to us at www.zekelabs.com or call us at +91 8095465880 or drop a mail at info@zekelabs.com
Amazon Relational Database Service (Amazon RDS) is a web service that makes it easier to set up, operate, and scale a relational database in the cloud. It provides cost-efficient, re-sizable capacity for an industry-standard relational database and manages common database administration tasks
Overview on Amazon EMR and its benefits for a wide variety of use cases and how to get started alongside Apache Zeppelin for interactive data analytics and document collaboration.
AWS CloudFormation is a service that helps you model and set up your Amazon Web Services resources so you can spend less time managing those resources, and more time focusing on your applications.
This slide will guide you, how to write JSON templet.
In the first Webinar of the 2014 Masterclass Series AWS Technical Evangelist Ian Massingham dives deep into the Amazon Simple Storage Service, S3. He starts by providing an overview of the high level architecture of S3 and the fundamental characteristics of the service before moving on to take a tour through the various features of S3 including storage classes, namespaces, encryption, access controls, transitions and lifecycle management. He also covers related AWS services such as Glacier and the AWS content distribution network, CloudFront, as well as explaining how you can use Amazon S3 to serve static web content.
O Amazon Redshift é um data warehouse rápido, gerenciado e em escala de petabytes que torna mais simples e econômica a análise de todos os seus dados usando as ferramentas de inteligência de negócios de que você já dispõe. Comece aos poucos, por apenas 0,25 USD por hora, sem compromissos, e aumente a escala até petabytes por 1.000 USD por terabyte por ano, menos de um décimo do custo das soluções tradicionais. Normalmente, os clientes relatam uma compactação de 3x, que reduz seus custos para 333 USD por terabyte não compactado por ano.
Scientists, developers, and many other technologists from many different industries are taking advantage of Amazon Web Services to meet the challenges of the increasing volume, variety, and velocity of digital information. Amazon Web Services offers an end-to-end portfolio of cloud computing resources to help you manage big data by reducing costs, gaining a competitive advantage and increasing the speed of innovation.
In this presentation from a webinar focusing on running Data Analytics on AWS, AWS Technical Evangelist, Ian Massingham, discusses the role that AWS services can play in helping you to derive value from your data. Topics include stream processing with Amazon Kinesis, processing data with Amazon Elastic MapReduce (EMR)and its ecosystem of tools and running large scale data warehouses on AWS with Redshift.
Topics covered in this session:
• Discover how AWS customers are extracting value from Big Data
• Understand the role that AWS services could play in helping you to manage your data
• Learn about running Hadoop on AWS Amazon EMR and its ecosystem of tools for data processing and analysis
See a recording of this webinar on YouTube here: http://youtu.be/ueRarqsCbJM
See past and future webinars in the Journey Through the Cloud series here: http://aws.amazon.com/campaigns/emea/journey/
For a deep dive into specific AWS services, you might also be interested in the Masterclass webinar series, which you can find here: http://aws.amazon.com/campaigns/emea/masterclass/
Amazon Aurora is a MySQL and PostgreSQL compatible relational database built for the cloud, that combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. AWS Database Migration Service helps you migrate databases to AWS quickly and securely. The source database remains fully operational during the migration, minimizing downtime to applications that rely on the database. In this session, we explore features of Amazon Aurora and demonstrate database migration using the AWS Database Migration Service.
Consolidate MySQL Shards Into Amazon Aurora Using AWS Database Migration Serv...Amazon Web Services
If you’re running a MySQL database at scale, there’s a good chance you’re sharding your database deployment. Sharding is a useful way to increase the scale of your deployment, but it has drawbacks like higher costs, high administration overheard and lower elasticity. It’s harder to grow or shrink a sharded database deployment to match your traffic patterns. In this session, we will discuss and demonstrate how to use AWS Database Migration Service to consolidate multiple MySQL shards into an Amazon Aurora cluster to reduce cost, improve elasticity and make it easier to manage your database.
Learning Objectives:
Learn how to scale your MySQL database at reduced cost and higher elasticity, by consolidating multiple shards into one Amazon Aurora cluster.
El almacenamiento en la nube es un componente crítico de la informática en la nube, que guarda la información que utilizan las aplicaciones. El análisis de big data, los almacenes de datos, el Internet de las cosas, las bases de datos y las aplicaciones de backup y archivado dependen de algún tipo de arquitectura de almacenamiento de datos. El almacenamiento en la nube, por lo general, es más fiable, escalable y seguro que los sistemas de almacenamiento en las instalaciones tradicionales.
AWS ofrece una gama completa de servicios de almacenamiento en la nube para respaldar los requisitos de conformidad de las aplicaciones y el archivado. Seleccione entre servicios de almacenamiento de objetos, archivos y por bloques, así como opciones de migración de datos a la nube para comenzar a diseñar las bases de su entorno de TI en la nube.
YouTube Link: https://youtu.be/9HsEMyKrlnw
**AWS Certification Training: https://www.edureka.co/cloudcomputing **
This "AWS S3 Tutorial for Beginners" PPT by Edureka will help you understand one of the most popular storage service, Amazon S3, and related concepts in detail. Following are the offerings of this PPT:
1. AWS Storage Services
2. What is AWS S3?
3. Buckets & Objects
4. Versioning & Cross Region Replication
5. Transfer Acceleration
6. S3 Demo and Use Case
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Organizations need to perform increasingly complex analysis on data — streaming analytics, ad-hoc querying, and predictive analytics — in order to get better customer insights and actionable business intelligence. Apache Spark has recently emerged as the framework of choice to address many of these challenges. In this session, we show you how to use Apache Spark on AWS to implement and scale common big data use cases such as real-time data processing, interactive data science, predictive analytics, and more. We will talk about common architectures, best practices to quickly create Spark clusters using Amazon EMR, and ways to integrate Spark with other big data services in AWS.
Learning Objectives:
• Learn why Spark is great for ad-hoc interactive analysis and real-time stream processing.
• How to deploy and tune scalable clusters running Spark on Amazon EMR.
• How to use EMR File System (EMRFS) with Spark to query data directly in Amazon S3.
• Common architectures to leverage Spark with Amazon DynamoDB, Amazon Redshift, Amazon Kinesis, and more.
If you are interested to know more about AWS Chicago Summit, please use the following to register: http://amzn.to/1RooPPL
Many AWS customers store vast amounts of data in Amazon S3, a low cost, scalable, and durable object store; Amazon DynamoDB, a NoSQL database; or Amazon Kinesis, a real time data stream processing service. With large datasets in various AWS services, how do you derive value from this information in a cost-effective way? Using Amazon Elastic MapReduce (Amazon EMR) with applications in the Apache Hadoop ecosystem, you can directly interact with data in each of these storage services for scalable analytics workloads or ad hoc queries. You can quickly and easily launch an Amazon EMR cluster from the AWS Management Console, and scale your cluster to match the compute and memory resources needed for your workflow, independent from the storage capacity used in your AWS storage services. The webinar will accelerate your use of Amazon EMR by showing you how to create and monitor Amazon EMR clusters, and provide several use cases and architectures for using Amazon EMR with different AWS data stores.
Learning Objectives: • Recognize when to use Amazon EMR • Understand the steps required to set up and monitor an Amazon EMR cluster • Architect applications that effectively use Amazon EMR • Understand how to use HUE for ad hoc query of data in Amazon S3
Who Should Attend: • Developers, LOB owners, Continuous Integration & Continuous Delivery (CICD) practitioners
Organizations often need to quickly analyze large amounts of data, such as logs generated from a wide variety of sources and formats. However, traditional approaches require a lot of time and effort designing complex data transformation and loading processes; and configuring data warehouses. Using AWS, you can start querying your datasets within minutes. In this session you will learn how you can deploy a managed Presto environment in minutes to interactively query log data using standard ANSI SQL. Presto is a popular open source SQL engine for running interactive analytic queries against data sources of all sizes. We will talk about common use cases and best practices for running Presto on Amazon EMR.
Spark and the Hadoop Ecosystem: Best Practices for Amazon EMRAmazon Web Services
Amazon EMR is a managed service that lets you process and analyze extremely large data sets using the latest versions of over 15 open-source frameworks in the Apache Hadoop and Spark ecosystems. In this session, we introduce you to Amazon EMR design patterns such as using Amazon S3 instead of HDFS, taking advantage of both long and short-lived clusters, and other Amazon EMR architectural best practices. We talk about how to scale your cluster up or down dynamically and introduce you to ways you can fine-tune your cluster. We also share best practices to keep your Amazon EMR cluster cost-efficient. Finally, we dive into some of our recent launches to keep you current on our latest features. This session will feature Asurion, a provider of device protection and support services for over 280 million smartphones and other consumer electronics devices.
Training for AWS Solutions Architect at http://zekelabs.com/courses/amazon-web-services-training-bangalore/.This slide describes about database offering, Relational Database services (RDS), Read Replica, Multi-AZ, DynamoDB, Elasticache, Redshift, Aurora and Neptune
___________________________________________________
zekeLabs is a Technology training platform. We provide instructor led corporate training and classroom training on Industry relevant Cutting Edge Technologies like Big Data, Machine Learning, Natural Language Processing, Artificial Intelligence, Data Science, Amazon Web Services, DevOps, Cloud Computing and Frameworks like Django,Spring, Ruby on Rails, Angular 2 and many more to Professionals.
Reach out to us at www.zekelabs.com or call us at +91 8095465880 or drop a mail at info@zekelabs.com
Training for AWS Solutions Architect at http://zekelabs.com/courses/amazon-web-services-training-bangalore/.This slide describes about features of EC2, EC2 Options, family type, storage, EBS Volumes, EC2 Instance Store, Security Groups, Volumes and Snapshots, Amazon Machine Image (AMI), Elastic load balancer, Classic load balancer, Application load balancer, Network load balancer, AWS CLI and EC2 Metadata
___________________________________________________
zekeLabs is a Technology training platform. We provide instructor led corporate training and classroom training on Industry relevant Cutting Edge Technologies like Big Data, Machine Learning, Natural Language Processing, Artificial Intelligence, Data Science, Amazon Web Services, DevOps, Cloud Computing and Frameworks like Django,Spring, Ruby on Rails, Angular 2 and many more to Professionals.
Reach out to us at www.zekelabs.com or call us at +91 8095465880 or drop a mail at info@zekelabs.com
Deep learning is an implementation of machine learning that uses neural networks to solve difficult and complex problems, such as computer vision, natural language processing, and recommendations. Due to the availability of deep learning libraries and frameworks, developers have the ability to enhance the capabilities of their applications and projects. In this workshop, you learn how to build and deploy a powerful deep learning framework called MXNet on containers. The portability and resource management benefit of containers means developers can focus less on infrastructure and more on building. The labs start by demonstrating the automation capabilities of AWS CloudFormation to stand up core infrastructure; as an added bonus, you use Spot Fleet to leverage the cost benefits of using Spot Instances, especially for developer environments. Then, you walk through creating an MXNet container in Docker and deploying it with Amazon ECS. Finally, you walk through an image classification demo of MXNet to validate that everything is working as expected. Note: This workshop focuses on containerizing MXNet. The features of MXNet and capabilities of deep learning in general are vast, and there are recorded sessions from re:Invent that dive deeper on these topics. All you need to participate is a laptop and AWS account. Pizza will be provided.
Elastic Compute Cloud (EC2) on AWS PresentationKnoldus Inc.
In this session, we will delve into Amazon Elastic Compute Cloud (Amazon EC2) , EC2 is a cloud computing service provided by Amazon Web Services (AWS) that enables users to easily and flexibly deploy and manage virtual servers, known as instances, in the cloud. EC2 offers a wide range of instance types to cater to diverse computing needs, from small-scale web applications to high-performance computing clusters. Users can select the operating system, configure the instance specifications, and scale their compute capacity up or down as needed, paying only for the compute resources they consume. This service empowers businesses and developers to efficiently run their applications, host websites, and perform various computing tasks in a scalable and cost-effective manner without the hassle of managing physical hardware.
Amazon Elastic Compute Cloud is defined as a virtual computing environment. It allows people to use their web service interfaces for launching several instances with diverse operating systems. Along with that, it also allows the users to implement network access control or permissions. For more information please visit https://www.whizlabs.com/blog/amazon-elastic-compute-cloud-guide/
Kin Wilms, AWS Solutions Architect's presentation to the Production & Post-Production track at the Media & Entertainment Cloud Symposium on Nov 4, 2016
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
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.
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.
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.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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/
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.
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.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
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.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
"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.
2. EC2
Amazon Elastic Compute Cloud (Amazon EC2) is a web service that
provides resizable compute capacity in the cloud. It is designed to make
web-scale computing easier for developers.
Can spin up VMs on cloud within mins per your requirement.
Revolutionary/Game changing paradigm that’s different and innovative
from conventional ways(Machine procurement).
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3. Why EC2 is so important?
Instant provisioning
Auto scaling
ELB
Low cost
Resizable(up and down)
AZ
CloudWatch monitoring, etc
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4. EC2 Pricing options
On demand-Pay/Hour model.
Reserved- 1/3 yr contract for a fixed capacity of EC2 instances. Low cost
per hour charges than on demand.
Spot- bid the price for instance-for requirements where start and end date
is not a concern.
Dedicated-Physical EC2 servers available as pay/hour fashion.(use existing
server bound licenses).
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5. Types of EC2 instance
Amazon EC2 instances are grouped into 5 families: General Purpose, Compute
Optimized, Memory Optimized, GPU, and Storage Optimized instances. General Purpose
Instances have memory to CPU ratios suitable for most general purpose applications and
come with fixed performance (M4 and M3 instances) or burstable performance (T2);
Compute Optimized instances (C4 and C3 instances) have proportionally more CPU
resources than memory (RAM) and are well suited for scale out compute-intensive
applications and High Performance Computing (HPC) workloads; Memory Optimized
Instances (R3 and R4 instances) offer larger memory sizes for memory-intensive
applications, including database and memory caching applications; GPU Compute
instances (P2) take advantage of the parallel processing capabilities of NVIDIA Tesla
GPUs for high performance parallel computing; GPU Graphics instances (G2) offer high-
performance 3D graphics capabilities for applications using OpenGL and DirectX;
Storage Optimized Instances include I2 instances that provide very high, low latency, I/O
capacity using SSD-based local instance storage for I/O-intensive applications and D2,
Dense-storage instances, that provide high storage density and sequential I/O
performance for data warehousing, Hadoop and other data-intensive applications.
When choosing instance types, you should consider the characteristics of your
application with regards to resource utilization (i.e. CPU, Memory, Storage) and select the
optimal instance family and instance size.
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6. EBS
Elastic Block storage lets you to create storage volumes and attach it with
ec2 instance.
Block based
Can install software's or used for storage.
EBS volumes are placed on specific AZ and replicated automatically to
withstand single point of failure.
Cannot attach 1 EBS volume to multiple EC2 instances-For this EFS can be
used.
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7. EBS Volume types:
General Purpose SSD(GP2)-Upto 10,000 IOPS
Provisioned IOPS SSD(IO1)-More than 10,000 IOPS
Throughput optimized HDD-magnetic volume(ST1)-Frequent access of data
Cold HDD-Magnetic Volume(SC1)-IA data
Magnetic(Standard)-Lowest cost,IA bootable storage.
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9. Thank You
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