This document discusses deploying web services using AWS Lambda. It begins with an agenda that covers Lambda essentials, creating Lambda code, limitations of Lambda, a demo, event-driven architecture, and Q&A. The document then discusses what Lambda is, Lambda essentials like memory allocation and supported languages, a "Hello World" example, how to deploy a Lambda function from the command line, event sources for Lambda, Lambda limitations, security, a demo of a file sharing app using Lambda, event-driven architecture, pricing, deployment frameworks, and concludes with thanking the audience and asking for questions.
These are the slides of the second talk of the second Tech Talk@TransferWise Singapore, which happened on the 1st of March 2018.
We take a look at what Serverless Computing is, find out what we can do with Amazon Web Services Lambda and when it can be useful. We also explore how it has evolved for the past 3 years and learn about its remaining limitations.
Serverless Microservices w/ AWS Lambda and node.jsFrank Valcarcel
This document discusses serverless microservices using AWS Lambda and Node.js. It begins by explaining that AWS Lambda is a serverless computing platform that runs code without provisioning or managing servers. It then discusses how serverless architectures can be used to build microservices and outlines some of the pros and cons of AWS Lambda, including event-driven automatic scaling, on-demand pricing model, and resource limits. It concludes by providing examples of serverless use cases and architectures using AWS Lambda and other AWS services.
This document introduces Amazon Web Services (AWS) including Amazon Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2). S3 provides backup storage and content delivery while EC2 allows running applications like Apache, MySQL, and memcache on cloud computing resources. Using AWS services like S3 and EC2 can reduce hardware costs and provide scalability. An example project converted 4TB of scanned documents to PDF using 100 EC2 instances for $3000 over 2-3 days. EC2 pricing starts at $0.01 per hour for small instances. EC2onRails makes it easy to deploy Ruby on Rails applications on AWS.
Container management with docker & kubernetesKasun Rajapakse
Kasun Rajapakse provides an overview of container management with Azure Kubernetes Service (AKS). AKS is a managed Kubernetes service provided by Azure that makes it easy to get started with enterprise-scale container environments. Key points include:
- Containers are more lightweight than VMs and share the host OS kernel for efficiency. Docker is a tool for building and running containers.
- Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications. It was originally developed by Google.
- AKS removes the need to manage the Kubernetes master nodes, allowing users to focus on containerized applications. It provides automated upgrades, scaling
Common considerations on Serverless architecture, AWS Lambda (including Serverless Framework) and ECS. Also introduces Guanyu, an open-sourced wrapper to Sophos-AV Free edition, as example to demonstrate patterns and tradeoffs in architecture.
This presentation covers how to use CloudFormation for deploying customized services on AWS. It goes through the background and advantages, as well as some commonly-used functions. Presented by Joseph Maxwell: lead developer at SwiftOtter Studios.
This document discusses Linux user management in serverless environments. It mentions cloudpack GL, AWS, RDS, and JAWS-UG as they relate to serverless computing. The last line refers to STNS Serverless, likely the topic of the meetup.
Amazon Web Services (AWS) began in 2003 to provide infrastructure services to support Amazon's internal needs and expansion. It has since grown to include over 60 services across compute, storage, databases, analytics, machine learning, IoT, mobile, and enterprise applications. Key AWS services include Elastic Compute Cloud (EC2) for virtual servers, Simple Storage Service (S3) for cloud storage, and CloudWatch for monitoring resources. Pricing varies based on compute and storage resources used, data transfer, and service type, with options like on-demand, reserved, and pay-as-you-go pricing.
Introduction to Windows Azure Service Bus Relay ServiceTamir Dresher
The document discusses Microsoft Azure Service Bus and its capabilities. Service Bus acts as an intermediary for applications to communicate across networks by relaying messages between clients and services. It supports various connectivity options and protocols to help address challenges like firewalls and internet connectivity. Service Bus provides scalability, availability, security and a registry for discovering services. Code examples are given to demonstrate creating client applications and services that communicate via Service Bus.
The document discusses adopting a serverless architecture to address pain points with a traditional architecture. Specifically, it notes that serverless allows processing without needing to run an always-on EC2 instance, easier management of resources for multiple tenants, lower cost parallel processing without expensive resource allocation, and lower costs overall. The new serverless architecture uses AWS Lambda for offloading analytics data hits from application servers to keep bills low, and uses Lambda functions triggered by SNS topics to send SMS messages through the standard SNS API.
This document provides an overview of clusterless serverless container deployment with AWS Fargate. It introduces concepts like containers, microservices, and container orchestration. It then discusses different AWS container services like ECS and EKS. The main topic is AWS Fargate, which is described as a fully managed container service that eliminates the need to manage clusters or nodes. It explains how Fargate works and its pricing model based on vCPU and memory resources used. A sample Fibonacci application deployed on Fargate is also briefly presented.
Structuring node.js projects - Seven Peaks Software (Node.JS Meetup 18 nov 2021)Seven Peaks Speaks
Denis is a professional programmer who has 12+ years of experience working in various startups!
Denis was dive deep into Structuring your Node.JS app, DI Container, Async Local Storage, Request handlers, Services, Unit of Work and Testing.
For more info about Seven Peaks Software:
https://lnkd.in/g2jMsDy
This document provides an overview of AWS Systems Manager, which is a collection of capabilities for configuring and managing Amazon EC2 instances, on-premises servers, and other AWS resources at scale. It addresses challenges like achieving compliance for instances, scalability, support for multi-cloud and hybrid environments, providing developer power, handling limited internet access, and low cost. Key capabilities of AWS Systems Manager include automation, compliance, running commands, patching, state management, and maintenance windows. The document provides examples of using it for bastion hosts, inventory, auditing changes, and patch compliance.
Performance Tales of Serverless - CloudNative London 2018☁️ Mikhail Shilkov
Function-as-a-Service "serverless" cloud offerings provide you with a super easy way to run custom code in response to events. One promise of FaaS model is the ability to scale without limits, up or down, whenever needed. But how does that work in practice? Can AWS Lambda handle thousands of messages per second? How fast can Azure Functions scale up under sudden heavy load? What kind of latency can you expect from Google Cloud Functions? During this session Mikhail will share with you short tales, each of them teaching a lesson about practical scalability of serverless applications. You will also explore the steps to evaluate whether your application profile is suitable for serverless today.
This document discusses cloud computing on AWS and Azure. It covers availability sets, blob storage, cloud backup, HDInsights, SQL as a service, file storage, load balancers, CDNs, firewalls, Kubernetes, cloud SQL, disk images, managed instance groups, and regional instance groups. It notes the good, bad, and ugly aspects of Azure's user interface as well as new beta interface. The document ends asking questions and saying goodbye.
The document discusses Amazon web services and cloud computing. It provides an overview of Amazon's services including Fulfillment, Associates, web search, Mechanical Turk, Payments, Infrastructure services like Simple Queue, SimpleDB, Simple Storage, and Elastic Compute Cloud. It also discusses cloud computing concepts and compares Amazon services to offerings from Google, Microsoft, Salesforce and others. The document considers potential applications and services that could be developed using these cloud platforms.
In this talk we will cover:
1. Using concurrency to maximize hardware (Elixir, Clojure, Haskell)
2. Serverless technologies for backend architecture (Amazon AWS Lambda, Microsoft Azure Cloud Functions)
3. BaaS – Backend as a Service (Google Firebase, etc)
This document discusses an AWS Premier event held in Osaka, Japan. It mentions EC2, cloudpack GL, AWS, RDS, and JAWS-UG which appear to be services, products or groups related to Amazon Web Services. The document provides high-level information about an AWS conference event but does not include many details.
Switching SaaS Hosting From dedicated virtual machines to container-based clu...AWS Germany
Presentation "Switching SaaS Hosting From dedicated virtual machines to container-based clusters" from Dr. Sven Ehlert at the AWS E-Business Web Day for windows applications. All videos and presentations can be found here: http://amzn.to/2ds3aMX
This document summarizes the key aspects of AWS orchestration for a company processing 6 billion requests per day across multiple services and regions. It discusses auto-scaling groups (ASGs) across 750 servers in 2 regions and 5 availability zones, with over 30 ASGs handling more than 20 API integrations. It also describes a homemade Redis autoscaling using master-slave replication across regions on spots and on-demand instances, handling 1.2 million operations per second. An event-driven architecture is implemented using a ØMQ mesh pipeline across ASGs for unidirectional data flow of 100k messages per second.
This document provides an introduction to defining cloud services using a declarative approach and YAML templates. It discusses how YAML can be used to describe services through key-value mappings and indentation. An example scenario is presented where a company wants to simplify application deployment on OpenStack. The document then presents conceptual models to meet the requirements of creating a repeatable infrastructure configuration and unique instantiations of that configuration. It demonstrates the structure of a YAML template with sections for description, parameters, resources, and outputs. Finally, it provides an example of using functions in templates to reference resources, parameters, and attributes and shows how resource dependencies can be captured.
Dray is a Go application that runs in a container and manages the execution and clean-up of task containers. It treats containers as single-purpose, short-lived tasks rather than long-running services. Dray groups related tasks into jobs that are posted as JSON documents. It marshals the output of one container to the input of the next, similar to UNIX pipes. An example job runs three tasks sequentially to deploy a Kubernetes cluster and install a remote agent on infrastructure provisioned by Panamax.
This document provides an introduction to AWS Lambda and the Serverless Framework. It defines serverless computing and discusses key differences between Platform as a Service (PaaS) and serverless models. AWS Lambda is introduced as Amazon's serverless compute platform, and other serverless platform providers are listed. The Serverless Framework is described as a development toolkit for building, managing and deploying serverless applications. Sample code and a serverless.yml configuration file are shown.
Serverless Comparison: AWS vs Azure vs Google vs IBMRightScale
This document provides a comparison of serverless computing platforms across AWS Lambda, Azure Functions, Google Cloud Functions, and IBM Cloud Functions. It covers aspects such as available languages, memory sizes and limits, scaling behavior, built-in triggers, pricing models, and example cost comparisons between serverless and traditional compute instances. The document finds that while all major clouds offer serverless computing, they differ in areas like languages supported, scaling performance, and pricing models, with no single option emerging as unanimously superior across all dimensions.
This document discusses deploying microservices on AWS. It begins by explaining what microservices are and then discusses hosting options on AWS including EC2, ECS, and Lambda. ECS is identified as the preferred option since it allows hosting containers with Docker. The document then covers deployment aspects like using source control with Git for multiple environments, building and testing code, deploying single services or entire clusters, live testing, and monitoring with alerts.
This presentation covers how to use CloudFormation for deploying customized services on AWS. It goes through the background and advantages, as well as some commonly-used functions. Presented by Joseph Maxwell: lead developer at SwiftOtter Studios.
This document discusses Linux user management in serverless environments. It mentions cloudpack GL, AWS, RDS, and JAWS-UG as they relate to serverless computing. The last line refers to STNS Serverless, likely the topic of the meetup.
Amazon Web Services (AWS) began in 2003 to provide infrastructure services to support Amazon's internal needs and expansion. It has since grown to include over 60 services across compute, storage, databases, analytics, machine learning, IoT, mobile, and enterprise applications. Key AWS services include Elastic Compute Cloud (EC2) for virtual servers, Simple Storage Service (S3) for cloud storage, and CloudWatch for monitoring resources. Pricing varies based on compute and storage resources used, data transfer, and service type, with options like on-demand, reserved, and pay-as-you-go pricing.
Introduction to Windows Azure Service Bus Relay ServiceTamir Dresher
The document discusses Microsoft Azure Service Bus and its capabilities. Service Bus acts as an intermediary for applications to communicate across networks by relaying messages between clients and services. It supports various connectivity options and protocols to help address challenges like firewalls and internet connectivity. Service Bus provides scalability, availability, security and a registry for discovering services. Code examples are given to demonstrate creating client applications and services that communicate via Service Bus.
The document discusses adopting a serverless architecture to address pain points with a traditional architecture. Specifically, it notes that serverless allows processing without needing to run an always-on EC2 instance, easier management of resources for multiple tenants, lower cost parallel processing without expensive resource allocation, and lower costs overall. The new serverless architecture uses AWS Lambda for offloading analytics data hits from application servers to keep bills low, and uses Lambda functions triggered by SNS topics to send SMS messages through the standard SNS API.
This document provides an overview of clusterless serverless container deployment with AWS Fargate. It introduces concepts like containers, microservices, and container orchestration. It then discusses different AWS container services like ECS and EKS. The main topic is AWS Fargate, which is described as a fully managed container service that eliminates the need to manage clusters or nodes. It explains how Fargate works and its pricing model based on vCPU and memory resources used. A sample Fibonacci application deployed on Fargate is also briefly presented.
Structuring node.js projects - Seven Peaks Software (Node.JS Meetup 18 nov 2021)Seven Peaks Speaks
Denis is a professional programmer who has 12+ years of experience working in various startups!
Denis was dive deep into Structuring your Node.JS app, DI Container, Async Local Storage, Request handlers, Services, Unit of Work and Testing.
For more info about Seven Peaks Software:
https://lnkd.in/g2jMsDy
This document provides an overview of AWS Systems Manager, which is a collection of capabilities for configuring and managing Amazon EC2 instances, on-premises servers, and other AWS resources at scale. It addresses challenges like achieving compliance for instances, scalability, support for multi-cloud and hybrid environments, providing developer power, handling limited internet access, and low cost. Key capabilities of AWS Systems Manager include automation, compliance, running commands, patching, state management, and maintenance windows. The document provides examples of using it for bastion hosts, inventory, auditing changes, and patch compliance.
Performance Tales of Serverless - CloudNative London 2018☁️ Mikhail Shilkov
Function-as-a-Service "serverless" cloud offerings provide you with a super easy way to run custom code in response to events. One promise of FaaS model is the ability to scale without limits, up or down, whenever needed. But how does that work in practice? Can AWS Lambda handle thousands of messages per second? How fast can Azure Functions scale up under sudden heavy load? What kind of latency can you expect from Google Cloud Functions? During this session Mikhail will share with you short tales, each of them teaching a lesson about practical scalability of serverless applications. You will also explore the steps to evaluate whether your application profile is suitable for serverless today.
This document discusses cloud computing on AWS and Azure. It covers availability sets, blob storage, cloud backup, HDInsights, SQL as a service, file storage, load balancers, CDNs, firewalls, Kubernetes, cloud SQL, disk images, managed instance groups, and regional instance groups. It notes the good, bad, and ugly aspects of Azure's user interface as well as new beta interface. The document ends asking questions and saying goodbye.
The document discusses Amazon web services and cloud computing. It provides an overview of Amazon's services including Fulfillment, Associates, web search, Mechanical Turk, Payments, Infrastructure services like Simple Queue, SimpleDB, Simple Storage, and Elastic Compute Cloud. It also discusses cloud computing concepts and compares Amazon services to offerings from Google, Microsoft, Salesforce and others. The document considers potential applications and services that could be developed using these cloud platforms.
In this talk we will cover:
1. Using concurrency to maximize hardware (Elixir, Clojure, Haskell)
2. Serverless technologies for backend architecture (Amazon AWS Lambda, Microsoft Azure Cloud Functions)
3. BaaS – Backend as a Service (Google Firebase, etc)
This document discusses an AWS Premier event held in Osaka, Japan. It mentions EC2, cloudpack GL, AWS, RDS, and JAWS-UG which appear to be services, products or groups related to Amazon Web Services. The document provides high-level information about an AWS conference event but does not include many details.
Switching SaaS Hosting From dedicated virtual machines to container-based clu...AWS Germany
Presentation "Switching SaaS Hosting From dedicated virtual machines to container-based clusters" from Dr. Sven Ehlert at the AWS E-Business Web Day for windows applications. All videos and presentations can be found here: http://amzn.to/2ds3aMX
This document summarizes the key aspects of AWS orchestration for a company processing 6 billion requests per day across multiple services and regions. It discusses auto-scaling groups (ASGs) across 750 servers in 2 regions and 5 availability zones, with over 30 ASGs handling more than 20 API integrations. It also describes a homemade Redis autoscaling using master-slave replication across regions on spots and on-demand instances, handling 1.2 million operations per second. An event-driven architecture is implemented using a ØMQ mesh pipeline across ASGs for unidirectional data flow of 100k messages per second.
This document provides an introduction to defining cloud services using a declarative approach and YAML templates. It discusses how YAML can be used to describe services through key-value mappings and indentation. An example scenario is presented where a company wants to simplify application deployment on OpenStack. The document then presents conceptual models to meet the requirements of creating a repeatable infrastructure configuration and unique instantiations of that configuration. It demonstrates the structure of a YAML template with sections for description, parameters, resources, and outputs. Finally, it provides an example of using functions in templates to reference resources, parameters, and attributes and shows how resource dependencies can be captured.
Dray is a Go application that runs in a container and manages the execution and clean-up of task containers. It treats containers as single-purpose, short-lived tasks rather than long-running services. Dray groups related tasks into jobs that are posted as JSON documents. It marshals the output of one container to the input of the next, similar to UNIX pipes. An example job runs three tasks sequentially to deploy a Kubernetes cluster and install a remote agent on infrastructure provisioned by Panamax.
This document provides an introduction to AWS Lambda and the Serverless Framework. It defines serverless computing and discusses key differences between Platform as a Service (PaaS) and serverless models. AWS Lambda is introduced as Amazon's serverless compute platform, and other serverless platform providers are listed. The Serverless Framework is described as a development toolkit for building, managing and deploying serverless applications. Sample code and a serverless.yml configuration file are shown.
Serverless Comparison: AWS vs Azure vs Google vs IBMRightScale
This document provides a comparison of serverless computing platforms across AWS Lambda, Azure Functions, Google Cloud Functions, and IBM Cloud Functions. It covers aspects such as available languages, memory sizes and limits, scaling behavior, built-in triggers, pricing models, and example cost comparisons between serverless and traditional compute instances. The document finds that while all major clouds offer serverless computing, they differ in areas like languages supported, scaling performance, and pricing models, with no single option emerging as unanimously superior across all dimensions.
This document discusses deploying microservices on AWS. It begins by explaining what microservices are and then discusses hosting options on AWS including EC2, ECS, and Lambda. ECS is identified as the preferred option since it allows hosting containers with Docker. The document then covers deployment aspects like using source control with Git for multiple environments, building and testing code, deploying single services or entire clusters, live testing, and monitoring with alerts.
Serverless applications allow developers to focus on writing code without worrying about managing infrastructure. With serverless, there is zero administration, no provisioning is needed, and applications can scale seamlessly. Some key benefits of the serverless approach are that it allows for rapid innovation and focusing on business value. Serverless uses building blocks like AWS API Gateway and AWS Lambda. API Gateway handles authorization and scaling for APIs, while Lambda allows code to be run in a serverless environment and scales automatically based on usage.
This document discusses serverless architectures using AWS Lambda. It provides an overview of serverless computing and AWS Lambda, outlines some common use cases and challenges at OpsGenie, and describes their serverless technology stack. Some key points include:
- AWS Lambda allows running code without managing servers and only paying for the compute time used
- OpsGenie uses AWS Lambda along with other serverless AWS services like DynamoDB, S3, and API Gateway for various use cases including reporting, indexing data to Elasticsearch, and a service management pilot
- Challenges of using serverless include Java cold starts, proper monitoring without agents, and deployment processes
Serverless is a misnomer because there are servers. We will discuss what Serverless is, how it is part of an evolving abstraction, and what's on the horizon - InterCloud.
This document provides information about the author, including their roles as a technical program manager and co-founder of a startup called Hoozip. It then discusses various AWS services like Lambda, API Gateway, DynamoDB, and S3 that the author uses in their work with Hoozip to build scalable serverless backends. Specific use cases around property reports and real estate deals are outlined. Code examples are provided for building a simple API using Lambda and API Gateway. Pricing and best practices for Lambda are also covered.
Serverless architectures are promising and will play an important role in the coming years but the ecosystem around serverless is still pretty young. We have been operating Lambda based applications for about a year and faced several challenges. In this presentation we share these challenges and propose some solutions to work around them.
This talk will help you understand better how AWS help you to create a serverless solution using SQS, Lambda function, API gateway. This talk shows how to use it both in the developer field and DevOps
How to Build a Big Data Application: Serverless Editionecobold
Come learn how to build, launch, and scale a Big Data application in a serverless context. This is going to be an information packed meetup around Big Data processing, Lambda functions, Lambda Step functions, and everything that ties them together.
Big Data is something we're very passionate about. As the cost of servers have come down and the cost of software has become free, using data to drive your business has become much more obtainable to a larger group of companies. The serverless methodology has recently come in the scene, and it's proving to be just as transformational as cloud has been to the Big Data analytics space. We will be sharing some of our learnings and experiences over the last two years of working with Big Data in a serverless context. We will cover one or two examples of eventful Big Data processing, and the impact it can have on your business in terms of speed of analytics and cost savings to the bottom line.
A high level overview of MeteorJS, Amazon Web Services, and how to scale MeteorJS on Amazon's cloud to handle tends of thousands of concurrent websocket connections.
This document provides an overview of AWS (Amazon Web Services) for Java developers. It introduces the speaker and covers various AWS core services including S3, EC2, databases, Elastic Beanstalk, EC2 Container Service, tooling, billing, and monitoring. Serverless architectures using AWS Lambda are also discussed. The document concludes with demos of building serverless projects in Eclipse using AWS services like API Gateway and DynamoDB.
Microservices Manchester: Serverless Architectures By Rafal GancarzOpenCredo
It can be argued that the future of cloud computing is going to be serverless (and containerless) and cloud providers will be responsible for providing the runtime environment and all the building blocks needed for creating large scale, distributed systems. Rafal Gancarz presents how such a future could look like based on currently available AWS stack (Lambda, API Gateway, DynamoDB, S3, Kinesis, CloudWatch and more). Gatling is a scalable performance testing framework providing a rich and flexible DSL written in Scala. If you need to perf/load test a REST API or a web app you can use Gatling to generate a substantial amount of load and define your testing scenarios with ease. Rafal will provide an overview of the DSL and show how easy and productive using Gatling is, including a live demo.
About Rafal Gancarz
Rafal GanCarz is a Lead Consultant for OpenCredo having joined the company in 2014. Rafal is responsible for leading engagements for OpenCredo with its clients. He is a technologist with experience in high quality distributed systems, improving project delivery and building high performance Agile teams.
Mariusz Richtscheid: Architektura typu serverless wraz z terminem "Function as a Service" zyskują coraz większą popularność. To całkiem odmienne podejście do tworzenia aplikacji oraz ich wdrażania ma wiele zalet, ale musimy być też świadomi problemów, jakie się z nim wiążą. W trakcie prezentacji pokażę, w jaki sposób można zmodyfikować istniejącą aplikację Node.js tak, by wykorzystać zalety tej architektury.
Speaker: Raphael Londner, Developer Advocate, MongoDB
Speaker: Paul Sears, Partner Solutions Architect, Amazon Web Services
Level: 200 (Intermediate)
Track: Atlas
In this session, AWS Solutions Architect Paul Sears will provide an overview of AWS Lambda functions, including some key integration use cases with MongoDB Atlas. Developer Advocate Raphael Londner will walk you through how to code a Lambda function connected to MongoDB Atlas, with a specific focus on performance optimization. Raphael will then demonstrate how to orchestrate multiple Lambda functions inside a state machine built on top of AWS Step Functions.
What You Will Learn:
- Common use cases for which MongoDB Atlas + AWS Lambda help you boost developer productivity and minimize operational costs.
- How to write a performance-optimized Lambda function that re-uses MongoDB Atlas database connections across multiple calls in order to speed up queries.
- How AWS Step Functions can help you easily build application workflows to coordinate your Lambda functions.
AWS re:Invent re:Cap 2017 - A presentation sharing all the latest updates from the keynote presentations and product announcements put together by Canadian Amazon Web Services Premier Consulting Partner, TriNimbus Technologies, Inc. www.trinimbus.com
How to Build a Big Data Application: Serverless EditionLecole Cole
How to Build a Big Data Application: Serverless Edition
Come learn how do build, launch, and scale a Big Data application in a serverless context. This is going to be an information packed meetup around Big Data processing, Lambda functions, Lambda Step functions, and everything that ties them together.
Introduce AWS Lambda for newbie and Non-IT
อธิบาย ความเป็นมาของ Serverless และ AWS Lambda คืออะไร ดีอย่างไร เพื่อให้คนไม่รู้จักและคนที่ไม่ใช่ IT ได้เข้าใจง่ายๆ
Index
- What's Serverless
- What's AWS Lambda
- Working with AWS Lambda
- AWS Lambda Life-Cycle
- AWS Lambda Anatomy
- Beware Cold Start
- How to debug
- Do and Don't to implement
- Pricing structure and example
- Advantage/Disadvantage
Presentation is English Version
Blog is Thai Version : https://myifew.com/5166/understand-serverless-with-aws-lambda-for-newbie/
This document provides an overview and agenda for an AWS workshop. It introduces the presenter and covers various AWS services including compute (EC2, Lambda), storage (S3, EBS), databases (RDS), and serverless architecture. It also discusses AWS tooling, billing, security, and monitoring. The document concludes by pointing attendees to example labs they can complete to get hands-on experience with AWS.
Special Meetup Edition - TDX Bengaluru Meetup #52.pptxshyamraj55
We’re bringing the TDX energy to our community with 2 power-packed sessions:
🛠️ Workshop: MuleSoft for Agentforce
Explore the new version of our hands-on workshop featuring the latest Topic Center and API Catalog updates.
📄 Talk: Power Up Document Processing
Dive into smart automation with MuleSoft IDP, NLP, and Einstein AI for intelligent document workflows.
AI and Data Privacy in 2025: Global TrendsInData Labs
In this infographic, we explore how businesses can implement effective governance frameworks to address AI data privacy. Understanding it is crucial for developing effective strategies that ensure compliance, safeguard customer trust, and leverage AI responsibly. Equip yourself with insights that can drive informed decision-making and position your organization for success in the future of data privacy.
This infographic contains:
-AI and data privacy: Key findings
-Statistics on AI data privacy in the today’s world
-Tips on how to overcome data privacy challenges
-Benefits of AI data security investments.
Keep up-to-date on how AI is reshaping privacy standards and what this entails for both individuals and organizations.
TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...TrustArc
Most consumers believe they’re making informed decisions about their personal data—adjusting privacy settings, blocking trackers, and opting out where they can. However, our new research reveals that while awareness is high, taking meaningful action is still lacking. On the corporate side, many organizations report strong policies for managing third-party data and consumer consent yet fall short when it comes to consistency, accountability and transparency.
This session will explore the research findings from TrustArc’s Privacy Pulse Survey, examining consumer attitudes toward personal data collection and practical suggestions for corporate practices around purchasing third-party data.
Attendees will learn:
- Consumer awareness around data brokers and what consumers are doing to limit data collection
- How businesses assess third-party vendors and their consent management operations
- Where business preparedness needs improvement
- What these trends mean for the future of privacy governance and public trust
This discussion is essential for privacy, risk, and compliance professionals who want to ground their strategies in current data and prepare for what’s next in the privacy landscape.
What is Model Context Protocol(MCP) - The new technology for communication bw...Vishnu Singh Chundawat
The MCP (Model Context Protocol) is a framework designed to manage context and interaction within complex systems. This SlideShare presentation will provide a detailed overview of the MCP Model, its applications, and how it plays a crucial role in improving communication and decision-making in distributed systems. We will explore the key concepts behind the protocol, including the importance of context, data management, and how this model enhances system adaptability and responsiveness. Ideal for software developers, system architects, and IT professionals, this presentation will offer valuable insights into how the MCP Model can streamline workflows, improve efficiency, and create more intuitive systems for a wide range of use cases.
Noah Loul Shares 5 Steps to Implement AI Agents for Maximum Business Efficien...Noah Loul
Artificial intelligence is changing how businesses operate. Companies are using AI agents to automate tasks, reduce time spent on repetitive work, and focus more on high-value activities. Noah Loul, an AI strategist and entrepreneur, has helped dozens of companies streamline their operations using smart automation. He believes AI agents aren't just tools—they're workers that take on repeatable tasks so your human team can focus on what matters. If you want to reduce time waste and increase output, AI agents are the next move.
#StandardsGoals for 2025: Standards & certification roundup - Tech Forum 2025BookNet Canada
Book industry standards are evolving rapidly. In the first part of this session, we’ll share an overview of key developments from 2024 and the early months of 2025. Then, BookNet’s resident standards expert, Tom Richardson, and CEO, Lauren Stewart, have a forward-looking conversation about what’s next.
Link to recording, transcript, and accompanying resource: https://bnctechforum.ca/sessions/standardsgoals-for-2025-standards-certification-roundup/
Presented by BookNet Canada on May 6, 2025 with support from the Department of Canadian Heritage.
Dev Dives: Automate and orchestrate your processes with UiPath MaestroUiPathCommunity
This session is designed to equip developers with the skills needed to build mission-critical, end-to-end processes that seamlessly orchestrate agents, people, and robots.
📕 Here's what you can expect:
- Modeling: Build end-to-end processes using BPMN.
- Implementing: Integrate agentic tasks, RPA, APIs, and advanced decisioning into processes.
- Operating: Control process instances with rewind, replay, pause, and stop functions.
- Monitoring: Use dashboards and embedded analytics for real-time insights into process instances.
This webinar is a must-attend for developers looking to enhance their agentic automation skills and orchestrate robust, mission-critical processes.
👨🏫 Speaker:
Andrei Vintila, Principal Product Manager @UiPath
This session streamed live on April 29, 2025, 16:00 CET.
Check out all our upcoming Dev Dives sessions at https://community.uipath.com/dev-dives-automation-developer-2025/.
Enhancing ICU Intelligence: How Our Functional Testing Enabled a Healthcare I...Impelsys Inc.
Impelsys provided a robust testing solution, leveraging a risk-based and requirement-mapped approach to validate ICU Connect and CritiXpert. A well-defined test suite was developed to assess data communication, clinical data collection, transformation, and visualization across integrated devices.
Quantum Computing Quick Research Guide by Arthur MorganArthur Morgan
This is a Quick Research Guide (QRG).
QRGs include the following:
- A brief, high-level overview of the QRG topic.
- A milestone timeline for the QRG topic.
- Links to various free online resource materials to provide a deeper dive into the QRG topic.
- Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic.
QRGs planned for the series:
- Artificial Intelligence QRG
- Quantum Computing QRG
- Big Data Analytics QRG
- Spacecraft Guidance, Navigation & Control QRG (coming 2026)
- UK Home Computing & The Birth of ARM QRG (coming 2027)
Any questions or comments?
- Please contact Arthur Morgan at [email protected].
100% human made.
Massive Power Outage Hits Spain, Portugal, and France: Causes, Impact, and On...Aqusag Technologies
In late April 2025, a significant portion of Europe, particularly Spain, Portugal, and parts of southern France, experienced widespread, rolling power outages that continue to affect millions of residents, businesses, and infrastructure systems.
UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager APIUiPathCommunity
Join this UiPath Community Berlin meetup to explore the Orchestrator API, Swagger interface, and the Test Manager API. Learn how to leverage these tools to streamline automation, enhance testing, and integrate more efficiently with UiPath. Perfect for developers, testers, and automation enthusiasts!
📕 Agenda
Welcome & Introductions
Orchestrator API Overview
Exploring the Swagger Interface
Test Manager API Highlights
Streamlining Automation & Testing with APIs (Demo)
Q&A and Open Discussion
Perfect for developers, testers, and automation enthusiasts!
👉 Join our UiPath Community Berlin chapter: https://community.uipath.com/berlin/
This session streamed live on April 29, 2025, 18:00 CET.
Check out all our upcoming UiPath Community sessions at https://community.uipath.com/events/.
Spark is a powerhouse for large datasets, but when it comes to smaller data workloads, its overhead can sometimes slow things down. What if you could achieve high performance and efficiency without the need for Spark?
At S&P Global Commodity Insights, having a complete view of global energy and commodities markets enables customers to make data-driven decisions with confidence and create long-term, sustainable value. 🌍
Explore delta-rs + CDC and how these open-source innovations power lightweight, high-performance data applications beyond Spark! 🚀
AI Changes Everything – Talk at Cardiff Metropolitan University, 29th April 2...Alan Dix
Talk at the final event of Data Fusion Dynamics: A Collaborative UK-Saudi Initiative in Cybersecurity and Artificial Intelligence funded by the British Council UK-Saudi Challenge Fund 2024, Cardiff Metropolitan University, 29th April 2025
https://alandix.com/academic/talks/CMet2025-AI-Changes-Everything/
Is AI just another technology, or does it fundamentally change the way we live and think?
Every technology has a direct impact with micro-ethical consequences, some good, some bad. However more profound are the ways in which some technologies reshape the very fabric of society with macro-ethical impacts. The invention of the stirrup revolutionised mounted combat, but as a side effect gave rise to the feudal system, which still shapes politics today. The internal combustion engine offers personal freedom and creates pollution, but has also transformed the nature of urban planning and international trade. When we look at AI the micro-ethical issues, such as bias, are most obvious, but the macro-ethical challenges may be greater.
At a micro-ethical level AI has the potential to deepen social, ethnic and gender bias, issues I have warned about since the early 1990s! It is also being used increasingly on the battlefield. However, it also offers amazing opportunities in health and educations, as the recent Nobel prizes for the developers of AlphaFold illustrate. More radically, the need to encode ethics acts as a mirror to surface essential ethical problems and conflicts.
At the macro-ethical level, by the early 2000s digital technology had already begun to undermine sovereignty (e.g. gambling), market economics (through network effects and emergent monopolies), and the very meaning of money. Modern AI is the child of big data, big computation and ultimately big business, intensifying the inherent tendency of digital technology to concentrate power. AI is already unravelling the fundamentals of the social, political and economic world around us, but this is a world that needs radical reimagining to overcome the global environmental and human challenges that confront us. Our challenge is whether to let the threads fall as they may, or to use them to weave a better future.
2. PARTE I
• O que é escalabilidade?
• Visão geral do Elastic Benstalk
• Visão geral do Lambda
• Prós, Contras e comparativos entre os dois
• Considerações importantes de escalabilidade
• Banco de dados numa aplicação escalável
4. ESCALABILIDADE
“Scalability is the property of a system
to handle a growing amount of work
by adding resources to the system”
• Geographic scalability: The ability to
maintain effectiveness during
expansion from a local area to a
larger region.
• Load scalability: The ability for
a distributed system to expand and
contract to accommodate heavier or
lighter loads, including, the ease
with which a system or component
can be modified, added, or
removed, to accommodate changing
loads.
6. AWS ELASTIC BEANSTALK
• “AWS Elastic Beanstalk is an easy-to-use service for deploying and
scaling web applications and services”
• “You can simply upload your code and Elastic Beanstalk automatically
handles the deployment, from capacity provisioning, load balancing,
auto-scaling to application health monitoring. At the same time, you
retain full control over the AWS resources powering your application
and can access the underlying resources at any time.”
• “There is no additional charge for Elastic Beanstalk - you pay only for
the AWS resources needed to store and run your applications.”
14. ELASTIC BEANSTALK
PRÓS
• Variedade de linguagens e
docker
• Deploy, balanceamento, controle
de versão, escalabilidade
• Deploy muito fácil
• Tipos de deploy
• Altamento configurável
• Custo 0 (paga estrutura por trás)
CONTRAS
• Muito sensível a falhas de
deploy
• Configuração inicial complexa
• Busca por erros difícil
• Deploy pode demorar muito
• Limitado em alguns pontos
• Versões das linguages demoram
• Permissionamento
15. LAMBDA
• “AWS Lambda lets you run code without provisioning or
managing servers. You pay only for the compute time you
consume.”
• “With Lambda, you can run code for virtually any type of
application or backend service - all with zero administration.
Just upload your code and Lambda takes care of everything
required to run and scale your code with high availability. You
can set up your code to automatically trigger from other AWS
services or call it directly from any web or mobile app.”
19. LAMBDA
PRÓS
• Custo reduzido para baixo
tráfego
• Sem necessidade de
gerenciamento
• Rápido desenvolvimento (1
função)
• Alta escalabilidade
• Deploy independente por
função
CONTRAS
• Alto custo para grande tráfego
• Sem controle sobre ambiente
• Arquitetura complexa
• Quantidade de funções aumenta rápido
• DoS (1000 concorrências)
• Duração (máximo de 15 minutos)
• Cold Starts
• Monitorar / debugar (onde achar um erro entre
300 funções)
27. DATABASES
• Pontos obrigatórios
1. Replicação para outras regiões com baixa latência
2. Serviço gerenciado
3. Baixo custo
• Desejáveis
1. NoSQL para evitar migrations
2. Global Write
28. DATABASES
MySQL Aurora MongoDB DynamoDB
Replicação X X X X
Gerenciado X X X X
NoSQL X X
Global Write +- X
Facilidade de uso X X X