Stephen Liedig: Building Serverless Backends with AWS Lambda and API GatewaySteve Androulakis
Stephen Liedig (Amazon Web Services) is a Public Sector Solutions Architect at AWS working closely with local and state governments, educational institutions, and non-profit organisations across Australia and New Zealand to design, and deliver, highly secure, scalable, reliable and fault-tolerant architectures in the AWS Cloud while sharing best practices and current trends, with a specific focus on DevOps, messaging, and serverless technologies.
Machine learning at scale with aws sage makerPhilipBasford
The adoption of Machine Learning (ML) has boomed over the last 12 months; from initial prototypes and now into fully managed production workloads that embed ML in critical areas of both start-up and enterprise businesses. These workloads need to be highly available, elastic, have low latency, be very secure, and also cost efficient.
The corner stone of this is AWS SageMaker. AWS SageMaker offers a great platform for Machine Learning that includes one-click deployment of models for inference using AWS SageMaker Endpoints. This talk will provide advice and recommendations on how to use cases AWS SageMaker Endpoints as there is an awful lot more to AWS SageMaker Endpoints than meets the eye. During this talk we will look how to use AWS SageMaker Endpoints, how to build a custom model; look at how to scale them using Auto Scaling, look at canary style deployments, how to monitor them with CloudWatch. We will also look at how AWS SageMaker Endpoints can be used within serverless APIs with real-time observations using AWS X-Ray.
Cost Effective Rendering in the Cloud with Spot InstancesAmazon Web Services
Usman Shakeel from Amazon Web Services, explains to us how to use AWS Spot Instances to implement low cost video rendering applications and workflows.
This presentation was delivered during the AWS Toronto Media and Entertainment Symposium
Serverless on AWS : Understanding the hard parts at Froscon 2019Vadym Kazulkin
In unserem Vortrag tauchen wir tiefer in die Serverless-Welt ein und zeigen wie eine produktionsreife Serverless-Anwendung mithilfe von AWS-Cloud mit dem Technologie-Stack API Gateway, SNS, Lambda and DynamoDB aufgebaut werden kann. Dabei gehen wir auf die Herausforderungen der jeweiligen Services ein, wie "cold start" bei Lamda oder "provisioned throughput" und "adaptice capacity" bei DynamoDB. Dabei zeigen wir, welche Strategien und Wege es gibt, damit umzugehen. Außerdem behandeln wir solche Themen wie Implementierung von Aggregationslogik und (Scheduled) Auto Scaling bei DynamoDB. Am Ende werfen wir einen Blick in die Zukunft und sprechen über die erste relationale serverless Datenbank "Aurora Serverless"
Stephen Liedig: Building Serverless Backends with AWS Lambda and API GatewaySteve Androulakis
Stephen Liedig (Amazon Web Services) is a Public Sector Solutions Architect at AWS working closely with local and state governments, educational institutions, and non-profit organisations across Australia and New Zealand to design, and deliver, highly secure, scalable, reliable and fault-tolerant architectures in the AWS Cloud while sharing best practices and current trends, with a specific focus on DevOps, messaging, and serverless technologies.
Machine learning at scale with aws sage makerPhilipBasford
The adoption of Machine Learning (ML) has boomed over the last 12 months; from initial prototypes and now into fully managed production workloads that embed ML in critical areas of both start-up and enterprise businesses. These workloads need to be highly available, elastic, have low latency, be very secure, and also cost efficient.
The corner stone of this is AWS SageMaker. AWS SageMaker offers a great platform for Machine Learning that includes one-click deployment of models for inference using AWS SageMaker Endpoints. This talk will provide advice and recommendations on how to use cases AWS SageMaker Endpoints as there is an awful lot more to AWS SageMaker Endpoints than meets the eye. During this talk we will look how to use AWS SageMaker Endpoints, how to build a custom model; look at how to scale them using Auto Scaling, look at canary style deployments, how to monitor them with CloudWatch. We will also look at how AWS SageMaker Endpoints can be used within serverless APIs with real-time observations using AWS X-Ray.
Cost Effective Rendering in the Cloud with Spot InstancesAmazon Web Services
Usman Shakeel from Amazon Web Services, explains to us how to use AWS Spot Instances to implement low cost video rendering applications and workflows.
This presentation was delivered during the AWS Toronto Media and Entertainment Symposium
Serverless on AWS : Understanding the hard parts at Froscon 2019Vadym Kazulkin
In unserem Vortrag tauchen wir tiefer in die Serverless-Welt ein und zeigen wie eine produktionsreife Serverless-Anwendung mithilfe von AWS-Cloud mit dem Technologie-Stack API Gateway, SNS, Lambda and DynamoDB aufgebaut werden kann. Dabei gehen wir auf die Herausforderungen der jeweiligen Services ein, wie "cold start" bei Lamda oder "provisioned throughput" und "adaptice capacity" bei DynamoDB. Dabei zeigen wir, welche Strategien und Wege es gibt, damit umzugehen. Außerdem behandeln wir solche Themen wie Implementierung von Aggregationslogik und (Scheduled) Auto Scaling bei DynamoDB. Am Ende werfen wir einen Blick in die Zukunft und sprechen über die erste relationale serverless Datenbank "Aurora Serverless"
Technical 101: AWS Innovation at Scale
This session, gives an insider view of some the innovations that help make the AWS Cloud unique. He will show examples of AWS networking innovations from the interregional network backbone, through custom routers and networking rotocol stack, all the way down to individual servers. He will show examples from AWS server hardware, storage, and power distribution and then, up the stack, in high scale streaming data processing. Rodney will also dive into fundamental database work AWS is delivering to open up scaling and performance limits, reduce costs, and eliminate much of the administrative burden of managing databases. Join this session and walk away with a deeper understanding of the underlying innovations powering the cloud.
Speaker: Rodeny Haywood, Manager Solutions Architecture, Amazon Web Services
Everything fails all the time! A quote repeated by many everyday. How does it feel when things fail in production? How do you recover from such situations? How can you make sure they don’t repeat? All these discussed with real production incidents and the measures taken to mitigate such failures. We will also look at few of the most common failure possibilities in a serverless ecosystem.
Remember, when everything fails all the time, you must learn something everyday to be operational all the time!
GPU Renderfarm with Integrated Asset Management & Production System (AMPS)Budianto Tandianus
Was presented in GPU Technology Conference 2014 by Dr. Chen Quan.
The presentation recording and the definitive version of the slide can be downloaded from : http://on-demand-gtc.gputechconf.com/gtcnew/on-demand-gtc.php?searchByKeyword=S4356&searchItems=session_id&submit=
AWS re:Invent 2016: ElastiCache Deep Dive: Best Practices and Usage Patterns ...Amazon Web Services
In this session, we provide a peek behind the scenes to learn about Amazon ElastiCache's design and architecture. See common design patterns with our Redis and Memcached offerings and how customers have used them for in-memory operations to reduce latency and improve application throughput. During this session, we review ElastiCache best practices, design patterns, and anti-patterns.
AWS re:Invent 2016: Best Practices for Data Warehousing with Amazon Redshift ...Amazon Web Services
Analyzing big data quickly and efficiently requires a data warehouse optimized to handle and scale for large datasets. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it simple and cost-effective to analyze all of your data for a fraction of the cost of traditional data warehouses. In this session, we take an in-depth look at data warehousing with Amazon Redshift for big data analytics. We cover best practices to take advantage of Amazon Redshift's columnar technology and parallel processing capabilities to deliver high throughput and query performance. We also discuss how to design optimal schemas, load data efficiently, and use work load management.
Pragmatic Approach to Workload Migrations - London Summit Enteprise Track RePlayAmazon Web Services
Migrating a portfolio of legacy applications to AWS cloud infrastructure requires careful planning as each phase needs balancing between risk tolerance and the speed of migration. This session will present a set of successful best practices, tools and techniques that help migration speed of delivery and increase success rate. We will also cover the complete lifecycle of an application portfolio migration including a special focus on how to organise and conduct the assessment and identify elements that can benefit from cloud architecture.
AWS re:Invent 2016: Optimizing workloads in SAP HANA with Amazon EC2 X1 Insta...Amazon Web Services
AWS and SAP have worked together closely to certify the AWS platform so that companies of all sizes can fully realize all the benefits of the SAP HANA in-memory database platform on the AWS cloud. By placing SAP systems in the cloud, organizations are achieving greater agility, flexibility, and cost efficiency while saving resources to focus on their core businesses. We will discuss recent SAP and AWS innovations including the Amazon EC2 X1 instance type that offers up to 2TB of RAM, and dive into features of the AWS platform that bring significant flexibility to SAP HANA deployments.
AWS re:Invent 2016: Design, Deploy, and Optimize Microsoft SharePoint on AWS ...Amazon Web Services
AWS can help you rapidly deploy and scale your Microsoft SharePoint environment to help you collaborate more efficiently and cost-effectively. This session reviews architectural considerations for building a SharePoint deployment on AWS, best practices to ensure optimal performance, how to leverage multiple Availability Zones for high availability and disaster recovery, and how to integrate with Microsoft Active Directory. We will also look at new Quick Start guides, AWS CloudFormation templates, and other tools that dramatically reduce the time to deployment.
AWS re:Invent 2016: Building HPC Clusters as Code in the (Almost) Infinite Cl...Amazon Web Services
Every day, the computing power of high-performance computing (HPC) clusters helps scientists make breakthroughs, such as proving the existence of gravitational waves and screening new compounds for new drugs. Yet building HPC clusters is out of reach for most organizations, due to the upfront hardware costs and ongoing operational expenses. Now the speed of innovation is only bound by your imagination, not your budget. Researchers can run one cluster for 10,000 hours or 10,000 clusters for one hour anytime, from anywhere, and both cost the same in the cloud. And with the availability of Public Data Sets in Amazon S3, petabyte scale data is instantly accessible in the cloud. Attend and learn how to build HPC clusters on the fly, leverage Amazon’s Spot market pricing to minimize the cost of HPC jobs, and scale HPC jobs on a small budget, using all the same tools you use today, and a few new ones too.
AWS Summit 2014 Melbourne - Breakout 3
A behind the scenes look at key aspects of the AWS infrastructure deployments. Some of the true differences between a cloud infrastructure design and conventional enterprise infrastructure deployment and why the cloud fundamentally changes application deployment speed, economics, and provides more and better tools for delivering high reliability applications. Few companies can afford to have a datacenter in every region in which they serve customers or have employees. Even fewer can afford to have multiple datacenter in each region where they have a presence. Even fewer can afford to invest in custom optimized network, server, storage, monitoring, cooling, and power distribution systems and software. We'll look more closely at these systems, how they work, how they are scaled, and the advantages they bring to customers.
Presenter: Rodney Haywood, Manager, Solutions Architects, Amazon Web Services
AWS re:Invent 2016: High Performance Computing on AWS (CMP207)Amazon Web Services
High performance computing in the cloud is enabling high scale compute- and graphics-intensive workloads across industries, ranging from aerospace, automotive, and manufacturing to life sciences, financial services, and energy. AWS provides application developers and end users with unprecedented computational power for massively parallel applications, in areas such as large-scale fluid and materials simulations, 3D content rendering, financial computing, and deep learning. This session provides an overview of HPC capabilities on AWS, describes the newest generations of accelerated computing instances (including P2), as well as highlighting customer and partner use-cases across industries.
Attendees learn about best practices for running HPC workflows in the cloud, including graphical pre- and post-processing, workflow automation, and optimization. Attendees also learn about new and emerging HPC use cases: in particular, deep learning training and inference, large-scale simulations, and high performance data analytics.
Intended for customers who have (or will have) thousands of instances on AWS, this session is about reducing the complexity of managing costs for these large fleets so they run efficiently. Attendees will learn about common roadblocks that prevent large customers from cost optimizing, tools they can use to efficiently remove those roadblocks, and techniques to monitor their rate of cost optimization. The session will include a case study that will talk in detail about the millions of dollars saved using these techniques. Customers will learn about a range of templates they can use to quickly implement these techniques, and also partners who can help them implement these templates.
Top 5 Ways to Optimize for Cost Efficiency with the CloudAmazon Web Services
This session covers the Top 5 ways you can reduce the cost of your workloads in the AWS Cloud including high-level architectures and when to use and our numerous pricing options for components of those architectures.
We walk through several examples to illustrate when to use each feature, configuration or pricing option. This session is aimed at technically savvy managers and engineers who need to reduce their cloud spending.
Reasons to attend:
Learn about Reserved Instances, On-Demand Instances and Spot Instances.
Discover ways of running more for less in Amazon EC2.
If you are already running a workload in AWS, attend this webinar to learn how to run the same workload at reduced costs.
Amazon EC2 Container Service is a highly scalable, fast, container management service that makes it easy to run, stop, and manage Docker containers on a cluster of Amazon EC2 instances. Part of ECS is Amazon EC2 Container Registry (ECR). Amazon ECR is a fully-managed Docker container registry that makes it easy for developers to store, manage, and deploy Docker container images. This session will describe how you can use ECS and ECR for your applications.
Speaker: Sascha Möllering, Solutions Architect, AWS
Migration Recipes for Success - AWS Summit Cape Town 2017 Amazon Web Services
Now that you have earmarked workloads for migration, it's time to look at the various tools and methodologies that are available to help customers shift applications to AWS. This session highlights some of the key AWS tools, services and approaches that organisations are using to successfully migrate to the cloud.
AWS Speaker: Sven Hansen, Solution Architect - Amazon Web Services
Customer Speaker: Pieter Breed – Core Platform Engineer Zoona
Cloud Migration, Application Modernization, and Security Tom Laszewski
As AWS continues to expand, enterprise customers are looking to our partner ecosystem to assist in migrating their workloads to the cloud. This session describes the challenges, lessons learned and best practices for large scale application migrations. We will use real examples from our consulting partners and AWS Professional Services to illustrate how to move workloads to the cloud while modernizing the associated applications to take advantage of AWS’ unique benefits. We will also dive into how to use an array of AWS services and features to improve a customer’s security posture as they are migrating and once they are up and running in the cloud
Aws Summit Berlin 2013 - Understanding database options on AWSAWS Germany
With AWS you can choose the right database for the right job. Given the myriad of choices, from relational databases to non-relational stores, this session will profile details and examples of some of the choices available to you (MySQL, RDS, Elasticache, Redis, Cassandra, MongoDB and DynamoDB), with details on real world deployments from customers using Amazon RDS, ElastiCache and DynamoDB.
Technical 101: AWS Innovation at Scale
This session, gives an insider view of some the innovations that help make the AWS Cloud unique. He will show examples of AWS networking innovations from the interregional network backbone, through custom routers and networking rotocol stack, all the way down to individual servers. He will show examples from AWS server hardware, storage, and power distribution and then, up the stack, in high scale streaming data processing. Rodney will also dive into fundamental database work AWS is delivering to open up scaling and performance limits, reduce costs, and eliminate much of the administrative burden of managing databases. Join this session and walk away with a deeper understanding of the underlying innovations powering the cloud.
Speaker: Rodeny Haywood, Manager Solutions Architecture, Amazon Web Services
Everything fails all the time! A quote repeated by many everyday. How does it feel when things fail in production? How do you recover from such situations? How can you make sure they don’t repeat? All these discussed with real production incidents and the measures taken to mitigate such failures. We will also look at few of the most common failure possibilities in a serverless ecosystem.
Remember, when everything fails all the time, you must learn something everyday to be operational all the time!
GPU Renderfarm with Integrated Asset Management & Production System (AMPS)Budianto Tandianus
Was presented in GPU Technology Conference 2014 by Dr. Chen Quan.
The presentation recording and the definitive version of the slide can be downloaded from : http://on-demand-gtc.gputechconf.com/gtcnew/on-demand-gtc.php?searchByKeyword=S4356&searchItems=session_id&submit=
AWS re:Invent 2016: ElastiCache Deep Dive: Best Practices and Usage Patterns ...Amazon Web Services
In this session, we provide a peek behind the scenes to learn about Amazon ElastiCache's design and architecture. See common design patterns with our Redis and Memcached offerings and how customers have used them for in-memory operations to reduce latency and improve application throughput. During this session, we review ElastiCache best practices, design patterns, and anti-patterns.
AWS re:Invent 2016: Best Practices for Data Warehousing with Amazon Redshift ...Amazon Web Services
Analyzing big data quickly and efficiently requires a data warehouse optimized to handle and scale for large datasets. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it simple and cost-effective to analyze all of your data for a fraction of the cost of traditional data warehouses. In this session, we take an in-depth look at data warehousing with Amazon Redshift for big data analytics. We cover best practices to take advantage of Amazon Redshift's columnar technology and parallel processing capabilities to deliver high throughput and query performance. We also discuss how to design optimal schemas, load data efficiently, and use work load management.
Pragmatic Approach to Workload Migrations - London Summit Enteprise Track RePlayAmazon Web Services
Migrating a portfolio of legacy applications to AWS cloud infrastructure requires careful planning as each phase needs balancing between risk tolerance and the speed of migration. This session will present a set of successful best practices, tools and techniques that help migration speed of delivery and increase success rate. We will also cover the complete lifecycle of an application portfolio migration including a special focus on how to organise and conduct the assessment and identify elements that can benefit from cloud architecture.
AWS re:Invent 2016: Optimizing workloads in SAP HANA with Amazon EC2 X1 Insta...Amazon Web Services
AWS and SAP have worked together closely to certify the AWS platform so that companies of all sizes can fully realize all the benefits of the SAP HANA in-memory database platform on the AWS cloud. By placing SAP systems in the cloud, organizations are achieving greater agility, flexibility, and cost efficiency while saving resources to focus on their core businesses. We will discuss recent SAP and AWS innovations including the Amazon EC2 X1 instance type that offers up to 2TB of RAM, and dive into features of the AWS platform that bring significant flexibility to SAP HANA deployments.
AWS re:Invent 2016: Design, Deploy, and Optimize Microsoft SharePoint on AWS ...Amazon Web Services
AWS can help you rapidly deploy and scale your Microsoft SharePoint environment to help you collaborate more efficiently and cost-effectively. This session reviews architectural considerations for building a SharePoint deployment on AWS, best practices to ensure optimal performance, how to leverage multiple Availability Zones for high availability and disaster recovery, and how to integrate with Microsoft Active Directory. We will also look at new Quick Start guides, AWS CloudFormation templates, and other tools that dramatically reduce the time to deployment.
AWS re:Invent 2016: Building HPC Clusters as Code in the (Almost) Infinite Cl...Amazon Web Services
Every day, the computing power of high-performance computing (HPC) clusters helps scientists make breakthroughs, such as proving the existence of gravitational waves and screening new compounds for new drugs. Yet building HPC clusters is out of reach for most organizations, due to the upfront hardware costs and ongoing operational expenses. Now the speed of innovation is only bound by your imagination, not your budget. Researchers can run one cluster for 10,000 hours or 10,000 clusters for one hour anytime, from anywhere, and both cost the same in the cloud. And with the availability of Public Data Sets in Amazon S3, petabyte scale data is instantly accessible in the cloud. Attend and learn how to build HPC clusters on the fly, leverage Amazon’s Spot market pricing to minimize the cost of HPC jobs, and scale HPC jobs on a small budget, using all the same tools you use today, and a few new ones too.
AWS Summit 2014 Melbourne - Breakout 3
A behind the scenes look at key aspects of the AWS infrastructure deployments. Some of the true differences between a cloud infrastructure design and conventional enterprise infrastructure deployment and why the cloud fundamentally changes application deployment speed, economics, and provides more and better tools for delivering high reliability applications. Few companies can afford to have a datacenter in every region in which they serve customers or have employees. Even fewer can afford to have multiple datacenter in each region where they have a presence. Even fewer can afford to invest in custom optimized network, server, storage, monitoring, cooling, and power distribution systems and software. We'll look more closely at these systems, how they work, how they are scaled, and the advantages they bring to customers.
Presenter: Rodney Haywood, Manager, Solutions Architects, Amazon Web Services
AWS re:Invent 2016: High Performance Computing on AWS (CMP207)Amazon Web Services
High performance computing in the cloud is enabling high scale compute- and graphics-intensive workloads across industries, ranging from aerospace, automotive, and manufacturing to life sciences, financial services, and energy. AWS provides application developers and end users with unprecedented computational power for massively parallel applications, in areas such as large-scale fluid and materials simulations, 3D content rendering, financial computing, and deep learning. This session provides an overview of HPC capabilities on AWS, describes the newest generations of accelerated computing instances (including P2), as well as highlighting customer and partner use-cases across industries.
Attendees learn about best practices for running HPC workflows in the cloud, including graphical pre- and post-processing, workflow automation, and optimization. Attendees also learn about new and emerging HPC use cases: in particular, deep learning training and inference, large-scale simulations, and high performance data analytics.
Intended for customers who have (or will have) thousands of instances on AWS, this session is about reducing the complexity of managing costs for these large fleets so they run efficiently. Attendees will learn about common roadblocks that prevent large customers from cost optimizing, tools they can use to efficiently remove those roadblocks, and techniques to monitor their rate of cost optimization. The session will include a case study that will talk in detail about the millions of dollars saved using these techniques. Customers will learn about a range of templates they can use to quickly implement these techniques, and also partners who can help them implement these templates.
Top 5 Ways to Optimize for Cost Efficiency with the CloudAmazon Web Services
This session covers the Top 5 ways you can reduce the cost of your workloads in the AWS Cloud including high-level architectures and when to use and our numerous pricing options for components of those architectures.
We walk through several examples to illustrate when to use each feature, configuration or pricing option. This session is aimed at technically savvy managers and engineers who need to reduce their cloud spending.
Reasons to attend:
Learn about Reserved Instances, On-Demand Instances and Spot Instances.
Discover ways of running more for less in Amazon EC2.
If you are already running a workload in AWS, attend this webinar to learn how to run the same workload at reduced costs.
Amazon EC2 Container Service is a highly scalable, fast, container management service that makes it easy to run, stop, and manage Docker containers on a cluster of Amazon EC2 instances. Part of ECS is Amazon EC2 Container Registry (ECR). Amazon ECR is a fully-managed Docker container registry that makes it easy for developers to store, manage, and deploy Docker container images. This session will describe how you can use ECS and ECR for your applications.
Speaker: Sascha Möllering, Solutions Architect, AWS
Migration Recipes for Success - AWS Summit Cape Town 2017 Amazon Web Services
Now that you have earmarked workloads for migration, it's time to look at the various tools and methodologies that are available to help customers shift applications to AWS. This session highlights some of the key AWS tools, services and approaches that organisations are using to successfully migrate to the cloud.
AWS Speaker: Sven Hansen, Solution Architect - Amazon Web Services
Customer Speaker: Pieter Breed – Core Platform Engineer Zoona
Cloud Migration, Application Modernization, and Security Tom Laszewski
As AWS continues to expand, enterprise customers are looking to our partner ecosystem to assist in migrating their workloads to the cloud. This session describes the challenges, lessons learned and best practices for large scale application migrations. We will use real examples from our consulting partners and AWS Professional Services to illustrate how to move workloads to the cloud while modernizing the associated applications to take advantage of AWS’ unique benefits. We will also dive into how to use an array of AWS services and features to improve a customer’s security posture as they are migrating and once they are up and running in the cloud
Aws Summit Berlin 2013 - Understanding database options on AWSAWS Germany
With AWS you can choose the right database for the right job. Given the myriad of choices, from relational databases to non-relational stores, this session will profile details and examples of some of the choices available to you (MySQL, RDS, Elasticache, Redis, Cassandra, MongoDB and DynamoDB), with details on real world deployments from customers using Amazon RDS, ElastiCache and DynamoDB.
Serverless design considerations for Cloud Native workloadsTensult
We have built a news website with more than a billion views per month and we are sharing the learnings from that experience covering Serverless architectures, Design considerations, and Gotchas.
With AWS Lambda, you can easily build scalable microservices for mobile, web, and IoT applications or respond to events from other AWS services without managing infrastructure. In this session, you’ll see demonstrations and hear more about newly launched features. We’ll show you how to use Lambda to build web, mobile, or IoT backends and voice-enabled apps, and we'll show you how to extend both AWS and third party services by triggering Lambda functions. We’ll also provide productivity and performance tips for getting the most out of your Lambda functions and show how cloud native architectures use Lambda to eliminate “cold servers” and excess capacity without sacrificing scalability or responsiveness.
If you could not be one of the 60,000+ in attendance at Amazon AWS re:Invent, the yearly Amazon Cloud Conference, get the 411 on what major announcements that were made in Las Vegas. This presentation covers new AWS services & products, exciting announcements, and updated features.
Get the EDGE to scale: Using Cloudfront along with edge compute to scale your...Amazon Web Services
You could use Cloud Front to deliver pages faster, however, customized processing still required requests to be forwarded back to compute resources at centralized servers, which may slow down the end user experience. This session shows how a combination of Cloud Front, and edge compute can help you scale out your resources in a much more effective way than you think.
Speaker: Anil Nair
Solution Architect, Amazon India
Venture capitalist Matt Ocko’s 20-year track record of success in the startup world has given him unique insight into how AWS has changed the venture financing process. In this session, you’ll learn about industries susceptible to disruption by AWS-based startups, and where VCs are willing to take new risks on those startups, including the heavily-regulated medical, government, financial, and industrial sectors. Matt will talk about how new, supercomputing startups are now possible because of AWS technologies. Hear about how using AWS technologies can actually reduce risk – and reduce time to customer penetration – from a VC perspective, and how to go from ‘AWS to Series A’ in 5 easy pieces.
This session introduces Lambda@Edge, a new AWS Lambda feature that allows developers to perform simple computations at AWS edge locations in response to CloudFront events. This will be of interest to developers who want to build low-latency, customized web experiences. We cover product functionality and details of the programming model, and we walk through potential use cases.
With AWS Lambda, you can easily build scalable microservices for mobile, web, and IoT applications or respond to events from other AWS services without managing infrastructure. In this session, you’ll see demonstrations and hear more about newly launched features. We’ll show you how to use Lambda to build web, mobile, or IoT backends and voice-enabled apps, and we'll show you how to extend both AWS and third party services by triggering Lambda functions. We’ll also provide productivity and performance tips for getting the most out of your Lambda functions and show how cloud native architectures use Lambda to eliminate “cold servers” and excess capacity without sacrificing scalability or responsiveness.
As serverless architectures become more popular, AWS customers need a framework of patterns to help them deploy their workloads without managing servers or operating systems.
As serverless architectures become more popular, AWS customers need a framework of patterns to help them deploy their workloads without managing servers or operating systems.
AWS re:Invent 2016: The State of Serverless Computing (SVR311)Amazon Web Services
Join us to learn about the state of serverless computing from Dr. Tim Wagner, General Manager of AWS Lambda. Dr. Wagner discusses the latest developments from AWS Lambda and the serverless computing ecosystem. He talks about how serverless computing is becoming a core component in how companies build and run their applications and services, and he also discusses how serverless computing will continue to evolve.
Join us to learn about the state of serverless computing from Dr. Tim Wagner, General Manager of AWS Lambda. Dr. Wagner discusses the latest developments from AWS Lambda and the serverless computing ecosystem. He talks about how serverless computing is becoming a core component in how companies build and run their applications and services, and he also discusses how serverless computing will continue to evolve.
Similar to AWS Serverless patterns & best-practices in AWS (20)
Collapsing Narratives: Exploring Non-Linearity • a micro report by Rosie WellsRosie Wells
Insight: In a landscape where traditional narrative structures are giving way to fragmented and non-linear forms of storytelling, there lies immense potential for creativity and exploration.
'Collapsing Narratives: Exploring Non-Linearity' is a micro report from Rosie Wells.
Rosie Wells is an Arts & Cultural Strategist uniquely positioned at the intersection of grassroots and mainstream storytelling.
Their work is focused on developing meaningful and lasting connections that can drive social change.
Please download this presentation to enjoy the hyperlinks!
This presentation, created by Syed Faiz ul Hassan, explores the profound influence of media on public perception and behavior. It delves into the evolution of media from oral traditions to modern digital and social media platforms. Key topics include the role of media in information propagation, socialization, crisis awareness, globalization, and education. The presentation also examines media influence through agenda setting, propaganda, and manipulative techniques used by advertisers and marketers. Furthermore, it highlights the impact of surveillance enabled by media technologies on personal behavior and preferences. Through this comprehensive overview, the presentation aims to shed light on how media shapes collective consciousness and public opinion.
2. This presentation has been prepared by EPAM Systems, Inc. solely for use by EPAM at its EPAM Zed
Conference. This presentation or the information contained herein may not be reproduced or used
for any other purpose. This presentation includes highly confidential and proprietary information and
is delivered on the express condition that such information will not be disclosed to anyone except
persons in the recipient organization who have a need to know solely for the purpose described
above. No copies of this presentation will be made, and no other distribution will be made, without
the consent of EPAM. Any distribution of this presentation to any other person, in whole or in part,
or the reproduction of this presentation, or the divulgence of any of its contents is unauthorized.
CONFIDENTIAL INFORMATION
6. Focus on business value, not infrastructure
1. F A S T E R T I M E T O M A R K E T
2.
3.
R E D U C E D C O S T S
I M P R O V E D R E L I A B I L I T Y
6
4. I N C R E A S E D R AT E O F I N N O VAT I O N
7. Faster time to market
By eliminating operational overhead, your teams can release quickly, get
feedback, and iterate to get to market faster.
8. Reduced costs
With a pay-for-value billing model, you never pay for over-provisioning and
your resource utilization is optimized on your behalf.
10. Increased rate of innovation
Serverless applications have built-in service integrations, so you can focus on
building your application instead of configuring it.
12. AWS Lambda/Serverless patterns overview
AWS designed many solutions, and you should just find building
blocks for your cases
• Web application
• Mobile application for social distancing
• Mobile back-end
• Real-time stream processing
• IoT back-end
• AWS Connected mobility architecture
• Real-time file processing
• MapReduce
• Image recognition & processing
• Image moderator chatbot
12
https://aws.amazon.com/lambda/resources/reference-architectures/
17. Myths
Myth #1: Serverless means “no server and hardware”
• You need to setup required RAM size
Myth #2: Serverless == Lambda (AWS Lambda, Azure Functions etc.)
• Amazon enumerates as serverless such services as S3, SQS, SNS, API Gateway, DynamoDB
Myth #3: Serverless is cheap, definitely cheaper than “serverfull” solution
• Not always, you always should calculate costs ahead to see if it’s good fit
18. Going Stateful Anti-Pattern
Antipattern #1: Going stateful (in-memory state)
Problem
• Though lambda instance can be preserved for the next requests (such called
“hot start”), it is not guaranteed
• After lambda run, lambda instance can be terminated anytime
Solution
• You need a state, store it in external services
18
19. Do Not Pay Attention To Service Specifics
Antipattern #2: Do not pay attention to service specifics
Problem
• “I just write my code and deploy it to AWS Lambda – and everything works” – right, but only if
you agree with terms of service. AWS Lambda for example, have number of limitations (quotas):
• Request size <= 6Mb (so you cannot use it for file upload, use S3 for that)
• Max execution time is 15 minutes (lambda is terminated by timeout then)
Solution
• Regularly revisit quotas, know your data, check if they fit
• Remember there are hard and soft limits, soft limits can be increased on request
19
20. My Favorite Stack Is Great At Lambdas
Antipattern #3: Use your favorite tech stack without paying attention at cost
Problem
• Startup can be much slower in comparison to using plain old java or another language
• You are charged on a second basis.
Reducing overall duration from 10 seconds to 5 seconds will cut your costs twice
• Decreasing memory size (because code in Java was rewritten in Go) by two times will cut your costs
twice
Solution
• As lambda should be small, you can write it in Go/Python/JavaScript even if you are not a Pro in this
language
• So the pattern is: consider if the cost benefit worth learning
20
21. Multithreading Is Great In Lambdas
Antipattern #4: Using old-fashioned way for orchestration
Problem
“I will save a record in DynamoDB from lambda
and then Thread.sleep for another service to update it’s status”
• Each second if lambda does not do anything, you still pay money
• Avoid explicit and try to avoid implicit waits
• Implicit wait – blocking lambda instance awaiting for response from synchronous calls (RESTs)
• Explicit wait – Thread.sleep, polling messages from queues in while loops, checking state in while loops
etc.
Solution
• Orchestration using AWS Step Functions
• Choreography using message brokers (SQS, EventBridge, Kinesis, DynamoDB Streams)
21
23. Serverless Application Model
• Build serverless applications in simple and clean syntax
• Features:
• Built on AWS CloudFormation
• Built-In Best Practices
• Single Deployment Configuration
• Local Testing and Debugging
(+ https://localstack.cloud/)
• Serverless Application Model - https://aws.amazon.com/serverless/sam/
25. Nested Stacks
• Nested stacks are stacks created as part of other stacks.
• Nested stacks can themselves contain other nested stacks, resulting in a
hierarchy of stacks, as in the diagram below. The root stack is the top-
level stack to which all the nested stacks ultimately belong. In addition,
each nested stack has an immediate parent stack. For the first level of
nested stacks, the root stack is also the parent stack. in the diagram
below, for example:
• Stack A is the root stack for all the other, nested, stacks in the hierarchy.
• For stack B, stack A is both the parent stack, and the root stack.
• For stack D, stack C is the parent stack; while for stack C, stack B is the
parent stack.
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-
cfn-nested-stacks.html
26. Know Your Limits
• Lambda’s executions
• Concurrent executions - 1,000
• Step Functions
• Maximum number of registered state machines - 10,000
• Maximum open executions per account - 1,000,000 executions
per AWS account.
• ENIs for Lambdas are not endless
• Elastic network interfaces per virtual private cloud (VPC) - 250
• Limit on S3 buckets for Lambdas
• Buckets - 100 per account
27. AWS Lambda Power Tuning
AWS Lambda Power Tuning is a state machine powered by AWS Step Functions that helps you optimize your Lambda functions for cost
and/or performance in a data-driven way.
https://github.com/alexcasalboni/aws-lambda-power-tuning
28. DB Connections Management
Serverless works best with services rather than connections.
Connection management:
• Application connection pooling
• RDS Proxy
• Amazon Aurora Serverless v2
• Data API
• Dynamo DB
• https://aws.amazon.com/blogs/database/best-practices-for-working-
with-amazon-aurora-serverless/
29. Thank you!
For more information, contact
Dima Pasko
Solution Architect II
Dmytro_Pasko@epam.com
https://www.linkedin.com/in/dimapasko
Editor's Notes
Hello ZED Conference 2021Let’s talk about …
Based on real life experience in Insurance domain
Kharkiv, Ukraine
Solution Architect
Passionate and successful Architect with over 17 years of experience including 6 years of experience in Software Architecture
Experience in Digital Transformation projects with Microservices & Serverless
Multi-cloud experience: AWS, Azure
Next evolution of cloud computing.
Serverless <> not only lambda, it is serverless DBs Engines, Container services, BPMN engines.
Servers not have gone you do not manage them only.
Faster time to market
(Business logic –> API) – >Messaging & Orchestration -> Storage & Databases -> Compute -> Physical Infrastructure
AWS Lambda automatically runs your code without requiring you to provision or manage infrastructure. Just write the code and upload it to Lambda either as a ZIP file or container image.
Focus on most important part of your application
Technology abstraction allows us to focus on building just the pieces of code and configuration that are providing truly unique value for the client.
Productive for the day one
Cost optimized with millisecond metering
With AWS Lambda, you only pay for the compute time you consume, so you’re never paying for over-provisioned infrastructure. You are charged for every millisecond your code executes and the number of times your code is triggered.
At its most basic, the cost case for serverless boils down to utilization. You’ve probably seen the numbers — traditional, on-premise datacenter servers tend to be only 15 to 30% utilized. (We’ve even heard that most large EC2 users struggle to reach this utilization rate as well!) Put the other way, that means 70 to 85% of your server costs are dead weight. Waste.
Аналогия – абонемент в спортзале
No hidden costs:
Security
Platform outdated
(personal story) test environment for 18 teams ~ $400
Scale from zero to infinity and back
Consistent performance at any scale(smooths)
With AWS Lambda, you can optimize your code execution time by choosing the right memory size for your function. You can also keep your functions initialized and hyper-ready to respond within double digit milliseconds by enabling Provisioned Concurrency.
Easy to start new project, very cheap, modularity, elasticity
Experiments, new environment, iteration cycle
A lot of integrations. Event based. Out of the box.
Architecture improvement: breaking the monolith into functions that could be independently deployed, meant that they were better able to split the team up to work on more things in parallel, and to deploy each feature separately
Next evolution of cloud computing.
Continuously improving: ARM + Graviton
Don’t invent a wheel and review AWS resources
Try to search and adopt existing to your case
Also this is a good reason to learn how to draw diagrams for AWS
AWS Well-Architected Framework
The AWS Well-Architected Framework Lens provides a set of foundational questions for you to consider for all of your cloud architectures.
Serverless Lens
Description
The AWS Serverless Application Lens provides a set of additional questions for you to consider for your serverless applications.
Tell how you open AWS console, add workload, grouped questions, download a report
Tell how you open AWS console, add workload, grouped questions, download a report
Serverless can gain polarized opinion starting from “use it everywhere, it’s cool!” to “just a hype, I’m good with my Java 5 + tomcat”And this emotional attitude often drives technology selection
That’s why this slide is more about myths about serverless than about antipatterns
Myth #1: Serverless means “no server and hardware” Servers not have gone you do not manage them only.
And sometimes this abstraction leaks – for lambda you need to setup required RAM size
Serverless more means “no infrastructure work” – all the infrastructure maintenance is on provider
Portability, Vendor lock
Myth #2: Serverless == Lambda (AWS Lambda, Azure Functions etc.)
As Serverless means “no infrastructure work”, many of services familiar to you are already serverless. AWS S3 for example.
Amazon enumerates as serverless such services as S3, SQS, SNS, API Gateway, DynamoDB
Even modification of Aurora falls into this category
Myth #3: Serverless is cheap, definitely cheaper than serverfull solution
Not always, you always should calculate costs ahead to see if it’s good fit
Not all workloads are suitable for serverless
Example from Insurance domain, predictable loadAd tech, stock exchange – could bad domain example
The Sirens & Odysseus
Antipattern #1: Going stateful (in-memory state)
We are not talking about state saved in external service (caches like Redis, databases etc) – that approach is fine
But accumulating in-memory state is definitely antipattern:
Though lambda instance can be preserved for the next requests (such called “hot start”), it is not guaranteed
After lambda run, lambda instance can be terminated anytime
So the pattern is: if you need a state, store it in external services. For fast access use distributed caches as AWS ElastiCache (managed Redis)
You CAN go with in-memory state if you know what you are doing (lambdas are in warm state, have provisioned/reserved concurrency on – so instances will likely be reused)
Icarus
Myth of Jason and the Argonauts
Antipattern #3: Use your favorite tech stack without paying attention at cost
“I will write this on Spring Boot” can have such downsides:
You might need more memory for lambda than for the same logic written in Go or Python (up to 4 times and more)
Startup can be much slower in comparison to using plain old java or another language
Can be mitigated by keeping lambda at warm state for hot start
Often for cold start the startup time can be longer than processing time itself
Both memory size and startup time add a cost
You are charged on a second basis. Reducing overall duration from 10 seconds to 5 seconds will cut your costs twice
Decreasing memory size (because code in Java was rewritten in Go) by two times will cut your costs twice
As lambda should be small, you can write it in Go/Python/JavaScript even if you are not a Pro in this language
So the pattern is: consider if the cost benefit worth learning a bit of Python
No Dependency Injection frameworks?
King Midas and his touch
Antipattern #4: Using old-fashioned way for orchestration
“I will save a record in DynamoDB from lambda and then Thread.sleep for another service to update it’s status”
Each second if lambda does not do anything, you still pay money
Design for retries
So the pattern is:
Avoid explicit and try to avoid implicit waits
Implicit wait – blocking lambda instance awaiting for response from synchronous calls (RESTs)
Explicit wait – Thread.sleep, polling messages from queues in while loops, checking state in while loops etc.
Use Cloud-Native way of logic organization:
Orchestration using AWS Step Functions
choreography using message brokers (SQS, EventBridge, Kinesis, DynamoDB Streams)
Nested Stacks
Monorepo – one repo for workload
Good to keep order, atomic deployments, PR in one repo, easier engennering best practices
11. AWS Account strategy (Sizing (Account per Team), sharing resources, hard to performance test, limits)
a. See Laura's Blog for some details on Lambda Concurrency issues :https://myconnections.lmig.com/blogs/n0085283/2019/03/14/aws-lambdas-setting-a-max-concurrency-its-consequences
Best practices: - Dashboards
Alerts, Notifications
Sets of best practices