An introduction into creating a multi tenant SaaS application, creating a database per tenant architecture. Incluiding a case study, example and general pointers
This document provides an overview of Docker, ECS, and how they can be used together on AWS. It defines Docker as application virtualization using containers that package code, runtime, and dependencies. ECS is AWS's container orchestration service that allows running Docker containers across a cluster, providing scheduling, networking, scaling, and reliability. The document outlines key aspects of using ECS including task definitions that specify container configurations, services that maintain a desired number of tasks, and load balancers for exposing applications. It also provides details on how ECS leverages underlying AWS resources and orchestrates tasks and services behind the scenes.
MongoDB .local Bengaluru 2019: Distributed Transactions: With Great Power Com...MongoDB
A year ago we launched replica-set transactions in MongoDB 4.0. We've now expanded transactions to span across shards, making development against MongoDB even easier. Snapshot isolation, write atomicity, distributed commit – we'll touch on it all. You'll learn all you need to know about distributed transactions before you push to prod.
The document discusses scaling relational and NoSQL databases on AWS. It provides an overview of AWS RDS features for scaling databases, including read replicas, multi-AZ deployments, and maintenance windows. It also discusses database replication strategies like synchronous and asynchronous replication. For scaling write-intensive databases, it recommends database sharding and introduces AWS DynamoDB as a NoSQL option that scales for both reads and writes. Streams in DynamoDB enable triggers on row updates.
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.
This document provides an overview of using Python applications on the Microsoft Azure platform. It discusses various deployment options on Azure including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and container services. It then focuses on deploying a Python web app on Azure Web Apps using the PaaS option. Code samples are provided for the Python web app, requirements file, runtime configuration file, and web.config file. Steps for deploying the application via Git push are also outlined. The document concludes with a demonstration of managing Azure resources through the Azure SDK for Python.
EC2 and S3 are core AWS services. EC2 provides virtual servers and S3 provides cloud storage. EC2 instances run on different hardware types and can be configured with operating systems and software. S3 stores files and objects accessed via unique buckets. EBS provides persistent block storage volumes for EC2 instances, while S3 provides scalable cloud storage. VPC allows creation of virtual private networks within AWS.
This document discusses several architecture patterns for building systems on Amazon Web Services (AWS). It outlines patterns for snapshotting data, scaling servers vertically and horizontally, using elastic block storage, distributing applications across multiple availability zones and regions, implementing load balancing and caching, and configuring databases and networking. Both benefits and cautions are provided for each pattern to help architects design resilient and secure systems on AWS.
This document provides an overview of Docker, ECS, and how they can be used together on AWS. It defines Docker as application virtualization using containers that package code, runtime, and dependencies. ECS is AWS's container orchestration service that allows running Docker containers across a cluster, providing scheduling, networking, scaling, and reliability. The document outlines key aspects of using ECS including task definitions that specify container configurations, services that maintain a desired number of tasks, and load balancers for exposing applications. It also provides details on how ECS leverages underlying AWS resources and orchestrates tasks and services behind the scenes.
MongoDB .local Bengaluru 2019: Distributed Transactions: With Great Power Com...MongoDB
A year ago we launched replica-set transactions in MongoDB 4.0. We've now expanded transactions to span across shards, making development against MongoDB even easier. Snapshot isolation, write atomicity, distributed commit – we'll touch on it all. You'll learn all you need to know about distributed transactions before you push to prod.
The document discusses scaling relational and NoSQL databases on AWS. It provides an overview of AWS RDS features for scaling databases, including read replicas, multi-AZ deployments, and maintenance windows. It also discusses database replication strategies like synchronous and asynchronous replication. For scaling write-intensive databases, it recommends database sharding and introduces AWS DynamoDB as a NoSQL option that scales for both reads and writes. Streams in DynamoDB enable triggers on row updates.
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.
This document provides an overview of using Python applications on the Microsoft Azure platform. It discusses various deployment options on Azure including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and container services. It then focuses on deploying a Python web app on Azure Web Apps using the PaaS option. Code samples are provided for the Python web app, requirements file, runtime configuration file, and web.config file. Steps for deploying the application via Git push are also outlined. The document concludes with a demonstration of managing Azure resources through the Azure SDK for Python.
EC2 and S3 are core AWS services. EC2 provides virtual servers and S3 provides cloud storage. EC2 instances run on different hardware types and can be configured with operating systems and software. S3 stores files and objects accessed via unique buckets. EBS provides persistent block storage volumes for EC2 instances, while S3 provides scalable cloud storage. VPC allows creation of virtual private networks within AWS.
This document discusses several architecture patterns for building systems on Amazon Web Services (AWS). It outlines patterns for snapshotting data, scaling servers vertically and horizontally, using elastic block storage, distributing applications across multiple availability zones and regions, implementing load balancing and caching, and configuring databases and networking. Both benefits and cautions are provided for each pattern to help architects design resilient and secure systems on AWS.
From AWS to GCP, TABLEAPP Architecture StoryYen-Wen Chen
TABLEAPP is migrating from AWS to GCP due to scaling issues with their AWS architecture. They propose using Kubernetes on GCP to containerize their application and allow for easier auto-scaling. This will eliminate wasted resources and slow provisioning times. They present a new GCP architecture using Kubernetes, Cloud SQL, Cloud Load Balancing, and other GCP services. Migrating has reduced costs by 40% while maintaining availability and performance.
With Docker it became easy to start applications locally without installing any dependencies. Even running a local cluster is not a big thing anymore. AWS on the other side offers with ECS a managed container service that states to schedule containers based on resource needs, isolation policies and availability requirements. But what happens between? Is it really that easy? In this talk you’ll see which existing services can already be used to deploy your containers automatically and what still needs to be done to get them running on AWS.
This document discusses Google Kubernetes Engine (GKE). It introduces containers and Kubernetes, then summarizes GKE as a container platform that fully manages master nodes. GKE provides automated operations like cluster autoscaling and node auto-repair. It allows creating multiple node pools with different configurations. GKE also enables high availability clusters across zones and monitoring with Stackdriver. Demos show using GKE to run game servers and implementing continuous integration and delivery pipelines.
This document discusses autoscaling in Kubernetes. It describes horizontal and vertical autoscaling, and how Kubernetes can autoscale nodes and pods. For nodes, it proposes using Google Compute Engine's managed instance groups and cloud autoscaler to automatically scale the number of nodes based on resource utilization. For pods, it discusses using an autoscaler controller to scale the replica counts of replication controllers based on metrics from cAdvisor or Google Cloud Monitoring. Issues addressed include rebalancing pods and handling autoscaling during rolling updates.
Docker is an open platform for developers and system administrators to build, ship and run distributed applications. Using Docker, companies in Jordan have been able to build powerful system architectures that allow speeding up delivery, easing deployment processes and at the same time cutting major hosting costs.
Osama Jaber shares his experience at ArabiaWeather in how they moved away from AWS to a highly-redundant, high-performance and low-cost solution using docker and other open-source technologies.
This document summarizes a presentation about Amazon EC2 Container Service (ECS). It covers the key topics of cluster management, container scheduling, container deployment, scaling ECS, logging and monitoring, and service discovery. For each topic, it provides an overview and links to additional resources with more in-depth information.
Tableapp architecture migration story for GCPUG.TWYen-Wen Chen
This document summarizes the migration of a web application called TABLEAPP from AWS to GCP. It describes the original AWS architecture, problems encountered like slow scaling, and goals for the migration like improving performance and reducing costs. It then details experiments with Docker containers and Kubernetes on GCP and AWS. The selected solution deployed Kubernetes on GCP's Container Engine for auto-scaling and easy management. The new GCP architecture integrated Kubernetes, Cloud SQL, Cloud Storage and other services. This resulted in faster deployment times, higher performance, better log collection and a 40% reduction in costs compared to the original AWS architecture.
Using Kubernetes to deploy Django in GCPWalter Liu
Walter discusses using Kubernetes on Google Cloud Platform to deploy a Django application. He describes how Kubernetes provides infrastructure as code to automate and scale the application. Key Kubernetes components used include pods, deployments, statefulsets, secrets and configmaps. Services are used for internal and external load balancing, with an ingress controller providing a global load balancer. The document also touches on cluster creation steps, load balancing options, and templating with Python Jinja.
AWS September Webinar Series - Visual Effects Rendering in the AWS Cloud with...Amazon Web Services
Visual effects rendering has traditionally been a time consuming, resource intensive process. As a result, content producers are moving rendering workloads to the AWS cloud to take advantage of the scalable, on-demand compute resources that can accelerate their rendering workloads.
By attending this webinar, you will learn how to create a scalable rendering infrastructure to grow your farm for any size workload, reduce overall processing time with on-demand and reserve compute instances, and move to a project based cost structure. You will also learn how to implement hybrid rendering workloads using Thinkbox dependency manager.
Learning Objectives:
How to use AWS Cloud to rapidly scale up and down rendering infrastructure to power ThinkBox Deadline software in the cloud for visual effects rendering
Who should attend:
IT administrators, rendering and visual effects professionals
Mit Docker ist es einfach geworden, Applikationen lokal zu starten, ohne zusätzliche Abhängigkeiten installieren zu müssen. Einen Cluster auf seinem eigenen Rechner laufen zu lassen ist kein großes Ding mehr. Mit ECS bietet AWS einen Container-Management-Service für die Cloud an, der verspricht, Container entsprechend ihrem Ressourcenbedarf und Verfügbarkeitserfordernissen automatisch im Cluster zu platzieren.
Aber was passiert dazwischen? Und ist es wirklich so einfach?
In diesem Talk werden wir betrachten, welche existierenden Services von AWS verwendet werden können, um Container automatisch zu deployen, und was zusätzlich alles benötigt wird, um sie im Betrieb laufen zu lassen.
Learn how to get started with the EC2 Container Service, a highly scalable, high performance container management service that supports Docker containers and allows you to easily run applications on a managed cluster of Amazon EC2 instances. We will also cover integration with other AWS services such as Elastic Load Balancing, EBS volumes, and IAM roles.
Long running aws lambda - Joel Schuweiler, MinneapolisAWS Chicago
The document discusses running long-running tasks using AWS Lambda and ECS. It describes how Lambda has runtime and resource limits that prevent long running processes. It then outlines a method to use Lambda to trigger an ECS task to run the long-running process instead of running it directly in Lambda. Key aspects of the ECS task definition and IAM roles are also summarized.
The document discusses using Node.js on the Windows Azure platform. It describes how Node.js is a JavaScript runtime for building scalable network applications, and how it is fully supported on Windows Azure through deployment options like Web Sites and Cloud Services. It also introduces Web Matrix 2 as a lightweight IDE for developing Node.js applications on Windows Azure, providing features like IntelliSense and publishing capabilities.
This presentation will show you overview of Google Cloud Service and show step-by-step example with Wordpress to introduce each service on GCP
Google Cloud Study Jam Bangkok 2019 #1 and #2 at ITKMITL and CPE KU on October 19-20, 2019
by Ganesh Shankaran, Sr. Solutions Architect, AWS
Hands-on Lab to compare and contrast relational queries (using RDS for MySQL) with nonrelational queries (using ElastiCache for Redis). You’ll need a laptop with a Firefox or Chrome browser.
The document is a presentation about Google Compute Engine (GCE). It discusses cloud computing service levels including Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). GCE is described as an IaaS offering that provides virtual machines with flexible configurations and pricing based on minute usage. A demo is shown creating a VM and hosting a website using Apache. Another demo spins up a Hadoop cluster on GCE for distributed data processing.
The document introduces the Windows Azure HDInsight Service, which provides a managed Hadoop service on Windows Azure. It discusses big data and Hadoop, describes the components included in HDInsight like HDFS, MapReduce, Pig and Hive. It provides examples of using Pig, Hive and Sqoop with HDInsight and explains how HDInsight is administered through the management portal.
Jan Mußler from Zalando SE in Berlin held this presentation on "PostSQL on Kubernetes" on the DOCKER HAMBURG MEETUP in the Zalando adtech lab Office on 12th July 2017
Leveraging Amzon EC2 Container Services for Container OrchestrationNeeraj Shah
This is the slides for a talk I gave on AWS EC2 Container Services at AWS + Docker Meetup held @ LinkedIn Bangalore. The video of my presentation can be found at https://youtu.be/GbMGJbDTj-A
AWS Summit 2013 | India - Scaling Seamlessly and Going Global with the Cloud,...Amazon Web Services
AWS provides a platform that is ideally suited for deploying highly available and reliable systems that can scale with a minimal amount of human interaction. This talk describes a set of architectural patterns that support highly available services that are also scalable, low cost, low latency and allow for taking your application global with the click of a button. We walk through the various architectural decisions taken to achieve high scale and address global audience.
The document discusses architecting highly available applications on AWS. It begins with an overview of AWS services and best practices for scalability. It then walks through scaling an application from 1 user to over 1 million users, starting with a single EC2 instance and gradually introducing services like Auto Scaling, load balancing, database read replicas, caching, and separating components. The document emphasizes loose coupling of services, automation, and monitoring to allow scalability.
From AWS to GCP, TABLEAPP Architecture StoryYen-Wen Chen
TABLEAPP is migrating from AWS to GCP due to scaling issues with their AWS architecture. They propose using Kubernetes on GCP to containerize their application and allow for easier auto-scaling. This will eliminate wasted resources and slow provisioning times. They present a new GCP architecture using Kubernetes, Cloud SQL, Cloud Load Balancing, and other GCP services. Migrating has reduced costs by 40% while maintaining availability and performance.
With Docker it became easy to start applications locally without installing any dependencies. Even running a local cluster is not a big thing anymore. AWS on the other side offers with ECS a managed container service that states to schedule containers based on resource needs, isolation policies and availability requirements. But what happens between? Is it really that easy? In this talk you’ll see which existing services can already be used to deploy your containers automatically and what still needs to be done to get them running on AWS.
This document discusses Google Kubernetes Engine (GKE). It introduces containers and Kubernetes, then summarizes GKE as a container platform that fully manages master nodes. GKE provides automated operations like cluster autoscaling and node auto-repair. It allows creating multiple node pools with different configurations. GKE also enables high availability clusters across zones and monitoring with Stackdriver. Demos show using GKE to run game servers and implementing continuous integration and delivery pipelines.
This document discusses autoscaling in Kubernetes. It describes horizontal and vertical autoscaling, and how Kubernetes can autoscale nodes and pods. For nodes, it proposes using Google Compute Engine's managed instance groups and cloud autoscaler to automatically scale the number of nodes based on resource utilization. For pods, it discusses using an autoscaler controller to scale the replica counts of replication controllers based on metrics from cAdvisor or Google Cloud Monitoring. Issues addressed include rebalancing pods and handling autoscaling during rolling updates.
Docker is an open platform for developers and system administrators to build, ship and run distributed applications. Using Docker, companies in Jordan have been able to build powerful system architectures that allow speeding up delivery, easing deployment processes and at the same time cutting major hosting costs.
Osama Jaber shares his experience at ArabiaWeather in how they moved away from AWS to a highly-redundant, high-performance and low-cost solution using docker and other open-source technologies.
This document summarizes a presentation about Amazon EC2 Container Service (ECS). It covers the key topics of cluster management, container scheduling, container deployment, scaling ECS, logging and monitoring, and service discovery. For each topic, it provides an overview and links to additional resources with more in-depth information.
Tableapp architecture migration story for GCPUG.TWYen-Wen Chen
This document summarizes the migration of a web application called TABLEAPP from AWS to GCP. It describes the original AWS architecture, problems encountered like slow scaling, and goals for the migration like improving performance and reducing costs. It then details experiments with Docker containers and Kubernetes on GCP and AWS. The selected solution deployed Kubernetes on GCP's Container Engine for auto-scaling and easy management. The new GCP architecture integrated Kubernetes, Cloud SQL, Cloud Storage and other services. This resulted in faster deployment times, higher performance, better log collection and a 40% reduction in costs compared to the original AWS architecture.
Using Kubernetes to deploy Django in GCPWalter Liu
Walter discusses using Kubernetes on Google Cloud Platform to deploy a Django application. He describes how Kubernetes provides infrastructure as code to automate and scale the application. Key Kubernetes components used include pods, deployments, statefulsets, secrets and configmaps. Services are used for internal and external load balancing, with an ingress controller providing a global load balancer. The document also touches on cluster creation steps, load balancing options, and templating with Python Jinja.
AWS September Webinar Series - Visual Effects Rendering in the AWS Cloud with...Amazon Web Services
Visual effects rendering has traditionally been a time consuming, resource intensive process. As a result, content producers are moving rendering workloads to the AWS cloud to take advantage of the scalable, on-demand compute resources that can accelerate their rendering workloads.
By attending this webinar, you will learn how to create a scalable rendering infrastructure to grow your farm for any size workload, reduce overall processing time with on-demand and reserve compute instances, and move to a project based cost structure. You will also learn how to implement hybrid rendering workloads using Thinkbox dependency manager.
Learning Objectives:
How to use AWS Cloud to rapidly scale up and down rendering infrastructure to power ThinkBox Deadline software in the cloud for visual effects rendering
Who should attend:
IT administrators, rendering and visual effects professionals
Mit Docker ist es einfach geworden, Applikationen lokal zu starten, ohne zusätzliche Abhängigkeiten installieren zu müssen. Einen Cluster auf seinem eigenen Rechner laufen zu lassen ist kein großes Ding mehr. Mit ECS bietet AWS einen Container-Management-Service für die Cloud an, der verspricht, Container entsprechend ihrem Ressourcenbedarf und Verfügbarkeitserfordernissen automatisch im Cluster zu platzieren.
Aber was passiert dazwischen? Und ist es wirklich so einfach?
In diesem Talk werden wir betrachten, welche existierenden Services von AWS verwendet werden können, um Container automatisch zu deployen, und was zusätzlich alles benötigt wird, um sie im Betrieb laufen zu lassen.
Learn how to get started with the EC2 Container Service, a highly scalable, high performance container management service that supports Docker containers and allows you to easily run applications on a managed cluster of Amazon EC2 instances. We will also cover integration with other AWS services such as Elastic Load Balancing, EBS volumes, and IAM roles.
Long running aws lambda - Joel Schuweiler, MinneapolisAWS Chicago
The document discusses running long-running tasks using AWS Lambda and ECS. It describes how Lambda has runtime and resource limits that prevent long running processes. It then outlines a method to use Lambda to trigger an ECS task to run the long-running process instead of running it directly in Lambda. Key aspects of the ECS task definition and IAM roles are also summarized.
The document discusses using Node.js on the Windows Azure platform. It describes how Node.js is a JavaScript runtime for building scalable network applications, and how it is fully supported on Windows Azure through deployment options like Web Sites and Cloud Services. It also introduces Web Matrix 2 as a lightweight IDE for developing Node.js applications on Windows Azure, providing features like IntelliSense and publishing capabilities.
This presentation will show you overview of Google Cloud Service and show step-by-step example with Wordpress to introduce each service on GCP
Google Cloud Study Jam Bangkok 2019 #1 and #2 at ITKMITL and CPE KU on October 19-20, 2019
by Ganesh Shankaran, Sr. Solutions Architect, AWS
Hands-on Lab to compare and contrast relational queries (using RDS for MySQL) with nonrelational queries (using ElastiCache for Redis). You’ll need a laptop with a Firefox or Chrome browser.
The document is a presentation about Google Compute Engine (GCE). It discusses cloud computing service levels including Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). GCE is described as an IaaS offering that provides virtual machines with flexible configurations and pricing based on minute usage. A demo is shown creating a VM and hosting a website using Apache. Another demo spins up a Hadoop cluster on GCE for distributed data processing.
The document introduces the Windows Azure HDInsight Service, which provides a managed Hadoop service on Windows Azure. It discusses big data and Hadoop, describes the components included in HDInsight like HDFS, MapReduce, Pig and Hive. It provides examples of using Pig, Hive and Sqoop with HDInsight and explains how HDInsight is administered through the management portal.
Jan Mußler from Zalando SE in Berlin held this presentation on "PostSQL on Kubernetes" on the DOCKER HAMBURG MEETUP in the Zalando adtech lab Office on 12th July 2017
Leveraging Amzon EC2 Container Services for Container OrchestrationNeeraj Shah
This is the slides for a talk I gave on AWS EC2 Container Services at AWS + Docker Meetup held @ LinkedIn Bangalore. The video of my presentation can be found at https://youtu.be/GbMGJbDTj-A
AWS Summit 2013 | India - Scaling Seamlessly and Going Global with the Cloud,...Amazon Web Services
AWS provides a platform that is ideally suited for deploying highly available and reliable systems that can scale with a minimal amount of human interaction. This talk describes a set of architectural patterns that support highly available services that are also scalable, low cost, low latency and allow for taking your application global with the click of a button. We walk through the various architectural decisions taken to achieve high scale and address global audience.
The document discusses architecting highly available applications on AWS. It begins with an overview of AWS services and best practices for scalability. It then walks through scaling an application from 1 user to over 1 million users, starting with a single EC2 instance and gradually introducing services like Auto Scaling, load balancing, database read replicas, caching, and separating components. The document emphasizes loose coupling of services, automation, and monitoring to allow scalability.
Bitbucket Pipelines - Powered by KubernetesNathan Burrell
This talk covers how pipelines uses Kubernetes to power its builder infrastructure and shares some tips on running Kubernetes at scale in a secure way.
This presentation was presented to the sydney Kubernetes meetup on the 3rd of August 2017.
- The document discusses strategies for scaling a web application architecture to support 10 million users.
- It recommends starting with a well-designed two-tier architecture using SQL databases for reliability and scalability, and adding services like S3, CloudFront, and EMR to optimize performance and enable analytics at larger scales.
- Example architectures are presented starting with basic infrastructure and adding optimizations over time to support growing user bases from 10,000s to millions of users.
Scaling on AWS for the First 10 Million Users at Websummit DublinAmazon Web Services
Ian Massingham gave a presentation on scaling applications on AWS from initial launch to over 1 million users. He began by discussing foundational AWS services and database options. He then walked through examples of scaling an application from 1 user to over 500,000 users by leveraging services like EC2, RDS, DynamoDB, ElastiCache, S3, CloudFront, and Auto Scaling. Key strategies included separating components across instances, adding redundancy, implementing caching, and leveraging auto scaling to dynamically scale resources based on demand. Massingham concluded by discussing strategies for scaling beyond 500,000 users such as service-oriented architectures and workload distribution across availability zones.
Scaling on AWS for the First 10 Million Users at Websummit DublinIan Massingham
In this talk from the Dublin Websummit 2014 AWS Technical Evangelist Ian Massingham discusses the techniques that AWS customers can use to create highly scalable infrastructure to support the operation of large scale applications on the AWS cloud.
Includes a walk-through of how you can evolve your architecture as your application becomes more popular and you need to scale up your infrastructure to support increased demand.
This document summarizes Amazon DynamoDB features and new capabilities presented at AWS re:Invent 2017. It includes 3 case studies:
1) How Samsung migrated from Cassandra to DynamoDB, improving performance and reducing costs by 50%+.
2) New DynamoDB capabilities like global tables, encryption at rest, on-demand backups were evaluated.
3) Best practices for migration including decreasing threads and item batches to control load are discussed.
Kalibrr is a startup that provides an online talent assessment platform. They launched their minimum viable product (MVP) on AWS in March 2013, seeing user growth from 0 to 25,000 in two months. AWS allowed Kalibrr to scale easily and provided reliability with no downtime. Kalibrr uses EC2 instances to host their web servers, SES for email, S3 for content storage, ELB for load balancing, and Route 53 for DNS management. AWS's scalability, ease of use, and reliability helped Kalibrr launch their MVP successfully and support further growth.
Traditional data warehouses become expensive and slow down as the volume of your data grows. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it easy to analyze all of your data using existing business intelligence tools for 1/10th the traditional cost. This session will provide an introduction to Amazon Redshift and cover the essentials you need to deploy your data warehouse in the cloud so that you can achieve faster analytics and save costs. We’ll also cover the recently announced Redshift Spectrum, which allows you to query unstructured data directly from Amazon S3.
This document discusses different architectural approaches that can be used when deploying workloads on AWS like startups. It summarizes virtual machine-based n-tier architectures, container-based architectures using ECS, and serverless architectures using Lambda. It also discusses how these architectures impact cost, performance, reliability and other factors. The document recommends letting development teams choose the right tools for their needs and adopting a microservices approach to scale complexity over time.
For people who start to create a cloud service, it’s really important to know how to create a scalable cloud service to fit the growth of the future workloads. In this session, we will introduce how to design a scalable cloud service including AWS services introduction and best practices.
Monitoring in Motion: Monitoring Containers and Amazon ECSAmazon Web Services
Containers and other forms of dynamic infrastructure can prove challenging to monitor. How do you define normal, when your infrastructure is intentionally in motion and change from minute to minute? Join us as we discuss proven strategies for monitoring your containerized infrastructure on AWS and ECS.
The document discusses Amazon EC2 Container Service (ECS) and Amazon EC2 Container Registry (ECR). It provides an overview of how ECS manages Docker containers across server instances in a cluster, including task scheduling and service deployment. It also summarizes ECR as a fully managed private Docker container registry that provides security, reliability and integration with ECS and other AWS services. The document highlights key capabilities like load balancing, auto scaling, private access control and integration with tools like the Docker CLI.
This document discusses scaling applications on Amazon Web Services (AWS) as user counts increase. It begins with an overview of AWS services for applications with a single user, including compute (EC2), storage (EBS), load balancing (ELB), and auto-scaling. For applications with more than one user, it discusses choosing appropriate EC2 instance types and auto-scaling policies. The document then notes that as user counts grow to thousands or millions, it will discuss scaling strategies in further documents. It promotes additional AWS scaling guides and notes that the company presenting is hiring various roles.
AWS Summit 2014 Brisbane - Breakout 6
Technical deep dive in to 10 AWS Cloud best practices with in-depth look at the tips and tricks of architecting on the AWS platform.
Presenter: Dean Samuels, Solutions Architect, Amazon Web Services
Apache Druid Auto Scale-out/in for Streaming Data Ingestion on KubernetesDataWorks Summit
Apache Druid supports auto-scaling of Middle Manager nodes to handle changes in data ingestion load. On Kubernetes, this can be implemented using Horizontal Pod Autoscaling based on custom metrics exposed from the Druid Overlord process, such as the number of pending/running tasks and expected number of workers. The autoscaler scales the number of Middle Manager pods between minimum and maximum thresholds to maintain a target average load percentage.
Accelerate SQL Server Migration to the AWS Cloud Datavail
In today’s marketplace, moving to the public Cloud is a familiar and consistent trend within the SQL Server community.
But which cloud provider do you choose? After all there are different AWS instances each with their own distinctive features. Migrations to the cloud are only going to gain greater momentum as organizations grapple with their on-premises alternatives.
Recent cloud breaches may have some organizations hesitant to take the leap and move to the cloud, however market-leading cloud providers are making every attempt in adhering to compliance guidelines while boosting their security framework and reliability offerings. They are also becoming more competitive by managing their cost more effectively.
For both homogeneous and heterogeneous migrations, planning plays a critical role in moving to the cloud. Preparing a checklist and asking the right questions to stakeholders lays the groundwork in this planning. There are different methods to migrate databases from on-premises to the AWS cloud.
This webinar is in partnership with PASS, download the recording to learn more about:
Reasons to go to the cloud
SQL Server on AWS EC2 vs. AWS RDS
SQL Server high availability (HA) & disaster recovery (DR)
SQL Server migration methodology
DBAs role in the cloud
Building a Just-in-Time Application Stack for AnalystsAvere Systems
Slide presentation from Webinar on February 17, 2016.
People in analytical roles are demanding more and more compute and storage to get their jobs done. Instead of building out infrastructure for a few employees or a department, systems engineers and IT managers can find value in creating a compute stack in the cloud to meet the fluctuating demand of their clients.
In this 45-minute webinar, you’ll learn:
- How to identify the right analytical workloads
- How to create a scalable compute environment using the cloud for analysts in under 10 minutes
- How to best manage costs associated with the cloud compute stack
- How to create dedicated client stacks with their own scratch space as well as general access to reference data
Health systems departments, research & development departments, and business analyst groups all face silos of these challenging, compute-intensive use cases. By learning how to quickly build this flexible workflow that can be scaled up and down (or off) instantly, you can support business objectives while efficiently managing costs.
Getting Maximum Performance from Amazon Redshift (DAT305) | AWS re:Invent 2013Amazon Web Services
Get the most out of Amazon Redshift by learning about cutting-edge data warehousing implementations. Desk.com, a Salesforce.com company, discusses how they maintain a large concurrent user base on their customer-facing business intelligence portal powered by Amazon Redshift. HasOffers shares how they load 60 million events per day into Amazon Redshift with a 3-minute end-to-end load latency to support ad performance tracking for thousands of affiliate networks. Finally, Aggregate Knowledge discusses how they perform complex queries at scale with Amazon Redshift to support their media intelligence platform.
Henry been azure resource manager - inside outHenry Been
This document discusses infrastructure as code using Azure Resource Manager templates. It begins with an example of JSON code that defines a storage account resource. It then covers key aspects of ARM templates like their structure with parameters, variables, resources, and outputs. It also discusses functions that can be used in templates and different ways of deploying templates including via the Azure CLI, PowerShell, or pipelines.
Dot netsaterday henry been - logging instrumentation dashboards alertsHenry Been
This document discusses logging, instrumentation, dashboards and alerts for developers. It covers monitoring theory, what to monitor and not monitor, and using Azure services like Azure Monitor and Application Insights for metrics, logs and setting up dashboards and alerts. A demo of instrumenting an application and viewing metrics and logs is also included.
Henry Been - Secure development: keeping your application secrets privateHenry Been
Do you still store secrets in source control? Are your secrets safely stored, but are you struggling to distribute them to your applications? Do you feel this should be easy, but you can’t just find out how?
In this session, Henry will take you on a journey that starts with passwords in source control. From there he will quickly take you along on a series of improvements to make both local development and production deployments more and more secure with every change.
Along the way, you will learn how to use Azure Key Vault, Azure Active Directory (AAD) and App Service Managed Instance to get everyone on a need to know basis. Finally, you will see how forgetting about keys, certificates and passwords completely and just using AAD could solve all your problems. That is.., if everyone would just use AAD!
Logging, Instrumentation, Dashboards and Alerts - for developersHenry Been
An introduction into monitoring & logging, for developers. Some theory, a discussion of what to monitor and what not and getting started implementing monitoring & logging using Microsoft Azure
Secure deployments keeping your application secrets private -duug festHenry Been
This document discusses several approaches for securely managing secrets in deployments, including using a release orchestrator, ARM templates, accessing secrets directly from Key Vault, and accessing supported services directly. It recommends using a release orchestrator for existing situations, ARM templates to avoid duplicating secrets manually, and directly accessing Key Vault or supported services when possible to allow secrets to be automatically picked up on deployment and rolled more easily. Config builders are also presented as a way to handle secrets for local development and deployments.
Secure deployments keeping your application secrets private - condensedHenry Been
This document discusses different approaches for managing secrets securely in DevOps deployments. It presents four approaches: 1) using a release orchestrator which allows viewing secrets, 2) using ARM templates which prevents viewing secrets but they must be duplicated, 3) directly accessing key vault which prevents viewing and duplication of secrets but is only available on some Azure services, and 4) directly accessing other services which has the same benefits as 3 but is limited to supported services. The document recommends choosing an approach based on how code and infrastructure are deployed and what capabilities the services support. It also demonstrates config builders for managing secrets locally and in the cloud.
Writing, build and releasing your own vsts extensionHenry Been
This document discusses how to write, build, and release Visual Studio Team Services (VSTS) extensions. It provides an overview of the process for creating a VSTS extension, including using extension points, the extension manifest, and publishing to the VSTS marketplace. It also includes several useful resources for learning how to build VSTS extensions.
Focus on business value by going ServerlessHenry Been
An introduction into the serverless paradigm, relating it to other types of cloud offerings and sharing three major serverless offerings in MIcrosoft Azure
Henry been database-per-tenant with 50k databasesHenry Been
To create an application that is truly designed for massive scale, scale-out at every level of the solution is needed. While doing so at the services level, many developers are still using a single database to serve every request. In response to this, a new pattern, database-per-tenant, is emerging. In this pattern, all data is distributed over a large number of databases. In this session Henry will explore this pattern in detail, covering its advantages and disadvantages and a number of common scenarios around such an architecture.
Henry been - Multi-tenant applications using 30k databasesHenry Been
Talk I gave at TechDays 2017 on building a scale-out data layer in Azure SQL DB using elastic tools and capabilities, sharing both the SnelStart story and exploring the MS Wingtip example
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Zilliz
Join us to introduce Milvus Lite, a vector database that can run on notebooks and laptops, share the same API with Milvus, and integrate with every popular GenAI framework. This webinar is perfect for developers seeking easy-to-use, well-integrated vector databases for their GenAI apps.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
5. •Single point of failure
•More expensive
•Cannot grow in small steps
•Scaling up is failing up [1]
[1] Scalability rules: 50 principles for Scaling Web Sites
WHY?
9. 100% tenant isolation
•Snapshot backup/restore
•Recover to point in time
•Compliance
•Limited authorization risks
100% tenant isoluation
10.
11. •Designed for single tenant, single db
•Move to the cloud, one by one
•Use case I will present
Cloud strategy for legacy applications
12. WONDERING WHO
IS THAT GUY?
HENRY BEEN
Independent Devops & Azure Architect
E: consultancy@henrybeen.nl
T: @henry_been
L: linkedin.com/in/henrybeen
W: henrybeen.nl
13. A (very) short history of multi-tenancy
Tenant C
Standalone App
Tenant B
Tenant
DB
App
Tenant A
14. A (very) short history of multi-tenancy
App
Sharded Multi-tenant Database
Catalog
Tenant
C
Tenant
B
App
Tenant
M
Catalog
Tenants
A,B,C,D
Tenant
A
Tenants
E,F,J,K
Share everything Database per Tenant
Tenant
DB
App
Tenant
L
15. "Incidental Expenses" (CC BY-NC 2.0) by tim ellis
"O’ the Mysteries of Colorado" (CC BY-NC 2.0) by WarzauWynn
25. Catalog
Cust 1 Cust 2 Cust 3 Cust N
2. App uses key to get
connection from catalog
Tenant Databases
4. On subsequent requests, use a
cache!
Tenant Catalog
1. User connects to the app
Selfservice tenant creation and destruction
A. User signs up for a new
tenant
Cust 4
B. App provisions new
tenant db
C. …registers tenant key,
db location in catalog
3. …then connects to correct
tenant database
ARM / SQL Database
Tenant Onboarding Application Connection
Base
TenantDB
Tenant
bacpac
Apps
26. Catalog
Cust 1 Cust 2 Cust 3 Cust N
Tenant Databases
Tenant Catalog
More simple approach: no selfservice
Apps
Management scripts
AAD
27. So…. what do I need?
"tools" (CC BY-NC-ND 2.0) by ᴾᴴᴵᴸ
31. Elastic Database Client Library
using (SqlConnection conn = customerShardMap.OpenConnectionForKey(
customerId,
Configuration.GetCredentialsConnectionString(),
ConnectionOptions.Validate))
{
// Execute a simple command.
SqlCommand cmd = conn.CreateCommand();
cmd.CommandText = @"UPDATE Sales.Customer ….";
// … and more boring stuff ..
}
32. Elastic Transactions
using (var scope = new TransactionScope())
{
using (var conn1 = new SqlConnection(connStrDb1))
{ // … boring stuff … }
using (var conn2 = new SqlConnection(connStrDb2))
{ // … boring stuff }
scope.Complete();
}
33. Cust 1 Cust 2 Cust 3 Cust N
Schema management at scale
Cust 4
Catalog
Manage 1000s of databases as one
Apps
T-SQLT-SQLT-SQL T-SQLT-SQL
Azure Portal
Job
Account
T-SQL
CREATE TABLE…
CREATE INDEX…
INSERT INTO…
SELECT * FROM…
T-SQL Job
SELECT * FROM…
Elastic Jobs
Tenant Databases
Tenant Catalog
Jobs, target groups,
schedules, credentials
34. Cust 1 Cust 2
Tenant Databases
Cust 3 Cust N
Distributed query across tenant databases
Tenant Catalog
Adhoc
Analytics
Cust 4
Catalog
Database locations are
retrieved from catalog
Distributed query plan
External tables
project data from
tenant dbs
PowerBI
Query from any client
Query all tenants as if they are in a single database
Apps
Elastic Query
37. Standalone App Database per tenant Sharded Multi-tenant
Scale High
1-1000s
Very high
1-100,000s
Unlimited
1-1,000,000s
Database cost–per tenant High (sized for peaks) Low (using pools) Lowest (small tenants)
Tenant isolation Very High High Low (high for singletons)
Performance monitoring/mgt. Per-tenant Aggregate + per-tenant Aggregate, per-tenant for
singletons only
Restore single tenant Easy Easy Hard (easy for singletons)
Disaster recovery (all tenants) Moderate
Many components to
recover
Moderate
Patterns address complexity at
scale
Easy (for multi-tenant dbs)
Patterns address singleton
complexity at scale
Development complexity Low Low Medium (sharding)
Operational complexity Medium-High
Individually simple, complex
at scale
Low-Medium
Patterns address complexity at
scale
Low-High
Individual tenant management
is complex
Per-tenant customization Easy Easy Complex
Comparing the models, what we see…
38.
39. DO TRY THIS AT HOME!
HENRY BEEN
Independent Devops & Azure Architect
E: consultancy@henrybeen.nl
T: @henry_been
L: linkedin.com/in/henrybeen
W: henrybeen.nl
Editor's Notes
Licence notice for those parts I copied in from the WingTips presentations
MIT License Copyright (c) Microsoft Corporation. All rights reserved. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE
"O’ the Mysteries of Colorado" (CC BY-NC 2.0) by WarzauWynn
The Masterplan
The Masterplan
Image from Wikipedia, https://upload.wikimedia.org/wikipedia/commons/c/ca/DART_UML_DART_2011_2013_RAW.svg
"tools" (CC BY-NC-ND 2.0) by ᴾᴴᴵᴸ
Real telemetry from an accounting customer’s set of pools (when this data was recorded they had over 300 pools, and each pool had nearly 400 databases sharing 200 DTUs).
As you can see, their aggregate tenant workload is easily supported by 200 DTU pool.
[The pool at 200 DTUs is twice the per-database max of 100 DTUs so would allow 2 databases to be active]