This document provides information about an internship at Amazon Inc. for Asmita Sharma from 2012-2015. It includes details about her role as a Software Development Engineer Intern on the Balance Tracking System team, the development environment and tools used, and an overview of operational and minor project tasks completed during the internship related to migrating packages between Java versions and removing reconciliation functionality from pipelines. A major project goal to support query APIs on S3 is also outlined.
The document discusses different types of tests for microservices including unit tests, service tests, services composition tests, deployment tests, and modern approaches to testing microservices. It provides examples of testing functions, services, interactions, and deploying to containers using tools like Docker. It emphasizes the importance of testing at the unit, integration, deployment levels as well as testing documentation, full stack setups, and chaos engineering.
MS Office install has required the removal of the previously installed version of your Office product on the device or system. Office 365 and other subscription offers the various features, which you do not get when you do not purchase the Office product. The office can be used free, as MS provides the trial versions of every tool. VISIT HERE: Office setup TODAY.
The document discusses implementing reliable, isolated, and unified job submission for a distributed stream processing platform. It proposes:
1) Defining job submission and execution as atomic by requiring the job graph to be persisted before a job is considered submitted, and the job status to be set to DONE before a job is considered completed.
2) Compiling jobs in isolation on the cluster side by packaging user programs and dependencies and executing them in isolated containers to avoid bottlenecks and security risks at the client.
3) Exposing a three-layer unified client interface for deployment, cluster, and job management to provide a programmatic submission approach.
AWS April Webinar Series - Getting Started with Amazon EC2 Container ServiceAmazon Web Services
How do you deploy and manage containerized applications at scale? Amazon ECS is a new AWS service that makes it easy to run and manage Docker-enabled applications across a cluster of Amazon EC2 instances. This webinar will familiarize you with the benefits of containers, introduce Amazon EC2 Container Service (ECS), and demonstrate how to use Amazon ECS for your applications. You will learn how to define, schedule, and stop sets of containers. You will also learn how to access the state of your resources to view running tasks and EC2 instance utilization in your cluster.
Learning Objectives:
• Understand the benefits of containers
• Define and deploy containers on Amazon ECS
• Access cluster state information to track utilization and unning tasks
• Integrate Amazon ECS into your existing software release process or CI/CD (Continuous Integration / Continuous Delivery) pipeline
Who Should Attend:
• Developers, system administrators, Docker users, container users
This document provides an overview of migrating from Oracle SOA 10g to 11g. Key steps include installing the 11g server components, configuring prerequisites, and determining the migration method. There are two primary options - using the JDeveloper migration wizard to migrate projects one by one, or using command line utilities to migrate multiple projects at once. A post-migration checklist outlines steps to verify processes, adapters, metadata, and fault handling configuration.
The document provides an overview of Spring Cloud, including:
- Spring Cloud aims to provide tools for building distributed systems using familiar Spring tools. It wraps other implementation stacks to be consumed via Spring.
- Core components include service discovery with Eureka, client-side load balancing with Ribbon, and circuit breaking with Hystrix.
- Additional tools include the Feign REST client, API gateway capabilities, and integration with Spring Boot.
- Examples demonstrate basic configurations for service registration, load balancing between instances, and using circuit breakers and fallback methods.
Flink currently features different APIs for bounded/batch (DataSet) and streaming (DataStream) programs. And while the DataStream API can handle batch use cases, it is much less efficient in that compared to the DataSet API. The Table API was built as a unified API on top of both, to cover batch and streaming with the same API, and under the hood delegate to either DataSet or DataStream.
In this talk, we present the latest on the Flink community's efforts to rework the APIs and the stack for better unified batch & streaming experience. We will discuss:
- The future roles and interplay of DataSet, DataStream, and Table API
- The new Flink stack and the abstractions on which these APIs will build
- The new unified batch/streaming sources
- How batch and streaming optimizations differ in the runtime, and what the future interplay of batch and streaming execution could look like.
Virtual Flink Forward 2020: Integrate Flink with Kubernetes natively - Yang WangFlink Forward
Currently Flink supports the resource management system YARN and Mesos. However, they were not designed for fast moving cloud native architectures, and they could not support mixed workloads (e.g. batch, streaming, deep learning, web services, etc.) relatively well. At the same time, Kubernetes is evolving very fast to fill those gaps and become the de-facto orchestration framework. So running Flink on Kubernetes is a very basic requirement for many users. In this talk, firstly we will quickly go through Kubernetes architecture and the efforts we have been made to run Flink on Kubernetes. Then we deep dive into the technical details about how to make Flink natively run on Kubernetes. Native means Flink KubernetesResourceManager calls directly the Kubernetes APIs to allocate and release TaskManager pods. Next we will share some practices of application lifecycle management and production optimizations (e.g. high-availability, storage, network, etc.). Finally, we will conclude the talk with advantages for Flink on Kubernetes and a simple demo. This talk is aimed at users and companies who are looking to run Flink on Kubernetes cluster. We assume that the listener has some basic knowledge of cluster orchestration and containers.
The document discusses different types of tests for microservices including unit tests, service tests, services composition tests, deployment tests, and modern approaches to testing microservices. It provides examples of testing functions, services, interactions, and deploying to containers using tools like Docker. It emphasizes the importance of testing at the unit, integration, deployment levels as well as testing documentation, full stack setups, and chaos engineering.
MS Office install has required the removal of the previously installed version of your Office product on the device or system. Office 365 and other subscription offers the various features, which you do not get when you do not purchase the Office product. The office can be used free, as MS provides the trial versions of every tool. VISIT HERE: Office setup TODAY.
The document discusses implementing reliable, isolated, and unified job submission for a distributed stream processing platform. It proposes:
1) Defining job submission and execution as atomic by requiring the job graph to be persisted before a job is considered submitted, and the job status to be set to DONE before a job is considered completed.
2) Compiling jobs in isolation on the cluster side by packaging user programs and dependencies and executing them in isolated containers to avoid bottlenecks and security risks at the client.
3) Exposing a three-layer unified client interface for deployment, cluster, and job management to provide a programmatic submission approach.
AWS April Webinar Series - Getting Started with Amazon EC2 Container ServiceAmazon Web Services
How do you deploy and manage containerized applications at scale? Amazon ECS is a new AWS service that makes it easy to run and manage Docker-enabled applications across a cluster of Amazon EC2 instances. This webinar will familiarize you with the benefits of containers, introduce Amazon EC2 Container Service (ECS), and demonstrate how to use Amazon ECS for your applications. You will learn how to define, schedule, and stop sets of containers. You will also learn how to access the state of your resources to view running tasks and EC2 instance utilization in your cluster.
Learning Objectives:
• Understand the benefits of containers
• Define and deploy containers on Amazon ECS
• Access cluster state information to track utilization and unning tasks
• Integrate Amazon ECS into your existing software release process or CI/CD (Continuous Integration / Continuous Delivery) pipeline
Who Should Attend:
• Developers, system administrators, Docker users, container users
This document provides an overview of migrating from Oracle SOA 10g to 11g. Key steps include installing the 11g server components, configuring prerequisites, and determining the migration method. There are two primary options - using the JDeveloper migration wizard to migrate projects one by one, or using command line utilities to migrate multiple projects at once. A post-migration checklist outlines steps to verify processes, adapters, metadata, and fault handling configuration.
The document provides an overview of Spring Cloud, including:
- Spring Cloud aims to provide tools for building distributed systems using familiar Spring tools. It wraps other implementation stacks to be consumed via Spring.
- Core components include service discovery with Eureka, client-side load balancing with Ribbon, and circuit breaking with Hystrix.
- Additional tools include the Feign REST client, API gateway capabilities, and integration with Spring Boot.
- Examples demonstrate basic configurations for service registration, load balancing between instances, and using circuit breakers and fallback methods.
Flink currently features different APIs for bounded/batch (DataSet) and streaming (DataStream) programs. And while the DataStream API can handle batch use cases, it is much less efficient in that compared to the DataSet API. The Table API was built as a unified API on top of both, to cover batch and streaming with the same API, and under the hood delegate to either DataSet or DataStream.
In this talk, we present the latest on the Flink community's efforts to rework the APIs and the stack for better unified batch & streaming experience. We will discuss:
- The future roles and interplay of DataSet, DataStream, and Table API
- The new Flink stack and the abstractions on which these APIs will build
- The new unified batch/streaming sources
- How batch and streaming optimizations differ in the runtime, and what the future interplay of batch and streaming execution could look like.
Virtual Flink Forward 2020: Integrate Flink with Kubernetes natively - Yang WangFlink Forward
Currently Flink supports the resource management system YARN and Mesos. However, they were not designed for fast moving cloud native architectures, and they could not support mixed workloads (e.g. batch, streaming, deep learning, web services, etc.) relatively well. At the same time, Kubernetes is evolving very fast to fill those gaps and become the de-facto orchestration framework. So running Flink on Kubernetes is a very basic requirement for many users. In this talk, firstly we will quickly go through Kubernetes architecture and the efforts we have been made to run Flink on Kubernetes. Then we deep dive into the technical details about how to make Flink natively run on Kubernetes. Native means Flink KubernetesResourceManager calls directly the Kubernetes APIs to allocate and release TaskManager pods. Next we will share some practices of application lifecycle management and production optimizations (e.g. high-availability, storage, network, etc.). Finally, we will conclude the talk with advantages for Flink on Kubernetes and a simple demo. This talk is aimed at users and companies who are looking to run Flink on Kubernetes cluster. We assume that the listener has some basic knowledge of cluster orchestration and containers.
The document discusses how to operationalize R models by turning R analytics into web services using Microsoft R Server. Key points include:
- R analytics can be published as web services with one line of code using Swagger-based REST APIs for easy consumption by any programming language.
- Web services can be deployed on Windows, SQL Server, Linux, and Hadoop platforms both on-premises and in the cloud for fast scoring in real time and batch modes.
- R Server allows scaling to grids for powerful computing with load balancing and includes diagnostic and capacity evaluation tools.
Implementing Continuous Delivery with Enterprise MiddlewareXebiaLabs
This document discusses implementing continuous delivery with enterprise middleware. It begins with introductions of the speakers and an overview of ThoughtWorks Studios and XebiaLabs. It then provides definitions and explanations of continuous delivery. The remainder of the document discusses approaches to continuous delivery in the enterprise including dealing with complex dependency trees, diverse deployment landscapes, and integration with release management. It provides an example continuous delivery pipeline for a Java EE application and how it can be optimized for an enterprise approach.
MuleSoft Surat Virtual Meetup#31 - Async API, Process Error, Circuit Breaker ...Jitendra Bafna
The document provides details about an upcoming MuleSoft Surat Meetup event on AsyncAPI, error handling plugins, circuit breaker policies, and canary deployments. It includes the date, time, speakers, and agenda. The event will be recorded and uploaded within 24 hours. Attendees are encouraged to provide feedback through a form. The speaker, Jitendra Bafna, is introduced with his background and expertise in API and integration technologies including MuleSoft, AWS, and OCI. Demonstrations will be provided on using Async APIs, an event error handler plugin, a circuit breaker policy, and canary deployments in MuleSoft. A Q&A session will conclude the event.
Lessons Learned Building a Connector Using Kafka Connect (Katherine Stanley &...confluent
While many companies are embracing Apache Kafka as their core event streaming platform they may still have events they want to unlock in other systems. Kafka Connect provides a common API for developers to do just that and the number of open-source connectors available is growing rapidly. The IBM MQ sink and source connectors allow you to flow messages between your Apache Kafka cluster and your IBM MQ queues. In this session we will share our lessons learned and top tips for building a Kafka Connect connector. We'll explain how a connector is structured, how the framework calls it and some of the things to consider when providing configuration options. The more Kafka Connect connectors the community creates the better, as it will enable everyone to unlock the events in their existing systems.
Service Discovery in Distributed System with DCOS & Kubernettes. - Sahil SawhneyKnoldus Inc.
This pdf walks you through how service discovery could help us to facilitate inter-service communication in a distributed environment.
We would be targetting how service discovery is achieved in Kubernetes and DC/OS, the leading distributed infra-facilitators
This document provides guidance on integrating Jenkins with UFT by:
1. Deploying Jenkins and Tomcat on Windows, and configuring environment variables.
2. Installing the HP Application Automation Tools plugin in Jenkins to enable triggering UFT, QTP, ALM and other HP tests.
3. Configuring a Jenkins job to execute UFT test cases from the file system and archive results.
DevOps is a one-stop solution for all software engineering. From creating the software to implementing it in real-time, DevOps does all. This creates an infinite demand for excellent DevOps developers in the market. Since the platform is quite fast and effective, it is attracting the attention of many organizations that are looking to develop a software solution for their own business. Thus, here are a few DevOps interview questions that can help you crack an interview.
This talk is about monitoring with Prometheus. A progression is shown from monitoring concept, to Micrometer, Prometheus and Grafana.
Presented at Alithya by Richard Langlois and Gervais Naoussi, on September 19th, 2018
Testing Web Apps with Spring Framework 3.2Sam Brannen
This document provides an overview of the new testing features in the Spring Framework 3.2, including the Spring TestContext Framework and the new Spring MVC Test Framework. The Spring TestContext Framework allows for annotation-driven unit and integration testing of Spring-managed components. It supports loading application contexts, dependency injection of test instances, and transactional test management. The new Spring MVC Test Framework enables server-side testing of Spring MVC applications without requiring a servlet container. It provides a fluent API for building mock requests and asserting mock responses. The framework also supports testing client-side interactions using the RestTemplate.
The document outlines a project to build a feature for hosting reinforcement learning challenges on EvalAI. It describes the flow of submissions, how submissions are managed by queuing them and having an RL worker deploy the environment and agent containers on Kubernetes for evaluation. It provides an example challenge of balancing a pole on a cart and next steps to host more complex challenges and optimize resource usage on EvalAI.
Kafka on Kubernetes: Does it really have to be "The Hard Way"? (Viktor Gamov,...confluent
When it comes to choosing a distributed streaming platform for real-time data pipelines, everyone knows the answer - Apache Kafka! And when it comes to deploying applications at scale without needing to integrate different pieces of infrastructure yourself, the answer nowadays is increasingly Kubernetes. However, with all great things, the devil is truly in the details. While Kubernetes does provide all the building blocks that are needed, a lot of thought is required to truly create an enterprise-grade Kafka platform that can be used in production. In this technical deep dive, Michael and Viktor will go through challenges and pitfalls of managing Kafka on Kubernetes as well as the goals and lessons learned from the development of the Confluent Operator for Kubernetes.
NOTE: This talk together with Michael Ng from Confluent
Delivery pipelines at Symphony Talent - Present and FutureNathan Jones
This talk presents the pros and cons of some of the current (as of 2016) software delivery pipeline tooling at Symphony Talent and the steps being taken to create a unified pipeline for code, configuration and infrastructure changes using Puppet, Terraform and Packer.
Productivity Acceleration Tools for SOA TestersWSO2
- soapUI and Apache JMeter are popular tools for testing SOA and web services. soapUI allows automated testing of SOAP and REST services while JMeter is useful for load and performance testing.
- Examples showed how to use soapUI for testing SOAP services with authentication, assertions and REST services. JMeter examples included dynamic data testing, accessing APIs through tokens, and running tests in headless mode.
- Tips included using HTTPClient4 for load testing, disabling views for high throughput, external plugins, and isolating client/server for accurate performance metrics.
Lambda is the next stage in the evolution of the AWS platform. It allows you to build reactive, event-driven systems that are easy to deploy, update and scale. Amazon manages all the undifferentiated heavy-lifting for you so you can focus on delivering value to your customers with even greater speed and cost efficiency.
Join Yan in this talk as we take a deep dive through AWS Lambda and the Serverless framework.
We'll see how to start building reactive systems using AWS Lambda, Kinesis and API Gateway, without having to manage any servers. And, you only pay for your services when they are used. We'll discuss lessons learned, best practices and current limitations with AWS Lambda.
We'll also get to know the Serverless framework, which helps automate both deployment and versioning so that you can better focus on the things that matter to your customers.
Modern CI/CD in the microservices world with KubernetesMikalai Alimenkou
In this talk, we will go through the design process of modern CI/CD for the microservices-based system with Kubernetes support. We will discuss how to verify consistency between microservices, apply different levels of quality gates and promote artifacts between environments. Thanks to Kubernetes we will review different approaches of environment resources optimization for development needs during CI/CD cycles.
DevOps on the AWS Cloud introduces DevOps practices that can help companies innovate faster for customers. Traditional development models are becoming obsolete as business becomes more software-driven and users expect continuous improvement and stability. DevOps practices like infrastructure as code, microservices, logging and monitoring, and continuous integration/delivery enabled by AWS services can help increase business agility while decreasing development cycle times. Chef provides tools that integrate with AWS to enable common DevOps practices like provisioning infrastructure with code and automating continuous delivery workflows. Gannett uses Chef and AWS together in their development pipeline to test infrastructure changes and application deployments.
Simplify and Scale Enterprise Spring Apps in the Cloud | March 23, 2023VMware Tanzu
- Azure Spring Apps is a fully managed service for deploying and managing Spring Boot apps in the cloud without having to learn or manage Kubernetes. It provides auto-scaling, security, high availability, and auto-patching capabilities.
- Managing software updates and security patches across multiple components like apps, dependencies, JDKs, OSes, Kubernetes, etc. is challenging due to the large volume of updates and need for testing and approvals. Azure Spring Apps reduces this burden through auto-patching which applies critical security updates automatically during scheduled maintenance windows.
- Auto-patching helps customers stay ahead of security threats and vulnerabilities by proactively applying patches for exposed issues like Log4j, OpenSSL vulnerabilities,
AWS re:Invent 2016: Building a Platform for Collaborative Scientific Research...Amazon Web Services
This session discusses the architecture, formation, and usage of a collaborative HPC/big data scientific research and analysis environment on AWS. The pharmaceutical industry trend toward joint ventures and collaborations has created a need for new platforms in which to work together. We'll dive into architectural decisions for building collaborative systems. Examples include how such a platform allowed Human Longevity, Inc. to accelerate software deployment to production in a fast-paced research environment, and how Celgene uses AWS for research collaboration with outside universities and foundations.
The document discusses how to operationalize R models by turning R analytics into web services using Microsoft R Server. Key points include:
- R analytics can be published as web services with one line of code using Swagger-based REST APIs for easy consumption by any programming language.
- Web services can be deployed on Windows, SQL Server, Linux, and Hadoop platforms both on-premises and in the cloud for fast scoring in real time and batch modes.
- R Server allows scaling to grids for powerful computing with load balancing and includes diagnostic and capacity evaluation tools.
Implementing Continuous Delivery with Enterprise MiddlewareXebiaLabs
This document discusses implementing continuous delivery with enterprise middleware. It begins with introductions of the speakers and an overview of ThoughtWorks Studios and XebiaLabs. It then provides definitions and explanations of continuous delivery. The remainder of the document discusses approaches to continuous delivery in the enterprise including dealing with complex dependency trees, diverse deployment landscapes, and integration with release management. It provides an example continuous delivery pipeline for a Java EE application and how it can be optimized for an enterprise approach.
MuleSoft Surat Virtual Meetup#31 - Async API, Process Error, Circuit Breaker ...Jitendra Bafna
The document provides details about an upcoming MuleSoft Surat Meetup event on AsyncAPI, error handling plugins, circuit breaker policies, and canary deployments. It includes the date, time, speakers, and agenda. The event will be recorded and uploaded within 24 hours. Attendees are encouraged to provide feedback through a form. The speaker, Jitendra Bafna, is introduced with his background and expertise in API and integration technologies including MuleSoft, AWS, and OCI. Demonstrations will be provided on using Async APIs, an event error handler plugin, a circuit breaker policy, and canary deployments in MuleSoft. A Q&A session will conclude the event.
Lessons Learned Building a Connector Using Kafka Connect (Katherine Stanley &...confluent
While many companies are embracing Apache Kafka as their core event streaming platform they may still have events they want to unlock in other systems. Kafka Connect provides a common API for developers to do just that and the number of open-source connectors available is growing rapidly. The IBM MQ sink and source connectors allow you to flow messages between your Apache Kafka cluster and your IBM MQ queues. In this session we will share our lessons learned and top tips for building a Kafka Connect connector. We'll explain how a connector is structured, how the framework calls it and some of the things to consider when providing configuration options. The more Kafka Connect connectors the community creates the better, as it will enable everyone to unlock the events in their existing systems.
Service Discovery in Distributed System with DCOS & Kubernettes. - Sahil SawhneyKnoldus Inc.
This pdf walks you through how service discovery could help us to facilitate inter-service communication in a distributed environment.
We would be targetting how service discovery is achieved in Kubernetes and DC/OS, the leading distributed infra-facilitators
This document provides guidance on integrating Jenkins with UFT by:
1. Deploying Jenkins and Tomcat on Windows, and configuring environment variables.
2. Installing the HP Application Automation Tools plugin in Jenkins to enable triggering UFT, QTP, ALM and other HP tests.
3. Configuring a Jenkins job to execute UFT test cases from the file system and archive results.
DevOps is a one-stop solution for all software engineering. From creating the software to implementing it in real-time, DevOps does all. This creates an infinite demand for excellent DevOps developers in the market. Since the platform is quite fast and effective, it is attracting the attention of many organizations that are looking to develop a software solution for their own business. Thus, here are a few DevOps interview questions that can help you crack an interview.
This talk is about monitoring with Prometheus. A progression is shown from monitoring concept, to Micrometer, Prometheus and Grafana.
Presented at Alithya by Richard Langlois and Gervais Naoussi, on September 19th, 2018
Testing Web Apps with Spring Framework 3.2Sam Brannen
This document provides an overview of the new testing features in the Spring Framework 3.2, including the Spring TestContext Framework and the new Spring MVC Test Framework. The Spring TestContext Framework allows for annotation-driven unit and integration testing of Spring-managed components. It supports loading application contexts, dependency injection of test instances, and transactional test management. The new Spring MVC Test Framework enables server-side testing of Spring MVC applications without requiring a servlet container. It provides a fluent API for building mock requests and asserting mock responses. The framework also supports testing client-side interactions using the RestTemplate.
The document outlines a project to build a feature for hosting reinforcement learning challenges on EvalAI. It describes the flow of submissions, how submissions are managed by queuing them and having an RL worker deploy the environment and agent containers on Kubernetes for evaluation. It provides an example challenge of balancing a pole on a cart and next steps to host more complex challenges and optimize resource usage on EvalAI.
Kafka on Kubernetes: Does it really have to be "The Hard Way"? (Viktor Gamov,...confluent
When it comes to choosing a distributed streaming platform for real-time data pipelines, everyone knows the answer - Apache Kafka! And when it comes to deploying applications at scale without needing to integrate different pieces of infrastructure yourself, the answer nowadays is increasingly Kubernetes. However, with all great things, the devil is truly in the details. While Kubernetes does provide all the building blocks that are needed, a lot of thought is required to truly create an enterprise-grade Kafka platform that can be used in production. In this technical deep dive, Michael and Viktor will go through challenges and pitfalls of managing Kafka on Kubernetes as well as the goals and lessons learned from the development of the Confluent Operator for Kubernetes.
NOTE: This talk together with Michael Ng from Confluent
Delivery pipelines at Symphony Talent - Present and FutureNathan Jones
This talk presents the pros and cons of some of the current (as of 2016) software delivery pipeline tooling at Symphony Talent and the steps being taken to create a unified pipeline for code, configuration and infrastructure changes using Puppet, Terraform and Packer.
Productivity Acceleration Tools for SOA TestersWSO2
- soapUI and Apache JMeter are popular tools for testing SOA and web services. soapUI allows automated testing of SOAP and REST services while JMeter is useful for load and performance testing.
- Examples showed how to use soapUI for testing SOAP services with authentication, assertions and REST services. JMeter examples included dynamic data testing, accessing APIs through tokens, and running tests in headless mode.
- Tips included using HTTPClient4 for load testing, disabling views for high throughput, external plugins, and isolating client/server for accurate performance metrics.
Lambda is the next stage in the evolution of the AWS platform. It allows you to build reactive, event-driven systems that are easy to deploy, update and scale. Amazon manages all the undifferentiated heavy-lifting for you so you can focus on delivering value to your customers with even greater speed and cost efficiency.
Join Yan in this talk as we take a deep dive through AWS Lambda and the Serverless framework.
We'll see how to start building reactive systems using AWS Lambda, Kinesis and API Gateway, without having to manage any servers. And, you only pay for your services when they are used. We'll discuss lessons learned, best practices and current limitations with AWS Lambda.
We'll also get to know the Serverless framework, which helps automate both deployment and versioning so that you can better focus on the things that matter to your customers.
Modern CI/CD in the microservices world with KubernetesMikalai Alimenkou
In this talk, we will go through the design process of modern CI/CD for the microservices-based system with Kubernetes support. We will discuss how to verify consistency between microservices, apply different levels of quality gates and promote artifacts between environments. Thanks to Kubernetes we will review different approaches of environment resources optimization for development needs during CI/CD cycles.
DevOps on the AWS Cloud introduces DevOps practices that can help companies innovate faster for customers. Traditional development models are becoming obsolete as business becomes more software-driven and users expect continuous improvement and stability. DevOps practices like infrastructure as code, microservices, logging and monitoring, and continuous integration/delivery enabled by AWS services can help increase business agility while decreasing development cycle times. Chef provides tools that integrate with AWS to enable common DevOps practices like provisioning infrastructure with code and automating continuous delivery workflows. Gannett uses Chef and AWS together in their development pipeline to test infrastructure changes and application deployments.
Simplify and Scale Enterprise Spring Apps in the Cloud | March 23, 2023VMware Tanzu
- Azure Spring Apps is a fully managed service for deploying and managing Spring Boot apps in the cloud without having to learn or manage Kubernetes. It provides auto-scaling, security, high availability, and auto-patching capabilities.
- Managing software updates and security patches across multiple components like apps, dependencies, JDKs, OSes, Kubernetes, etc. is challenging due to the large volume of updates and need for testing and approvals. Azure Spring Apps reduces this burden through auto-patching which applies critical security updates automatically during scheduled maintenance windows.
- Auto-patching helps customers stay ahead of security threats and vulnerabilities by proactively applying patches for exposed issues like Log4j, OpenSSL vulnerabilities,
AWS re:Invent 2016: Building a Platform for Collaborative Scientific Research...Amazon Web Services
This session discusses the architecture, formation, and usage of a collaborative HPC/big data scientific research and analysis environment on AWS. The pharmaceutical industry trend toward joint ventures and collaborations has created a need for new platforms in which to work together. We'll dive into architectural decisions for building collaborative systems. Examples include how such a platform allowed Human Longevity, Inc. to accelerate software deployment to production in a fast-paced research environment, and how Celgene uses AWS for research collaboration with outside universities and foundations.
WinOps Conf 2016 - Ed Wilson - Configuration Management with Azure DSCWinOps Conf
Configuration management at scale, even with PowerShell and PowerShell DSC, can quickly become complicated, error-prone, and unruly. The new Desired State Configuration (DSC) feature of Azure Automation, in the Microsoft’s Operations Management Suite, provides a solution - a central, secure location for all your PowerShell DSC items and reports, that is scalable, reliable, and highly-available. Come learn how it can transform configuration management across your organization, using the PowerShell tools and knowledge you already have.
Pivotal CloudFoundry on Google cloud platformRonak Banka
This document is a slide presentation by Ronak Banka on using Pivotal Cloud Foundry (PCF) and Google Cloud Platform (GCP) together. It discusses how PCF provides a platform for deploying applications on GCP that enables both developer and operator productivity through features like automated deployments, service integration, and operations. It also highlights benefits of using PCF on GCP like performance, scale, cost savings, and access to differentiated GCP services.
The document provides an overview of Azure DevOps and why JavaScript developers should use it. It discusses features like source control, boards for tracking work items, pipelines for continuous integration and delivery, and testing. It also includes a demo of setting up a sample Create React App project in Azure DevOps, including configuring a pipeline to build and deploy the app to an Azure App Service. Resources for learning more about Azure DevOps, using it with JavaScript projects, and understanding Git are also provided.
20211028 ADDO Adapting to Covid with Serverless Craeg Strong Ariel PartnersCraeg Strong
This case study describes how we leveraged serverless technology and the AWS serverless application model (SAM) to support the needs of virtual training classes for a major US Federal agency. Our firm was excited to be selected as the main training partner to help a major US Federal government agency roll out Agile and DevOps processes across an organization comprising more than 1500 people. And then the pandemic hit—and what was to have been a series of in-person classes turned 100% virtual! We created a set of fully populated docker images containing all of the test data, plugins, and scenarios required for the student exercises. For our initial implementation, we simply pre-loaded our docker images into elastic beanstalk and then replicated them as many times as needed to provide the necessary number of instances for a given class. While this worked out fine at first, we found a number of shortcomings as we scaled up to more students and more classes. Eventually we came up with a much easier solution using serverless technology: we stood up a single page application that could kickoff tasks using AWS step functions to run docker images in elastic container service, all running under AWS Fargate. This application is a perfect fit for serverless technology and describing our evolution to serverless and SAM may help you gain insights into how these technologies may be beneficial in your situation.
AWS re:Invent 2016: Infrastructure Continuous Delivery Using AWS CloudFormati...Amazon Web Services
In this session, we will review ways to manage the lifecycle of your dev, test, and production infrastructure using CloudFormation. Learn how to architect your infrastructure through loosely coupled stacks using cross-stack references, tightly coupled nested stacks and other best practices. Learn how to use CloudFormation to provision and manage a continuous deployment pipeline for your infrastructure-as-code. Automate deployment of new development environments as your infrastructure evolves, promote your new architecture for testing, and deploy changes to production.
You've heard about Continuous Integration and Continuous Deilvery but how do you get code from your machine to production in a rapid, repeatable manner? Let a build pipeline do the work for you! Sam Brown will walk through the how, the when and the why of the various aspects of a Contiuous Delivery build pipeline and how you can get started tomorrow implementing changes to realize build automation. This talk will start with an example pipeline and go into depth with each section detailing the pros and cons of different steps and why you should include them in your build process.
Azure for SharePoint Developers - Workshop - Part 3: Web ServicesBob German
This document discusses .NET Core and ASP.NET Core, which provide a modular framework for building web applications and services across platforms. It covers setting up a sample ASP.NET Core web API project locally and deploying it to Azure App Service. It also discusses key Azure services like SQL Database, Resource Manager, Key Vault, and monitoring with Application Insights that can be used to build the application.
CON302_Building a CICD Pipeline for Containers on Amazon ECSAmazon Web Services
Containers can make it easier to scale applications in the cloud, but how do you set up your CI/CD workflow to automatically test and deploy code to containerized apps? In this session, we explore how developers can build effective CI/CD workflows to manage their containerized code deployments on AWS. Ajit Zadgaonkar, director of engineering and operations at Edmunds, walks through best practices for CI/CD architectures used by his team to deploy containers. We also deep dive into topics such as how to create an accessible CI/CD platform and architect for safe Blue-Green deployments.
The acute software testing process, tools we use and tools we\'ve developed. We test with both open source and licensed-based products, such as Selenium and Mercury.
Infrastructure Continuous Delivery Using AWS CloudFormationAmazon Web Services
This document discusses using AWS CloudFormation and AWS CodePipeline to implement infrastructure continuous delivery. It begins by explaining the need for infrastructure as code and continuous delivery workflows for infrastructure changes. AWS CloudFormation allows treating infrastructure as code by authoring templates and provisioning AWS resources from them. AWS CodePipeline can then be used to automate building, testing and deploying infrastructure changes as code is updated. The document demonstrates decomposing a sample application into CloudFormation templates and setting up a CodePipeline to continuously deliver changes. It provides examples of how to model pipelines for network resources and application components separately with dependencies.
This document discusses SPN's journey to implement CI/CD on AWS. It begins with describing SPN's original process for delivering services which involved many manual steps. It then discusses DevOps goals of faster delivery, lower failure rates, and faster recovery compared to the original process. The document outlines using AWS services like CloudFormation, OpsWorks, and Auto Scaling to implement CI/CD and automate deploying a sample analytic engine service. Lessons learned include automating as much as possible, splitting CloudFormation templates, focusing on updates without impacting SLAs, and emphasizing monitoring and testing.
Functional Continuous Integration with Selenium and HudsonDavid Jellison
This slide deck illustrates Constant Contact's approach to running sets of regression test suites on a regular schedule using SeleniumRC and Hudson. Hudson is a continuous integration server designed for building applications and running unit test unattended, and storing run report and metric artifacts. Hudson can also process a variety of different types of jobs, including running SeleniumRC Java test cases using JUnit as the test runner. SeleniumRC can be run unattended on multiple slave computers in parallel, each running SeleniumRC, to quickly run through many test cases.
2. Profile
Name – Asmita Sharma
Roll No. – 06
Year – 2012- 2015
University – Delhi University
University Mentor – Ms. Neelima
Gupta
Organization – Amazon Inc.
Manager – Mr. Ramesh Krishna
Kumar
Mentor – Itiyama Sadana
Team – BTS
Platform – Ecommerce Payments
Role – Software Development
Engineer Intern
Internship Start Date – 16 Feb 2015
Internship End Date – 15 Aug 2015
5. Glossary
Pipeline : A tool for modeling your release process and adding automation to it.
Version Set : A snapshot of application dependencies.
SQS : Simple Queuing Service
DynamoDB : NoSQL Database
S3 : Simple Storage Service
Workflow : Sequence of executable steps.
SWF : Simple Workflow
Environment Stages : Association between hosts and Apollo environments.
Alpha : Environment stage receiving no traffic.
Beta : Environment stage receiving minimal traffic for testing.
Prod : Environment stage receiving real-time traffic.
6. BTS - Overview
BTS (Balance Tracking System) is a Global Stored Value Platform of Amazon.
BTS is a part of ecommerce payments platform of Amazon.
It allows any business in Amazon to create instruments and track funds movement for
them.
It also provides simple APIs for querying balance of an instrument and history of fund
movement transactions done on an instrument.
8. Operational Task – Code Change
Changes to Config file involved adding,
removing and updating versions of build
and runtime dependencies to latest versions
supporting JAVA 8.
Config file changes also involved resolving
conflicting dependencies of the package
with it’s upstream and downstream
packages.
Changes to build.xml involved adding
properties for classpath of new packages
and few more changes to make upstream
JAVA 7 packages compatible with JAVA 8
migrated package.
Changes to Spring configuration xml files
involved modification of syntax for
dependencies migrated to latest versions
supporting JAVA 8.
Changes to Spring configuration xml files
also involved using classpath approach for
integrating spring packages instead of
providing url of spring packages.
9. Operational Task – Merge dependencies
Live is a version set which contains all the versions of all the packages required within
amazon.
Every package corresponds to a version set which contains all the dependencies of the
packages in that version set.
To upgrade or add a new version of any dependency, we need to merge that
dependency into the version set from live.
10. Operational Task – Testing
A package is first tested in the workplace itself using brazil CLI commands and targets
specified in build.xml.
After these tests are passed, any package dependent on this package is merged to
workspace and tested to run with these changes.
When above tests pass successfully, peer review is done and suggested improvements
are incorporated.
After peer review is complete , the package is pushed to a temporary branch of the
repository.
11. Operational Task – Deployment
The package from the temporary branch is build into the version set and deployed to the
pipeline.
It is tested at various stages (namely Alpha and Beta) of pipeline through regression
suites.
After it passes these stages and logs of the hosts at these stages are verified, it is
deployed to Prod.
12. Operational Task – Migrate Pipelines
Migrating pipeline involves merging all packages migrated to Java 8 that belong to that
pipeline or are a dependency of the packages belonging to the pipeline.
Any conflicts arising while merging these packages have to be resolved and then
merged again.
Logs of hosts at each stage (Alpha , Beta, Prod) have to be verified after this step also.
13. Minor Project
Objective : To remove reconciliation from
PerseusClient/development-clone and
MonadBalanceServiceListener pipeline.
Packages :
PerseusClient
PerseusClientInterface
PerseusTestClient
PerseusTestSuite
NotificationParser
ModelConverter
BalanceUpdateBusinessClient
BalanceQueryServiceSAO
SubTasks :
Code Change
Modifying Regressions
Modifying Unit Test Cases
Resetting AWS Credentials
Testing
Major Version Upgrade
Write Change Management (CM)
Document
Deployment
14. Minor Project – Code Change
Removing Tracker Table and Marker Table instances along with their interface and unit test cases.
Removing all SWF (Simple Workflow) workflows and corresponding unit tests.
Removing dependencies from Config file which are no longer needed.
Removing brazil-config file properties that are no longer required.
Removing unnecessary targets and properties from build.xml.
Removing reconciler instances from all packages.
Deleting spring configuration files corresponding to reconciler .
Removing all packages used by reconcilera which are no longer required.
15. Minor Project – Modifying Regressions
Removing DynamoDB instances previously used by tracker table and marker table.
Modifying regressions to test only notification functionality and neglect reconciliation.
Events in modified regression suite will not be dropped to test reconciler functionality.
All regressions related to reconciler and workflows will be deleted.
In modified regression suite, only notification listener will be tested by updating a dummy instrument
and verifying that it’s notification reaches event listener through SQS (Simple Queuing Service).
Reconciler instances and unnecessary dependencies will be removed from Config and xml files.
16. Minor Project – Modifying Unit Test Cases
Added unit test for Event Details class
Added spring beans to set S3 (Simple Storage Service) and AWS (Amazon Web Services) credentials
and configured the same in spring configuration xml files and brazil-config.
Removed unit test cases for workflows and dynamoDB tables.
Removed unit test cases involving missing sequence number tests and updated event listener test for
the same.
Modularized a function by shifting s3 upload functionality from the function to a separate method.
17. Minor Project – Resetting AWS Credentials
Earlier the AWS credentials were set using Odin which did not allow the credentials to be seamlessly
retrieved dynamically.
Hence, used AWSCredentialProvider to set AWS credentials for SQS in PerseusClient and
PerseusTestClient using spring beans and brazil-config.
This approach eliminates the race condition where dynamic credentials could change in between
calls to getAccessKey/getSecretAccessKey/getSessionToken and leave the customer with invalid
credentials.
This also makes it very easy for the AWSCredentialsProvider implementation to return different types of
credentials objects.
18. Minor Project – Testing
Created a child environment of the Alpha stage of the PerseusClient-development
pipeline and deployed it on local machine using Apollo.
Attached my workspace and modified packages to this child environment using brazil.
Activated the child environment using brazil.
Logged in to the remote host set up at Alpha stage of pipeline using SSH command.
Verified the logs running on the host.
Deactivated the parent environment.
Logged in to the SWF console and verified that the workflows have stopped executing.
19. Minor Project – Major Version Upgrade
Upgraded the major version of all packages to 2.0.
Changes were made to Config file and build.xml file of all packages.
20. Major Project
Objective : To support Query APIs on S3.
API:
GetEvent()
GetInstrumentEvents()
GetChildEvents()
GetInitializeStatus()
SubTasks :
Data Analysis
Design Approach
Write Design Document
Environment Setup
Code Development
Writing Unit Tests
Deriving and Coding Regressions
Testing
Deployment
21. Major Project – Data Analysis
Objective : To analyze up to 3 months old
logs to gather requirements.
API :
GetInstrumentEvents()
SubTasks :
Figure out data required from logs
Write Script to gather data from logs
Run script of hosts containing logs
Post-process data for concluding
requirements
Represent data graphically
Output :
Domains accessing more than year old
events
Total number of events returned by
each API call
Number of more than year old , more
than six month old and more than three
month old events returned by each API
call
Number of calls returning more than
year old events made by each domain
Difference between API call time and
creation time of oldest event returned
by each API call
22. Major Project – Design Approach
Objective : To come up with an approach
that best fits the requirements of all the four
APIs with optimal use of resources as per the
required performance.
SubTasks :
Understand the functionality , input
fields and output fields of the APIs
Figure out the required latencies
Analyze available tools for suitability as
per the requirements
Devise design approaches
Calculate storage, latencies and cost
metrics for each approach
Analyze feasibility, simplicity of
development, scalability and
maintenance of each approach
Choose between Sync and Async path
Compare candidate approaches
Choose the best fit
23. Major Project – Design Document Index
1.1 Prior Knowledge
1.1.1 APIs
1.1.2 EventID Format
1.1.3 InstrumentID Format
1.1.4 S3 File Format
1.2 Data Analysis
1.2.1 Script
1.2.2 Requirements
1.3 Design Approach
1.3.1 Storing S3 files on hourly basis and
scanning files for required instrument
1.3.2 Creating index on instrument ID per day
1.3.2.1 Index Structure
1.3.2.1.1 Start_File and End_File field
size calculation
1.3.2.2 Metrics
1.3.2.3 Cost of storing indexes in S3
1.3.2.4 Cost of storing indexes in
DynamoDB
1.3.2.5 Comparison
1.3.3 Creating instrument level indexes
1.3.4 Using CloudSearch to index S3 files
1.3.4.1 Costing
24. Yet To Do…
Minor Project
Deployment
Writing Change Management
Document
Major Project
Environment Setup
Code Development
Writing Unit Tests
Deriving and Coding Regressions
Testing
Deployment