Everything about Microservice.pptx
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Brief description: This ppt attempts to give an overview of microservices. It covers many topics but especially focuses on the design patterns of microservices. This ppt covers everything from history of how microservices came to be, to the different ways they communicate with each other, and their various design patterns and finally how the microservices can be deployed. Long description: The ppt begins with why the need was felt to shift from monolithic architecture, to how it evolved to SOA and finally microservice architecture. It explains what microservices are, and the different ways ( synchronous and asynchronous ) the microservices communicate with each other. It also briefly talks about REST APIs. Further, it delves into all the microservice patterns: Config server, naming server, Circuit breaker, API Gateway, and distributed tracing. Finally, it attempts to explain how to deploy microservices using Docker and Kubernetes
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Outline: presentation summary
- intro microservices objectives, focus on decoupled collaboration
- demo four mservices in different technologies (Node, Java, ...) ; no direct dependencies; show the code (running on its own), show the packing into a container and the step of running the containers on a container management platform, using both Kubernetes and a Container Cloud Service (later on this will further the point of collaborating between microservices that are widely separated)
- discuss generic capabilities of a microservices platform (facilities required in many microservices that should be available as microservice - such as cache, log, authenticate (and compare with Java EE application server)
- demo a microservice providing a generic cache functionality (based on MongoDB)
- outline the desired choreography (a four step workflow that requires participation from various microservices); briefly discuss routing slips and the Saga pattern
- discuss use of events and need of event bus
- intro Kafka
- demo pub and sub from each mservice to Kafka
- link IFTTT to Kafka (for demo: use ngrok to expose local Kafka to IFTTT cloud)
- demo end-to-end Social event=>IFTTT=>Kafka=>choreographed mservices=> final result
- demo: extend one of the microservices: change the code, package a new container image version and update the running version in the container platform; demonstrate that new workflows leverage the new version
- demo: move a microservice from on premises to cloud - showing that the decoupled nature of the mservices mean that this move does not have any impact
- demo: show a change in the logic of the routing slip; none of the mservices require any change for a changed workflow choreography to be executed
- discuss cloud deployment of event bus + mservices
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Microservices are independent, encapsulated entities that produce meaningful results and business functionality in tentative collaboration. Microservices need a platform to run on and to provide generic capabilities such as data caching, an event bus, access to RDBMS and File System. This platform should handle scaling and fail over of the microservices.
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Outline: presentation summary
- intro microservices objectives, focus on decoupled collaboration
- demo four mservices in different technologies (Node, Java, ...) ; no direct dependencies; show the code (running on its own), show the packing into a container and the step of running the containers on a container management platform, using both Kubernetes and a Container Cloud Service (later on this will further the point of collaborating between microservices that are widely separated)
- discuss generic capabilities of a microservices platform (facilities required in many microservices that should be available as microservice - such as cache, log, authenticate (and compare with Java EE application server)
- demo a microservice providing a generic cache functionality (based on MongoDB)
- outline the desired choreography (a four step workflow that requires participation from various microservices); briefly discuss routing slips and the Saga pattern
- discuss use of events and need of event bus
- intro Kafka
- demo pub and sub from each mservice to Kafka
- link IFTTT to Kafka (for demo: use ngrok to expose local Kafka to IFTTT cloud)
- demo end-to-end Social event=>IFTTT=>Kafka=>choreographed mservices=> final result
- demo: extend one of the microservices: change the code, package a new container image version and update the running version in the container platform; demonstrate that new workflows leverage the new version
- demo: move a microservice from on premises to cloud - showing that the decoupled nature of the mservices mean that this move does not have any impact
- demo: show a change in the logic of the routing slip; none of the mservices require any change for a changed workflow choreography to be executed
- discuss cloud deployment of event bus + mservices
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Containers are changing the compute landscape and for NFVi support of Containers is key. Kubernetes is a well known Container Cluster Management software and this is slide deck from a talk given in Opendaylight Summit 2016. This slide gives an insight about Microservice architecture, Kuberentes and how it can be integrated with ODL. Session Video can be found at https://www.youtube.com/watch?v=a4_pkp2qiX8&list=PL8F5jrwEpGAiRCzJIyboA8Di3_TAjTT-2
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Microservices architecture is presented as a solution to problems with monolithic architecture. Each microservice has a specific focus and functionality. Benefits include improved testability, loose coupling, and ability to develop, deploy and scale services independently. Challenges include increased complexity of developing, testing and operating distributed systems.
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Prem Sankar's presentation from the 2017 Open Networking Summit.
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We will demo deployments in Azure for the various models.
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Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Embedded machine learning-based road conditions and driving behavior monitoring
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Design and optimization of ion propulsion drone
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
学校原版美国波士顿大学毕业证学历学位证书原版一模一样
原版一模一样【微信：741003700 】【美国波士顿大学毕业证学历学位证书】【微信：741003700 】学位证，留信认证（真实可查，永久存档）offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Digital Twins Computer Networking Paper Presentation.pptx
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.
AI for Legal Research with applications, tools
AI applications in legal research include rapid document analysis, case law review, and statute interpretation. AI-powered tools can sift through vast legal databases to find relevant precedents and citations, enhancing research accuracy and speed. They assist in legal writing by drafting and proofreading documents. Predictive analytics help foresee case outcomes based on historical data, aiding in strategic decision-making. AI also automates routine tasks like contract review and due diligence, freeing up lawyers to focus on complex legal issues. These applications make legal research more efficient, cost-effective, and accessible.
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
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一比一原版(爱大毕业证书)爱荷华大学毕业证如何办理
原版一模一样【微信：741003700 】【(爱大毕业证书)爱荷华大学毕业证成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
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如果您处于以下几种情况：
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◇面对父母的压力，希望尽快拿到；
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◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
办理(爱大毕业证书)爱荷华大学毕业证【微信：741003700 】外观非常简单，由纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理(爱大毕业证书)爱荷华大学毕业证【微信：741003700 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
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校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理(爱大毕业证书)爱荷华大学毕业证【微信：741003700 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理(爱大毕业证书)爱荷华大学毕业证【微信：741003700 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。
AI + Data Community Tour - Build the Next Generation of Apps with the Einstei...
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Build the Next Generation of Apps with the Einstein 1 Platform.
Rejoignez Philippe Ozil pour une session de workshops qui vous guidera à travers les détails de la plateforme Einstein 1, l'importance des données pour la création d'applications d'intelligence artificielle et les différents outils et technologies que Salesforce propose pour vous apporter tous les bénéfices de l'IA.2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
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Applications of artificial Intelligence in Mechanical Engineering.pdf
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
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Everything about Microservice.pptx
- 2. CONTENTS • Microservice VS Monolithic • Challenged with Monolithic Architecture • What is a microservice • Core Components of Microservice • Rest API • Components • Naming Server • Spring Cloud Config Server • Circuit Breaker • API Gateway • Routing and Messaging • Distributed Tracing • Docker • Kubernetes • Demo • Q and A session
- 4. MONOLITH
- 6. SOA
- 7. WHAT IS A MICROSERVICE
- 10. REST API
- 12. • We use Config server to manage external properties with config server for applications across all environments
- 13. ARCHITECTURE
- 14. • Also known as Service Discovery • Two discovery patterns: • Client-side discovery and Server-side discovery
- 15. ARCHITECTURE
- 16. • Acts as a fault – tolerance robust system • The circuit breakers have three states: Open Closed Half-open State. • Circuit Breaker
- 17. ARCHITECTURE
- 18. • Unified interface to a client • Performs dynamic routing of microservice applications
- 19. ARCHITECTURE
- 20. • Inter Process Communication Library is used • Communication using HTTP is supported Routing and Messaging
- 21. ARCHITECTURE
- 22. • Helps gather timing data • Provides a mechanism for sending, receiving and visualising traces Distributed Tracing
- 23. • Encapsulates the microservice into a Docker Container • Containers include all resources the software would need DOCKER
- 24. • Open-source container orchestration platform for managing, automating, and scaling containerized applications KUBERNETES
- 25. https://medium.com/@shrutiebony/all-about-microservices-in-350-words- ee2f27287a6?source=friends_link&sk=50883306a90d6301c9ff8e8a57d19d48 Link - My Blog ( All about microservices in 350 words)