In this talk we are going to explore some patterns of evolution of legacy systems towards microservices, and how this transition can be oriented towards event-oriented architectures. We would like to talk about the trade-off between having a centralized database versus multiple microservices with their own database. In this scenario, how can we guarantee transaction consistency and when to use choreography versus orchestration. In addition, we are going to bring practical examples of when to use synchronous or asynchronous communication and when it makes sense to use something like Service Mesh or Event Sourcing.
The document provides an overview of Red Hat OpenShift Container Platform, including:
- OpenShift provides a fully automated Kubernetes container platform for any infrastructure.
- It offers integrated services like monitoring, logging, routing, and a container registry out of the box.
- The architecture runs everything in pods on worker nodes, with masters managing the control plane using Kubernetes APIs and OpenShift services.
- Key concepts include pods, services, routes, projects, configs and secrets that enable application deployment and management.
Kubernetes design principles, patterns and ecosystemSreenivas Makam
Kubernetes began as Google's internal container orchestration system called Borg and was open sourced as Kubernetes in 2014. It uses a declarative model where users describe their application components and infrastructure as code to manage the desired state. Key principles include being extensible through custom resources and controllers, meeting users where they are through integration with applications, and decoupling applications from infrastructure. Common extension points allow customizing authorization, scheduling, resources, and controllers. Operators help manage custom applications and Prometheus is a widely used monitoring operator. Best practices for day 2 operations focus on cluster design, application patterns, and security. A rich ecosystem of tools has grown around Kubernetes.
This presentation by Serhii Abanichev (System Architect, Consultant, GlobalLogic) was delivered at GlobalLogic Kharkiv DevOps TechTalk #1 on October 8, 2019.
In this talk were covered:
- Full coverage of DevOps with Azure DevOps Services:
- Create, test and deploy in any programming language, to any cloud or local environment.
- Run concurrently on Linux, macOS, and Windows, deploying containers for individual hosts or Kubernetes.
- Azure DevOps Services: a Microsoft solution that replaces dozens of tools ensuring smooth delivery to end users.
Event materials: https://www.globallogic.com/ua/events/kharkiv-devops-techtalk-1/
Cloud Migration Cookbook: A Guide To Moving Your Apps To The CloudNew Relic
The process of building new apps or migrating existing apps to a cloud-based platform is complex. There are hundreds of paths you can take and only a few will make sense for you and your business. Get a step-by-step guide on how to plan for a successful app migration.
Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery called Pods. ReplicaSets ensure that a specified number of pod replicas are running at any given time. Key components include Pods, Services for enabling network access to applications, and Deployments to update Pods and manage releases.
GDG Cloud Southlake #8 Steve Cravens: Infrastructure as-Code (IaC) in 2022: ...James Anderson
Infrastructure as Code (IaC) is a concept that has been around for a while now and much research has been done to not only prove out the value but also how to enhance IaC implementations. We have a full guest list including Steve Cravens, who can speak to the school of hard knocks of why IaC is important. Stenio Ferreira, who prior to Google worked at Hashicorp and has vast experience on how to successfully implement IaC with Terraform. Lastly, Josh Addington, who is an Sr. Solutions Engineer at Hashicorp and will be speaking to the Day 2 operations as well as other offerings that can enhance IaC implementations.
Here is the high level overview:
• IaC overview
• Terraform Tactical
• IaC day 2 and Governance
Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It was originally developed by Google based on years of experience running production workloads at scale. Kubernetes groups containers into logical units called pods and handles tasks like scheduling, health checking, scaling and rollbacks. The main components include a master node that manages the cluster and worker nodes that run application containers scheduled by the master.
Advanced Deployment Strategies with Kubernetes and IstioCloudOps2005
Jonathan Gold from Container Solutions gave a workshop on advanced deployment strategies with Kubernetes and Istio at the spring 2019 Kubernetes and Cloud Native meetup in Ottawa.
The document provides an overview of Red Hat OpenShift Container Platform, including:
- OpenShift provides a fully automated Kubernetes container platform for any infrastructure.
- It offers integrated services like monitoring, logging, routing, and a container registry out of the box.
- The architecture runs everything in pods on worker nodes, with masters managing the control plane using Kubernetes APIs and OpenShift services.
- Key concepts include pods, services, routes, projects, configs and secrets that enable application deployment and management.
Kubernetes design principles, patterns and ecosystemSreenivas Makam
Kubernetes began as Google's internal container orchestration system called Borg and was open sourced as Kubernetes in 2014. It uses a declarative model where users describe their application components and infrastructure as code to manage the desired state. Key principles include being extensible through custom resources and controllers, meeting users where they are through integration with applications, and decoupling applications from infrastructure. Common extension points allow customizing authorization, scheduling, resources, and controllers. Operators help manage custom applications and Prometheus is a widely used monitoring operator. Best practices for day 2 operations focus on cluster design, application patterns, and security. A rich ecosystem of tools has grown around Kubernetes.
This presentation by Serhii Abanichev (System Architect, Consultant, GlobalLogic) was delivered at GlobalLogic Kharkiv DevOps TechTalk #1 on October 8, 2019.
In this talk were covered:
- Full coverage of DevOps with Azure DevOps Services:
- Create, test and deploy in any programming language, to any cloud or local environment.
- Run concurrently on Linux, macOS, and Windows, deploying containers for individual hosts or Kubernetes.
- Azure DevOps Services: a Microsoft solution that replaces dozens of tools ensuring smooth delivery to end users.
Event materials: https://www.globallogic.com/ua/events/kharkiv-devops-techtalk-1/
Cloud Migration Cookbook: A Guide To Moving Your Apps To The CloudNew Relic
The process of building new apps or migrating existing apps to a cloud-based platform is complex. There are hundreds of paths you can take and only a few will make sense for you and your business. Get a step-by-step guide on how to plan for a successful app migration.
Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery called Pods. ReplicaSets ensure that a specified number of pod replicas are running at any given time. Key components include Pods, Services for enabling network access to applications, and Deployments to update Pods and manage releases.
GDG Cloud Southlake #8 Steve Cravens: Infrastructure as-Code (IaC) in 2022: ...James Anderson
Infrastructure as Code (IaC) is a concept that has been around for a while now and much research has been done to not only prove out the value but also how to enhance IaC implementations. We have a full guest list including Steve Cravens, who can speak to the school of hard knocks of why IaC is important. Stenio Ferreira, who prior to Google worked at Hashicorp and has vast experience on how to successfully implement IaC with Terraform. Lastly, Josh Addington, who is an Sr. Solutions Engineer at Hashicorp and will be speaking to the Day 2 operations as well as other offerings that can enhance IaC implementations.
Here is the high level overview:
• IaC overview
• Terraform Tactical
• IaC day 2 and Governance
Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It was originally developed by Google based on years of experience running production workloads at scale. Kubernetes groups containers into logical units called pods and handles tasks like scheduling, health checking, scaling and rollbacks. The main components include a master node that manages the cluster and worker nodes that run application containers scheduled by the master.
Advanced Deployment Strategies with Kubernetes and IstioCloudOps2005
Jonathan Gold from Container Solutions gave a workshop on advanced deployment strategies with Kubernetes and Istio at the spring 2019 Kubernetes and Cloud Native meetup in Ottawa.
The document introduces Docker, a container platform. It discusses how Docker addresses issues with deploying different PHP projects that have varying version requirements by allowing each project to run isolated in its own container with specified dependencies. It then covers key Docker concepts like images, containers, linking, exposing ports, volumes, and Dockerfiles. The document highlights advantages of Docker like enabling applications to run anywhere without compatibility issues and making deployment more efficient.
This document provides an overview of Kubernetes, including its architecture, components, concepts, and configuration. It describes that Kubernetes is an open-source container orchestration system designed by Google to manage containerized applications across multiple hosts. The key components include the master nodes which run control plane components like the API server, scheduler, and controller manager, and worker nodes which run the kubelet and containers. It also explains concepts like pods, services, deployments, networking, storage, and role-based access control (RBAC).
This document discusses Redis, MongoDB, and Amazon DynamoDB. It begins with an overview of NoSQL databases and the differences between SQL and NoSQL databases. It then covers Redis data types like strings, hashes, lists, sets, sorted sets, and streams. Examples use cases for Redis are also provided like leaderboards, geospatial queries, and message queues. The document also discusses MongoDB design patterns like embedding data, embracing duplication, and relationships. Finally, it provides a high-level overview of DynamoDB concepts like tables, items, attributes, and primary keys.
The document discusses Domain Driven Design (DDD), a software development approach that focuses on building an object-oriented model of the domain that software needs to represent. It emphasizes modeling the domain closely after the structure and language of the problem domain. Key aspects of DDD discussed include ubiquitous language, bounded contexts, entities, value objects, aggregate roots, repositories, specifications, domain services, modules, domain events, and command query separation. DDD is best suited for projects with a significant domain complexity where closely modeling the problem domain can help manage that complexity.
This document provides an overview of OpenShift Container Platform. It describes OpenShift's architecture including containers, pods, services, routes and the master control plane. It also covers key OpenShift features like self-service administration, automation, security, logging, monitoring, networking and integration with external services.
An Architectural Deep Dive With Kubernetes And Containers Powerpoint Presenta...SlideTeam
Introducing An Architectural Deep Dive With Kubernetes And Containers PowerPoint Presentation Slides. Present the need for the containers in an organization with the help of a readily available PPT slideshow. Discuss container architecture, use cases details to make your presentation elaborative. Showcase the features, architecture, installation roadmap, and the 30-60-90 day plan in Kubernetes with the help of modern-designed PPT infographics. Familiarize your viewers with the various components of Kubernetes with the help of content-ready Kubernetes Docker PPT visuals. Make full use of high-quality icons to make your presentation attention-grabbing and meaningful. Compare and contrast Kubernetes with docker swarm based on various parameters with the help of this attention-grabbing PPT slideshow. Elaborate on Kubelet, Kubectl, and Kubeadm with the help of labeled diagrams. Showcase the networking model of Kubernetes, security measures, and the development process with this easy-to-use docker Architecture PowerPoint template. Therefore, hit the download button now to grab this amazing presentation. https://bit.ly/3vtLeFb
This document discusses modernizing applications for the cloud. It outlines different paths like rehosting, refactoring, or rearchitecting applications using containers, microservices, and serverless architectures. It also discusses the importance of DevOps practices and using Azure services to assess applications, create migration roadmaps, and continuously deliver updates. Migrating applications to Azure IaaS can reduce costs while refactoring or rearchitecting can enable new capabilities and improve scalability.
This document provides an overview of Azure Kubernetes Service (AKS). It begins with introductions to containers and Kubernetes, then describes AKS's architecture and features. AKS allows users to quickly deploy and manage Kubernetes clusters on Azure without having to manage the master nodes. It reduces the operational complexity of running Kubernetes in production. The document outlines how to interact with AKS using the Azure portal, CLI, and ARM templates. It also lists AKS features like identity and access control, scaling, storage integration, and monitoring.
Kubernetes has evolved from Borg at Google to provide an open source platform for automating deployment, scaling, and management of containerized applications. The presentation discusses how to use Jenkins, Fabric8, and other tools to achieve continuous integration and delivery (CI/CD) with Kubernetes. It provides examples of configuring Jenkins and Fabric8 to build, test, and deploy container images to a Kubernetes cluster, illustrating an end-to-end CI/CD workflow on Kubernetes.
- Archeology: before and without Kubernetes
- Deployment: kube-up, DCOS, GKE
- Core Architecture: the apiserver, the kubelet and the scheduler
- Compute Model: the pod, the service and the controller
When it comes to Large Scale data processing and Machine Learning, Apache Spark is no doubt one of the top battle-tested frameworks out there for handling batched or streaming workloads. The ease of use, built-in Machine Learning modules, and multi-language support makes it a very attractive choice for data wonks. However bootstrapping and getting off the ground could be difficult for most teams without leveraging a Spark cluster that is already pre-provisioned and provided as a managed service in the Cloud, while this is a very attractive choice to get going, in the long run, it could be a very expensive option if it’s not well managed.
As an alternative to this approach, our team has been exploring and working a lot with running Spark and all our Machine Learning workloads and pipelines as containerized Docker packages on Kubernetes. This provides an infrastructure-agnostic abstraction layer for us, and as a result, it improves our operational efficiency and reduces our overall compute cost. Most importantly, we can easily target our Spark workload deployment to run on any major Cloud or On-prem infrastructure (with Kubernetes as the common denominator) by just modifying a few configurations.
In this talk, we will walk you through the process our team follows to make it easy for us to run a production deployment of our Machine Learning workloads and pipelines on Kubernetes which seamlessly allows us to port our implementation from a local Kubernetes set up on the laptop during development to either an On-prem or Cloud Kubernetes environment
Red Hat OpenShift 4 allows for automated and customized deployments. The Full Stack Automation method fully automates installation and updates of both the OpenShift platform and Red Hat Enterprise Linux CoreOS host operating system. The Pre-existing Infrastructure method allows OpenShift to be deployed on user-managed infrastructure, where the customer provisions resources like load balancers and DNS. Both methods use the openshift-install tool to generate ignition configs and monitor the cluster deployment.
A presentation delivered to the Melbourne AWS Meetup on the May 24, 2018 . Discusses the implementation of the new AWS Containers sub-generator, which allows JHipster applications to be deployed on Amazon ECS, leveraging Fargate.
This document provides an agenda and overview for an MLOps workshop hosted by Amazon Web Services. The agenda includes introductions to Amazon AI, MLOps, Amazon SageMaker, machine learning pipelines, and a hands-on exercise to build an MLOps pipeline. It discusses key concepts like personas in MLOps, the CRISP-DM process, microservices deployment, and challenges of MLOps. It also provides overviews of Amazon SageMaker for machine learning and AWS services for continuous integration/delivery.
Kubernetes is an open-source container cluster manager that was originally developed by Google. It was created as a rewrite of Google's internal Borg system using Go. Kubernetes aims to provide a declarative deployment and management of containerized applications and services. It facilitates both automatic bin packing as well as self-healing of applications. Some key features include horizontal pod autoscaling, load balancing, rolling updates, and application lifecycle management.
Datadog is a cloud-based monitoring solution that collects metrics from applications, servers, tools and services to provide visibility. It aggregates data across an organization's full technology stack in one place. Datadog allows users to build dashboards to monitor key metrics, receive alerts for critical issues, and gain insights through log collection and analysis. It supports monitoring of containers, Kubernetes, databases, microservices and other modern applications and infrastructure components through its agents. Datadog is used by many companies to gain operational visibility through its features for infrastructure monitoring, APM, logs, and more.
Anatomy of a Continuous Integration and Delivery (CICD) PipelineRobert McDermott
This presentation covers the anatomy of a production CICD pipeline that is used to develop and deploy the cancer research application Oncoscape (https://oncoscape.sttrcancer.org)
Introduction to red hat agile integration (Red Hat Workshop)Judy Breedlove
This presentation provides and overview of Red Hat's approached to Agile integration. It was presented at the "Agile integration with Containers & APIs" workshop series. Fall 2018
An event-driven architecture consists of event producers that generate event streams and event consumers that listen for events. It allows for loose coupling between components and asynchronous event handling. Key aspects include publish/subscribe messaging patterns, event processing by middleware, and real-time or near real-time information flow. Benefits include scalability, loose coupling, fault tolerance, and the ability to add new consumers easily. Challenges include guaranteed delivery, processing events in order or exactly once across multiple consumer instances. Common tools used include Apache Kafka, Apache ActiveMQ, Redis, and Apache Pulsar.
State of DevOps - Build the Thing RightSergiu Bodiu
So you’re running microservices in containers? Congratulations! This is an important step towards meeting those business needs around delivering applications to the hands of your customers as soon as possible. When DevOps first made its way into many organizations, It was believed to be a Dev & Ops initiative. I will explain how the traditional expressions of CALMS (Culture, Automation, Lean, Measurement, and Sharing) are still relevant.
The document introduces Docker, a container platform. It discusses how Docker addresses issues with deploying different PHP projects that have varying version requirements by allowing each project to run isolated in its own container with specified dependencies. It then covers key Docker concepts like images, containers, linking, exposing ports, volumes, and Dockerfiles. The document highlights advantages of Docker like enabling applications to run anywhere without compatibility issues and making deployment more efficient.
This document provides an overview of Kubernetes, including its architecture, components, concepts, and configuration. It describes that Kubernetes is an open-source container orchestration system designed by Google to manage containerized applications across multiple hosts. The key components include the master nodes which run control plane components like the API server, scheduler, and controller manager, and worker nodes which run the kubelet and containers. It also explains concepts like pods, services, deployments, networking, storage, and role-based access control (RBAC).
This document discusses Redis, MongoDB, and Amazon DynamoDB. It begins with an overview of NoSQL databases and the differences between SQL and NoSQL databases. It then covers Redis data types like strings, hashes, lists, sets, sorted sets, and streams. Examples use cases for Redis are also provided like leaderboards, geospatial queries, and message queues. The document also discusses MongoDB design patterns like embedding data, embracing duplication, and relationships. Finally, it provides a high-level overview of DynamoDB concepts like tables, items, attributes, and primary keys.
The document discusses Domain Driven Design (DDD), a software development approach that focuses on building an object-oriented model of the domain that software needs to represent. It emphasizes modeling the domain closely after the structure and language of the problem domain. Key aspects of DDD discussed include ubiquitous language, bounded contexts, entities, value objects, aggregate roots, repositories, specifications, domain services, modules, domain events, and command query separation. DDD is best suited for projects with a significant domain complexity where closely modeling the problem domain can help manage that complexity.
This document provides an overview of OpenShift Container Platform. It describes OpenShift's architecture including containers, pods, services, routes and the master control plane. It also covers key OpenShift features like self-service administration, automation, security, logging, monitoring, networking and integration with external services.
An Architectural Deep Dive With Kubernetes And Containers Powerpoint Presenta...SlideTeam
Introducing An Architectural Deep Dive With Kubernetes And Containers PowerPoint Presentation Slides. Present the need for the containers in an organization with the help of a readily available PPT slideshow. Discuss container architecture, use cases details to make your presentation elaborative. Showcase the features, architecture, installation roadmap, and the 30-60-90 day plan in Kubernetes with the help of modern-designed PPT infographics. Familiarize your viewers with the various components of Kubernetes with the help of content-ready Kubernetes Docker PPT visuals. Make full use of high-quality icons to make your presentation attention-grabbing and meaningful. Compare and contrast Kubernetes with docker swarm based on various parameters with the help of this attention-grabbing PPT slideshow. Elaborate on Kubelet, Kubectl, and Kubeadm with the help of labeled diagrams. Showcase the networking model of Kubernetes, security measures, and the development process with this easy-to-use docker Architecture PowerPoint template. Therefore, hit the download button now to grab this amazing presentation. https://bit.ly/3vtLeFb
This document discusses modernizing applications for the cloud. It outlines different paths like rehosting, refactoring, or rearchitecting applications using containers, microservices, and serverless architectures. It also discusses the importance of DevOps practices and using Azure services to assess applications, create migration roadmaps, and continuously deliver updates. Migrating applications to Azure IaaS can reduce costs while refactoring or rearchitecting can enable new capabilities and improve scalability.
This document provides an overview of Azure Kubernetes Service (AKS). It begins with introductions to containers and Kubernetes, then describes AKS's architecture and features. AKS allows users to quickly deploy and manage Kubernetes clusters on Azure without having to manage the master nodes. It reduces the operational complexity of running Kubernetes in production. The document outlines how to interact with AKS using the Azure portal, CLI, and ARM templates. It also lists AKS features like identity and access control, scaling, storage integration, and monitoring.
Kubernetes has evolved from Borg at Google to provide an open source platform for automating deployment, scaling, and management of containerized applications. The presentation discusses how to use Jenkins, Fabric8, and other tools to achieve continuous integration and delivery (CI/CD) with Kubernetes. It provides examples of configuring Jenkins and Fabric8 to build, test, and deploy container images to a Kubernetes cluster, illustrating an end-to-end CI/CD workflow on Kubernetes.
- Archeology: before and without Kubernetes
- Deployment: kube-up, DCOS, GKE
- Core Architecture: the apiserver, the kubelet and the scheduler
- Compute Model: the pod, the service and the controller
When it comes to Large Scale data processing and Machine Learning, Apache Spark is no doubt one of the top battle-tested frameworks out there for handling batched or streaming workloads. The ease of use, built-in Machine Learning modules, and multi-language support makes it a very attractive choice for data wonks. However bootstrapping and getting off the ground could be difficult for most teams without leveraging a Spark cluster that is already pre-provisioned and provided as a managed service in the Cloud, while this is a very attractive choice to get going, in the long run, it could be a very expensive option if it’s not well managed.
As an alternative to this approach, our team has been exploring and working a lot with running Spark and all our Machine Learning workloads and pipelines as containerized Docker packages on Kubernetes. This provides an infrastructure-agnostic abstraction layer for us, and as a result, it improves our operational efficiency and reduces our overall compute cost. Most importantly, we can easily target our Spark workload deployment to run on any major Cloud or On-prem infrastructure (with Kubernetes as the common denominator) by just modifying a few configurations.
In this talk, we will walk you through the process our team follows to make it easy for us to run a production deployment of our Machine Learning workloads and pipelines on Kubernetes which seamlessly allows us to port our implementation from a local Kubernetes set up on the laptop during development to either an On-prem or Cloud Kubernetes environment
Red Hat OpenShift 4 allows for automated and customized deployments. The Full Stack Automation method fully automates installation and updates of both the OpenShift platform and Red Hat Enterprise Linux CoreOS host operating system. The Pre-existing Infrastructure method allows OpenShift to be deployed on user-managed infrastructure, where the customer provisions resources like load balancers and DNS. Both methods use the openshift-install tool to generate ignition configs and monitor the cluster deployment.
A presentation delivered to the Melbourne AWS Meetup on the May 24, 2018 . Discusses the implementation of the new AWS Containers sub-generator, which allows JHipster applications to be deployed on Amazon ECS, leveraging Fargate.
This document provides an agenda and overview for an MLOps workshop hosted by Amazon Web Services. The agenda includes introductions to Amazon AI, MLOps, Amazon SageMaker, machine learning pipelines, and a hands-on exercise to build an MLOps pipeline. It discusses key concepts like personas in MLOps, the CRISP-DM process, microservices deployment, and challenges of MLOps. It also provides overviews of Amazon SageMaker for machine learning and AWS services for continuous integration/delivery.
Kubernetes is an open-source container cluster manager that was originally developed by Google. It was created as a rewrite of Google's internal Borg system using Go. Kubernetes aims to provide a declarative deployment and management of containerized applications and services. It facilitates both automatic bin packing as well as self-healing of applications. Some key features include horizontal pod autoscaling, load balancing, rolling updates, and application lifecycle management.
Datadog is a cloud-based monitoring solution that collects metrics from applications, servers, tools and services to provide visibility. It aggregates data across an organization's full technology stack in one place. Datadog allows users to build dashboards to monitor key metrics, receive alerts for critical issues, and gain insights through log collection and analysis. It supports monitoring of containers, Kubernetes, databases, microservices and other modern applications and infrastructure components through its agents. Datadog is used by many companies to gain operational visibility through its features for infrastructure monitoring, APM, logs, and more.
Anatomy of a Continuous Integration and Delivery (CICD) PipelineRobert McDermott
This presentation covers the anatomy of a production CICD pipeline that is used to develop and deploy the cancer research application Oncoscape (https://oncoscape.sttrcancer.org)
Introduction to red hat agile integration (Red Hat Workshop)Judy Breedlove
This presentation provides and overview of Red Hat's approached to Agile integration. It was presented at the "Agile integration with Containers & APIs" workshop series. Fall 2018
An event-driven architecture consists of event producers that generate event streams and event consumers that listen for events. It allows for loose coupling between components and asynchronous event handling. Key aspects include publish/subscribe messaging patterns, event processing by middleware, and real-time or near real-time information flow. Benefits include scalability, loose coupling, fault tolerance, and the ability to add new consumers easily. Challenges include guaranteed delivery, processing events in order or exactly once across multiple consumer instances. Common tools used include Apache Kafka, Apache ActiveMQ, Redis, and Apache Pulsar.
State of DevOps - Build the Thing RightSergiu Bodiu
So you’re running microservices in containers? Congratulations! This is an important step towards meeting those business needs around delivering applications to the hands of your customers as soon as possible. When DevOps first made its way into many organizations, It was believed to be a Dev & Ops initiative. I will explain how the traditional expressions of CALMS (Culture, Automation, Lean, Measurement, and Sharing) are still relevant.
Webinar presentation March 9, 2017
IT environments are now fundamentally hybrid in nature – devices, systems, and people are spread across the globe, and at the same time virtualized. Achieving integration across this ever changing environment, and doing so at the pace of modern digital initiatives, is a significant challenge.
This presentation introduces a hybrid integration reference architecture published by the Cloud Standards Customer Council. Learn best practices from leading-edge enterprises that are starting to leverage a hybrid integration platform to take advantage of best of breed cloud-based and on-premises integration approaches.
This webinar draws from the CSCC's deliverable, Cloud Customer Architecture for Hybrid Integration. Read it here: http://www.cloud-council.org/deliverables/cloud-customer-architecture-for-hybrid-integration.htm
apidays LIVE Paris 2021 - EDI & API on One Integration Platform by Mir Mustha...apidays
apidays LIVE Paris 2021 - APIs and the Future of Software
December 7, 8 & 9, 2021
EDI & API on One Integration Platform – Intcomex Success Story
Mir Musthafa Ali Pashar, Head - Middleware Practice at Royal Cyber Inc. & Grisel Infante Costa, IT Operations Coordinator at Intcomex
How do we add some sanity to the process of constructing microservices and provide guidelines and design heuristics on restructuring microservices. In this talk we will look at life after running microservices architectures in production and learn from the mistakes committed over the past five years. We will analyze real life systems on the criteria for consolidating microservices into monoliths or moduliths based on technical and business heuristics as illustrated In [4]. The techniques - a combination of mapping microservices to core technical attributes [2] reduced by affinity mapping and business domain context distillation [3] - have emerged from working with a number of customers where the value of microservices has not been realized despite leveraging Domain Driven Design.
1. Essay on this topic : https://hackmd.io/10j-7DfqSIu1C8GQjHa1Bw?view
2. https://content.pivotal.io/blog/should-that-be-a-microservice-keep-these-six-factors-in-mind
3. https://medium.com/nick-tune-tech-strategy-blog/core-domain-patterns-941f89446af5
4. https://twitter.com/RKela/status/1227188151887843329/photo/1
Getting Started with ThousandEyes Proof of ConceptsThousandEyes
This document outlines the process for conducting a proof of concept (PoC) using ThousandEyes, which provides internet and cloud monitoring. It begins with an overview and agenda. It then discusses identifying opportunities by qualifying customer problems and priorities. Success criteria for the PoC are defined, such as improving visibility, reducing troubleshooting time, and proactive monitoring. The execution process is explained, including installing agents, creating tests, building dashboards, and continuous monitoring. A demo is provided, followed by resources and next steps. The overall goal of the PoC is to demonstrate ThousandEyes' business value for the customer in addressing their specific needs.
A proof of concept is an excellent way to showcase how a technology will provide immediate business value for your customer. To conduct a successful proof of concept using ThousandEyes, it's important to qualify the opportunity and outline what success looks like to that customer.
In this webinar, we will walk you through:
- What you need to know to run successful ThousandEyes proof of concepts focusing on the Enterprise Digital Experience use case
- A demo of how to capture interesting events within the platform during a proof of concept
A presentation to explain the microservices architecture, the pro and the cons, with a view on how to migrate from a monolith to a SOA architecture. Also, we'll show the benefits of the microservices architecture also for the frontend side with the microfrontend architecture.
This document summarizes a presentation about Docker and microservices and what they mean for enterprise DevOps strategies. It discusses what Docker and microservices are, how they will impact development, operations, and other teams. It recommends that enterprises investigate these technologies, understand how to integrate them into existing systems and processes, and quantify the potential business benefits before adopting them. The presentation also discusses how the tool vendor XebiaLabs is helping customers prepare for and adopt containers and microservices.
Getting Started With ThousandEyes Proof of Concepts: End User Digital ExperienceThousandEyes
The document provides an overview of conducting a proof of concept (PoC) with ThousandEyes. It outlines the key stages of the PoC process, including preparation, trial active period, and go-forward planning. Success criteria for evaluating digital experience are also presented, such as correlating application performance with infrastructure issues, reducing troubleshooting time, and gaining proactive monitoring capabilities. The document emphasizes focusing the PoC on defined success criteria and having experts available for support during the trial period. A demo is also included to illustrate ThousandEyes capabilities.
This document discusses microservices and their evolution from monolithic applications. It defines microservices as the smallest deployable units that can function independently. The document outlines the benefits of microservices like improved agility, scalability and fault tolerance compared to earlier architectures like SOA. It also discusses some challenges of microservices like integration testing and service discovery. The document recommends approaches like automation, DevOps practices and service meshes to overcome microservices challenges. It advises that microservices are suitable when requirements involve frequent changes, time to market pressure or building cloud platforms.
Getting Started with ThousandEyes Proof of ConceptsThousandEyes
The document provides an overview of a ThousandEyes proof of concept process. It discusses identifying opportunities, defining success criteria, executing the PoC, and developing a go-forward plan. The success criteria section outlines metrics like reducing mean time to identify and resolve issues, improving visibility, and moving from reactive to proactive monitoring. The overall goal is to demonstrate how ThousandEyes can help lower troubleshooting times and improve the digital experience for end users and applications.
Overcoming Ongoing Digital Transformational Challenges with a Microservices A...Cognizant
IT organizations must look beyond yesterday's monolithic Web applications and embrace microservices, whose loosely-coupled architectures speed development, testing and deployment.
This document discusses 5 challenges to achieving observability at scale: 1) the complexity of dynamic multi-cloud environments, 2) monitoring dynamic microservices and containers in real-time, 3) the volume, velocity, and variety of data and alerts, 4) siloed infrastructure, development, operations, applications, and business teams, and 5) knowing which efforts drive positive business impact. It argues that to overcome these challenges, teams need to shift from manual monitoring to automated and intelligent observability powered by artificial intelligence in order to continuously understand systems, anticipate issues, and optimize efforts at scale across dynamic cloud environments.
The document discusses building a cloud practice using infrastructure as a service (IaaS). It provides an overview of components of IaaS including compute, storage, networking and costs. It discusses strategies for reselling versus bringing your own license and professional services around cloud. The document also discusses choosing the right IaaS partner and highlights benefits of partnering with SoftLayer including their global footprint, server options, and differentiators compared to other providers. Finally, it discusses perspectives on building a successful cloud practice and business from an organizational and financial standpoint.
Software Principles and Project Deadlines Don't have to be Polar Opposites.pdfCraig Saunders
As Software Engineers we pride ourselves to build high-quality software using the best industry practices and principles.
But what happens when you’re asked to deliver a project with impossible timescales where a quick hacky solution is all that time allows.
This presentation talks about such a scenario where and how we managed to achieve the right solution but also met the business deadline.
In addition, it talks briefly about the key principles we followed to achieve this feat.
CWIN17 Utrecht / cg u services - frank van der walCapgemini
The document discusses building blocks for digital transformation, including cloud infrastructure, artificial intelligence, data tools, and targeted applications. It recommends an architecture that is engineered for distribution, using microservices that can be deployed independently and communicate through APIs. The challenges of a microservices architecture include maintenance due to varied skills required, latency from network hops, data sharing between services, and manageability of a network of services. Digital transformation creates both digital and enterprise IT that require different approaches to exploration and security. An integration reference architecture is proposed with systems of engagement, integration layers, and systems of record.
Do Away with Legacy Applications_ Reduce Data Breaches and More.pptxSeclore
The document discusses the need for businesses to modernize legacy applications to align with current business needs and market demands. It states that Seclore has modernized its legacy applications by converting them to docker containers with improved reliability, scalability, and security. Modernizing applications provides benefits like faster upgrades, lower maintenance costs, and a stronger security posture.
Why we should consider Open Hybrid Cloud.pdfMasahiko Umeno
I am talking about four key points, Application Architecture, Development method, Organizations and Cooperation, Operation and Maintenance, to consider in legacy modernization and what the end result should be.
We think you'll understand why you should consider Red Hat's "open hybrid cloud" approach. Please take a look.
Getting Started with ThousandEyes Proof of ConceptsThousandEyes
The document provides an overview and agenda for a ThousandEyes proof of concept. It discusses the ThousandEyes overview, identifying opportunities, defining success criteria, executing the proof of concept, and includes a demo. The agenda includes preparing for the proof of concept over two weeks, running the active trial for 4-6 weeks, and developing a go-forward plan over another two weeks. It also discusses best practices for executing the proof of concept and ensuring a focus on the defined success criteria.
Similar to Patterns of evolution from monolith to microservices (20)
Flutter is a popular open source, cross-platform framework developed by Google. In this webinar we'll explore Flutter and its architecture, delve into the Flutter Embedder and Flutter’s Dart language, discover how to leverage Flutter for embedded device development, learn about Automotive Grade Linux (AGL) and its consortium and understand the rationale behind AGL's choice of Flutter for next-gen IVI systems. Don’t miss this opportunity to discover whether Flutter is right for your project.
A Comprehensive Guide on Implementing Real-World Mobile Testing Strategies fo...kalichargn70th171
In today's fiercely competitive mobile app market, the role of the QA team is pivotal for continuous improvement and sustained success. Effective testing strategies are essential to navigate the challenges confidently and precisely. Ensuring the perfection of mobile apps before they reach end-users requires thoughtful decisions in the testing plan.
Most important New features of Oracle 23c for DBAs and Developers. You can get more idea from my youtube channel video from https://youtu.be/XvL5WtaC20A
Everything You Need to Know About X-Sign: The eSign Functionality of XfilesPr...XfilesPro
Wondering how X-Sign gained popularity in a quick time span? This eSign functionality of XfilesPro DocuPrime has many advancements to offer for Salesforce users. Explore them now!
Unlock the Secrets to Effortless Video Creation with Invideo: Your Ultimate G...The Third Creative Media
"Navigating Invideo: A Comprehensive Guide" is an essential resource for anyone looking to master Invideo, an AI-powered video creation tool. This guide provides step-by-step instructions, helpful tips, and comparisons with other AI video creators. Whether you're a beginner or an experienced video editor, you'll find valuable insights to enhance your video projects and bring your creative ideas to life.
Baha Majid WCA4Z IBM Z Customer Council Boston June 2024.pdfBaha Majid
IBM watsonx Code Assistant for Z, our latest Generative AI-assisted mainframe application modernization solution. Mainframe (IBM Z) application modernization is a topic that every mainframe client is addressing to various degrees today, driven largely from digital transformation. With generative AI comes the opportunity to reimagine the mainframe application modernization experience. Infusing generative AI will enable speed and trust, help de-risk, and lower total costs associated with heavy-lifting application modernization initiatives. This document provides an overview of the IBM watsonx Code Assistant for Z which uses the power of generative AI to make it easier for developers to selectively modernize COBOL business services while maintaining mainframe qualities of service.
E-commerce Development Services- Hornet DynamicsHornet Dynamics
For any business hoping to succeed in the digital age, having a strong online presence is crucial. We offer Ecommerce Development Services that are customized according to your business requirements and client preferences, enabling you to create a dynamic, safe, and user-friendly online store.
INTRODUCTION TO AI CLASSICAL THEORY TARGETED EXAMPLESanfaltahir1010
Image: Include an image that represents the concept of precision, such as a AI helix or a futuristic healthcare
setting.
Objective: Provide a foundational understanding of precision medicine and its departure from traditional
approaches
Role of theory: Discuss how genomics, the study of an organism's complete set of AI ,
plays a crucial role in precision medicine.
Customizing treatment plans: Highlight how genetic information is used to customize
treatment plans based on an individual's genetic makeup.
Examples: Provide real-world examples of successful application of AI such as genetic
therapies or targeted treatments.
Importance of molecular diagnostics: Explain the role of molecular diagnostics in identifying
molecular and genetic markers associated with diseases.
Biomarker testing: Showcase how biomarker testing aids in creating personalized treatment plans.
Content:
• Ethical issues: Examine ethical concerns related to precision medicine, such as privacy, consent, and
potential misuse of genetic information.
• Regulations and guidelines: Present examples of ethical guidelines and regulations in place to safeguard
patient rights.
• Visuals: Include images or icons representing ethical considerations.
Content:
• Ethical issues: Examine ethical concerns related to precision medicine, such as privacy, consent, and
potential misuse of genetic information.
• Regulations and guidelines: Present examples of ethical guidelines and regulations in place to safeguard
patient rights.
• Visuals: Include images or icons representing ethical considerations.
Content:
• Ethical issues: Examine ethical concerns related to precision medicine, such as privacy, consent, and
potential misuse of genetic information.
• Regulations and guidelines: Present examples of ethical guidelines and regulations in place to safeguard
patient rights.
• Visuals: Include images or icons representing ethical considerations.
Real-world case study: Present a detailed case study showcasing the success of precision
medicine in a specific medical scenario.
Patient's journey: Discuss the patient's journey, treatment plan, and outcomes.
Impact: Emphasize the transformative effect of precision medicine on the individual's
health.
Objective: Ground the presentation in a real-world example, highlighting the practical
application and success of precision medicine.
Data challenges: Address the challenges associated with managing large sets of patient data in precision
medicine.
Technological solutions: Discuss technological innovations and solutions for handling and analyzing vast
datasets.
Visuals: Include graphics representing data management challenges and technological solutions.
Objective: Acknowledge the data-related challenges in precision medicine and highlight innovative solutions.
Data challenges: Address the challenges associated with managing large sets of patient data in precision
medicine.
Technological solutions: Discuss technological innovations and solutions
Consistent toolbox talks are critical for maintaining workplace safety, as they provide regular opportunities to address specific hazards and reinforce safe practices.
These brief, focused sessions ensure that safety is a continual conversation rather than a one-time event, which helps keep safety protocols fresh in employees' minds. Studies have shown that shorter, more frequent training sessions are more effective for retention and behavior change compared to longer, infrequent sessions.
Engaging workers regularly, toolbox talks promote a culture of safety, empower employees to voice concerns, and ultimately reduce the likelihood of accidents and injuries on site.
The traditional method of conducting safety talks with paper documents and lengthy meetings is not only time-consuming but also less effective. Manual tracking of attendance and compliance is prone to errors and inconsistencies, leading to gaps in safety communication and potential non-compliance with OSHA regulations. Switching to a digital solution like Safelyio offers significant advantages.
Safelyio automates the delivery and documentation of safety talks, ensuring consistency and accessibility. The microlearning approach breaks down complex safety protocols into manageable, bite-sized pieces, making it easier for employees to absorb and retain information.
This method minimizes disruptions to work schedules, eliminates the hassle of paperwork, and ensures that all safety communications are tracked and recorded accurately. Ultimately, using a digital platform like Safelyio enhances engagement, compliance, and overall safety performance on site. https://safelyio.com/
Project Management: The Role of Project Dashboards.pdfKarya Keeper
Project management is a crucial aspect of any organization, ensuring that projects are completed efficiently and effectively. One of the key tools used in project management is the project dashboard, which provides a comprehensive view of project progress and performance. In this article, we will explore the role of project dashboards in project management, highlighting their key features and benefits.
Unveiling the Advantages of Agile Software Development.pdfbrainerhub1
Learn about Agile Software Development's advantages. Simplify your workflow to spur quicker innovation. Jump right in! We have also discussed the advantages.
Why Apache Kafka Clusters Are Like Galaxies (And Other Cosmic Kafka Quandarie...Paul Brebner
Closing talk for the Performance Engineering track at Community Over Code EU (Bratislava, Slovakia, June 5 2024) https://eu.communityovercode.org/sessions/2024/why-apache-kafka-clusters-are-like-galaxies-and-other-cosmic-kafka-quandaries-explored/ Instaclustr (now part of NetApp) manages 100s of Apache Kafka clusters of many different sizes, for a variety of use cases and customers. For the last 7 years I’ve been focused outwardly on exploring Kafka application development challenges, but recently I decided to look inward and see what I could discover about the performance, scalability and resource characteristics of the Kafka clusters themselves. Using a suite of Performance Engineering techniques, I will reveal some surprising discoveries about cosmic Kafka mysteries in our data centres, related to: cluster sizes and distribution (using Zipf’s Law), horizontal vs. vertical scalability, and predicting Kafka performance using metrics, modelling and regression techniques. These insights are relevant to Kafka developers and operators.
The Key to Digital Success_ A Comprehensive Guide to Continuous Testing Integ...kalichargn70th171
In today's business landscape, digital integration is ubiquitous, demanding swift innovation as a necessity rather than a luxury. In a fiercely competitive market with heightened customer expectations, the timely launch of flawless digital products is crucial for both acquisition and retention—any delay risks ceding market share to competitors.
WWDC 2024 Keynote Review: For CocoaCoders AustinPatrick Weigel
Overview of WWDC 2024 Keynote Address.
Covers: Apple Intelligence, iOS18, macOS Sequoia, iPadOS, watchOS, visionOS, and Apple TV+.
Understandable dialogue on Apple TV+
On-device app controlling AI.
Access to ChatGPT with a guest appearance by Chief Data Thief Sam Altman!
App Locking! iPhone Mirroring! And a Calculator!!
Preparing Non - Technical Founders for Engaging a Tech AgencyISH Technologies
Preparing non-technical founders before engaging a tech agency is crucial for the success of their projects. It starts with clearly defining their vision and goals, conducting thorough market research, and gaining a basic understanding of relevant technologies. Setting realistic expectations and preparing a detailed project brief are essential steps. Founders should select a tech agency with a proven track record and establish clear communication channels. Additionally, addressing legal and contractual considerations and planning for post-launch support are vital to ensure a smooth and successful collaboration. This preparation empowers non-technical founders to effectively communicate their needs and work seamlessly with their chosen tech agency.Visit our site to get more details about this. Contact us today www.ishtechnologies.com.au
Mobile App Development Company In Noida | Drona InfotechDrona Infotech
Drona Infotech is a premier mobile app development company in Noida, providing cutting-edge solutions for businesses.
Visit Us For : https://www.dronainfotech.com/mobile-application-development/