The document discusses two topics: microservices and cloud monitoring. Microservices involve breaking applications into small, independent components. Cloud monitoring allows users to monitor cloud resources. The author proposes an "on demand monitoring" approach using a microservices-based infrastructure that provides scalable and configurable monitoring as a service. It automatically deploys a monitoring system that can be tailored to the user's needs and scales from simple to complex setups.
Building Kubernetes images at scale with Tanzu Build ServiceVMware Tanzu
Building a secure software supply chain
Leveraging Tanzu Build Service
How Build Service fits in the Tanzu portfolio
Modernize your applications
Live demos
Look ma: no Dockerfile!
This document discusses automating Dynamics 365 CE and PowerApps build and release processes using Azure DevOps and PowerApps build tools. It covers application lifecycle management (ALM), source control, solutions and layering in Dynamics 365, and using Azure DevOps for continuous integration and deployment with PowerApps build tools to import, export, publish and automate other deployment tasks. A demo is shown of creating a build/release pipeline with PowerApps build tools.
Cloud Native Engineering with SRE and GitOpsWeaveworks
1) The presentation introduced Brice Fernandes and Sebastian Bernheim from Weaveworks and discussed their roles as customer reliability engineers.
2) It provided an overview of Weaveworks' approach to enabling GitOps across the Kubernetes landscape through open source projects and consulting services.
3) Key SRE practices like embracing risk, establishing service level objectives, automating processes, and implementing deliberate release engineering were shown to be well-aligned with a GitOps model for Kubernetes management.
VMware Tanzu Community Edition: a First Look with Amanda and JoshVMware Tanzu
VMware Tanzu Community Edition is a freely available Kubernetes platform for learners and users. It provides the same open source software as Tanzu commercial editions, with no cost or usage limitations. Users can install and configure it in minutes on their local workstation or cloud, to learn independently or evaluate Tanzu before making strategic platform decisions. The document encourages readers to download Tanzu Community Edition from tanzucommunityedition.io to gain hands-on experience with a complete and customizable Kubernetes platform.
This presentation provides an overview and status update of the Steeltoe software framework. It discusses Steeltoe's components for observability, security, scalability, and ease of use. Recent updates include improvements to abstractions, configuration, connectors, discovery, management, and messaging. Future plans include further Kubernetes support, tooling enhancements, and making streams and data flow integration production-ready. The presentation encourages attendees to stay updated on Steeltoe's documentation, GitHub, Slack channel, and social media accounts.
This document provides an overview of the Nexus framework for scaling Scrum to multiple teams. Nexus introduces an integration team that is responsible for integrating the work of individual Scrum teams and ensuring the definition of done is met at each sprint's integrated increment. It also includes layered ceremonies that coordinate work across teams such as Nexus sprint planning and reviews. The key principles of Scrum like transparency, inspection, and adaptation still apply at scale with Nexus through its practices like a shared product backlog and integrated work demonstrations. Nexus allows Scrum to scale fractally through coordination of multiple Scrum teams.
Devops architecture involves three main categories of infrastructure: IT infrastructure (version control, issue tracking, etc.), build infrastructure (build servers with access to source code), and test infrastructure (deployment, acceptance, and functional testing). Continuous integration involves automating the integration of code changes, while continuous delivery ensures code is always releasable but actual deployment is manual. Continuous deployment automates deployment so that any code passing tests is immediately deployed to production. The document discusses infrastructure hosting options, automation approaches, common CI/CD workflows, and provides examples of low and medium-cost devops tooling setups using open source and proprietary software.
Building Kubernetes images at scale with Tanzu Build ServiceVMware Tanzu
Building a secure software supply chain
Leveraging Tanzu Build Service
How Build Service fits in the Tanzu portfolio
Modernize your applications
Live demos
Look ma: no Dockerfile!
This document discusses automating Dynamics 365 CE and PowerApps build and release processes using Azure DevOps and PowerApps build tools. It covers application lifecycle management (ALM), source control, solutions and layering in Dynamics 365, and using Azure DevOps for continuous integration and deployment with PowerApps build tools to import, export, publish and automate other deployment tasks. A demo is shown of creating a build/release pipeline with PowerApps build tools.
Cloud Native Engineering with SRE and GitOpsWeaveworks
1) The presentation introduced Brice Fernandes and Sebastian Bernheim from Weaveworks and discussed their roles as customer reliability engineers.
2) It provided an overview of Weaveworks' approach to enabling GitOps across the Kubernetes landscape through open source projects and consulting services.
3) Key SRE practices like embracing risk, establishing service level objectives, automating processes, and implementing deliberate release engineering were shown to be well-aligned with a GitOps model for Kubernetes management.
VMware Tanzu Community Edition: a First Look with Amanda and JoshVMware Tanzu
VMware Tanzu Community Edition is a freely available Kubernetes platform for learners and users. It provides the same open source software as Tanzu commercial editions, with no cost or usage limitations. Users can install and configure it in minutes on their local workstation or cloud, to learn independently or evaluate Tanzu before making strategic platform decisions. The document encourages readers to download Tanzu Community Edition from tanzucommunityedition.io to gain hands-on experience with a complete and customizable Kubernetes platform.
This presentation provides an overview and status update of the Steeltoe software framework. It discusses Steeltoe's components for observability, security, scalability, and ease of use. Recent updates include improvements to abstractions, configuration, connectors, discovery, management, and messaging. Future plans include further Kubernetes support, tooling enhancements, and making streams and data flow integration production-ready. The presentation encourages attendees to stay updated on Steeltoe's documentation, GitHub, Slack channel, and social media accounts.
This document provides an overview of the Nexus framework for scaling Scrum to multiple teams. Nexus introduces an integration team that is responsible for integrating the work of individual Scrum teams and ensuring the definition of done is met at each sprint's integrated increment. It also includes layered ceremonies that coordinate work across teams such as Nexus sprint planning and reviews. The key principles of Scrum like transparency, inspection, and adaptation still apply at scale with Nexus through its practices like a shared product backlog and integrated work demonstrations. Nexus allows Scrum to scale fractally through coordination of multiple Scrum teams.
Devops architecture involves three main categories of infrastructure: IT infrastructure (version control, issue tracking, etc.), build infrastructure (build servers with access to source code), and test infrastructure (deployment, acceptance, and functional testing). Continuous integration involves automating the integration of code changes, while continuous delivery ensures code is always releasable but actual deployment is manual. Continuous deployment automates deployment so that any code passing tests is immediately deployed to production. The document discusses infrastructure hosting options, automation approaches, common CI/CD workflows, and provides examples of low and medium-cost devops tooling setups using open source and proprietary software.
A tutorial about the API for the description of a monitoring infrastructure currently discussed inside the OCCI working group.
The slides start by giving the basic concepts, proceed with a description of the entities that implement the monitoring infrastructure, and conclude with a step by step definition of a non-trivial monitoring infrastructure.
Monitoring a virtual network infrastructure - An IaaS perspectiveAugusto Ciuffoletti
The document discusses the challenges of providing network resources as part of an Infrastructure as a Service (IaaS) cloud computing model. While IaaS has traditionally focused on storage and computing resources, the networking capabilities now exist to provision virtual network infrastructure as well. However, IaaS providers still typically only offer flat local area networks rather than composite network topologies that some users require. The key technology that enables virtual private networks is virtual bridging using VLAN tagging, which allows flexible virtual network configurations. For network monitoring in IaaS, a proxy that interacts with users is proposed to dynamically configure monitoring while maintaining provider control over network devices.
The document discusses the Open Cloud Computing Interface (OCCI), which aims to provide an open standard interface for cloud computing. It describes OCCI's goals of allowing interoperability between different cloud providers and preventing vendor lock-in. The core OCCI model defines basic resource and link entity types and supports extensions for additional types and functionality. OCCI uses a RESTful API and represents entities with URIs to allow their creation, retrieval, updating and deletion. Implementations of OCCI have been made for various programming languages and cloud platforms.
Automated Provisioning, Management & Cost Control for Kubernetes ClustersWeaveworks
In today’s economic climate, IT departments are feeling the pressure to reduce costs which can have a significant effect on development teams, and more specifically, Kubernetes strategies. For many organizations, there is a good chance that many Kubernetes resources are overprovisioned, and it’s often difficult to visualize which processes are responsible for this unnecessary spend.
Weaveworks has joined forces with KubeCost to show you how to “do more with less” by easily integrating a Kubernetes FinOps solution into your existing workflows and seamlessly automating the provisioning and management of FinOps enabled Kubernetes clusters from a single UI / dashboard.
Join this webinar to discover best practices for monitoring and reducing Kubernetes spend, while balancing cost, performance, and reliability.
What you’ll learn:
- Best practices for implementing a FinOps strategy in your organization.
- Cluster management and templating capabilities using Weave GitOps for automating FinOps.
- How to use predefined, automated policies for reliable cost control across your Kubernetes environment.
Comparative Analysis of IT Monitoring Toolsapprize360
This document provides a comparative analysis of IT monitoring platforms from CA Technologies, SolarWinds, IBM, and Nagios. It finds that CA Nimsoft Monitor version 7.5 had the fastest time to begin monitoring devices, being able to monitor 100 devices within 61 minutes of downloading and installing the software. In comparison, it took over 3 hours for Nagios XI and over 2 hours for some SolarWinds products to complete the same tasks. The analysis concludes that CA Nimsoft Monitor offers a single, unified monitoring solution while competitors require multiple individual products, and that CA Nimsoft Monitor's installation and configuration process is much easier and faster than the alternatives.
Migrating large, complex, multi-tiered applications to Kubernetes can be a challenging task. In the talk, we share the experience of migrating our service-based, unified monitoring solution, NetEye 4 (https://www.wuerth-phoenix.com/en/solutions/it-system-management/unified-monitoring/), to a more modern micro-service oriented solution like Kubernetes, with the ultimate goal of providing a monitoring solution as a Service for large and multi-tenant infrastructures
Currently, NetEye 4 is built on top of the Red Hat cluster technology, which provides a set of features to implement resilient applications. With this technology, each tier of NetEye 4 is indeed high-available and distributed across multiple physical servers.
However, the burden to obtain a high-available, highly performing and scalable solution is high: it requires custom implementations to leverage the full set of functionalities offered by the infrastructure, which is not always available out-of-the-box.
Can Kubernetes be the possible solution to these problems? Which complexity is hidden under the hood of Kubernetes? Is Kubernetes complexity justified to fulfill our vision of offering unified monitoring as a Service and optimizing scalability in large environments? To answer these questions, we decide to use a product-testing method to explore potential solutions.
Four considerations when monitoring microservicesJason Bloomberg
The adoption of microservices add a new layer of complexity to an already complex application environment. When application issues arise, it becomes difficult to pinpoint the source and, too often, you find yourself in lengthy war rooms or assigning experts to triage every issue. As a result, brand loyalty, customer satisfaction and innovation are negatively impacted. The old approach to monitoring application performance just isn’t working. A new approach is needed. In this session we will discuss four areas that you should consider which will change the way you think about monitoring microservices
Continuous Delivery of a Cloud Deployment at a Large Telecommunications ProviderM Kevin McHugh
This document discusses how a large telecommunications provider implemented continuous delivery for a cloud deployment. It defines continuous delivery as automating the process of software delivery through techniques like continuous integration, automated testing, and continuous deployment. It then describes the specific components and tools used in the telecom provider's implementation, including adopting agile methodology, integrating rational team concert, automated testing with a REST API, and using SmartCloud Orchestrator for automated builds and deployment.
Automating it management with Puppet + ServiceNowPuppet
As the leading IT Service Management and IT Operations Management platform in the marketplace, ServiceNow is used by many organizations to address everything from self service IT requests to Change, Incident and Problem Management. The strength of the platform is in the workflows and processes that are built around the shared data model, represented in the CMDB. This provides the ‘single source of truth’ for the organization.
Puppet Enterprise is a leading automation platform focused on the IT Configuration Management and Compliance space. Puppet Enterprise has a unique perspective on the state of systems being managed, constantly being updated and kept accurate as part of the regular Puppet operation. Puppet Enterprise is the automation engine ensuring that the environment stays consistent and in compliance.
In this webinar, we will explore how to maximize the value of both solutions, with Puppet Enterprise automating the actions required to drive a change, and ServiceNow governing the process around that change, from definition to approval. We will introduce and demonstrate several published integration points between the two solutions, in the areas of Self-Service Infrastructure, Enriched Change Management and Automated Incident Registration.
A Comparative Study of Different types of Models in Software Development Life...IRJET Journal
This document compares and contrasts three common software development models: the waterfall model, iterative enhancement model, and prototyping model. It discusses the key stages and processes in each model, including requirements analysis, design, implementation, testing, and maintenance. The waterfall model is described as the classic sequential model, while the iterative and prototyping models allow for more flexibility and user feedback. The document analyzes the advantages and disadvantages of each approach and concludes each model tries to improve on the limitations of previous ones. The iterative model is seen as overcoming issues of the waterfall by allowing feedback, while the prototyping model is useful for complex or unestablished requirements.
The document summarizes a MuleSoft meetup event that took place in Princeton, NJ on September 23rd, 2023. The meetup agenda included an introduction by the organizers, a presentation and demo on troubleshooting with Anypoint Monitoring by the speaker Beauty Mishra, and a Q&A session. Key points covered in the presentation included an overview of Anypoint Monitoring features for apps running on CloudHub or on-premises servers, how to enable automatic monitoring, configure alerts, and use built-in and custom dashboards. The meetup concluded with a request for feedback and suggestions for future meetup topics.
Práticas, Técnicas e Ferramentas para Continuous Delivery com ALMMarcelo Sousa Ancelmo
Palestra feita na trilha de DevOps no TDC2014 em São Paulo.
Como estruturar uma estratégia de Continuous Delivery suportada por ALM, promovendo visibilidade, colaboração e controle
Mis on andmekeskuse uus standard - hüperkonvergents?
Kui kõiki kesksüsteeme ei ole võimalik pilve viia ja serverikeskuse kasv suurendab halduse keerukust, on väljapääs serverikeskuse konvergents. Simplivity Omnicube on konvergentsi uus tase. Millised on serverikeskuse kasvuga seotud põhiprobleemid ja kuidas neid lahendada? Kuidas korraldada Disaster Recovery ja Backup?
The document outlines an agenda for a conference on innovation, digitization and sustainability with AI. The agenda includes sessions on exploring ChatGPT and future language technology, AWS expanding in the Norwegian market and how to get started, digital twins with opportunities and risks, and using AI for football, environment and sustainability. There will be breaks between sessions and a social event from 19:00.
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 presentation is to reflect on the amazing advancement of the open source community in the field of Cloud Computing and how does it now allow us to build reliable software components quickly within truly agile infrastructure.
SlideTeam presents Kubernetes Docker Container Implementation Ppt PowerPoint Presentation Slide Templates. This PPT slideshow is an ideal virtual expression of the fundamentals of Kubernetes. The smart data-visualizations make this PowerPoint presentation easy-to-understand and perfect to introduce your audience to the container orchestration system. Use our PPT theme to communicate the definition and need for containers or virtual private servers. Communicate the container, and microservices architecture using cutting-edge graphics. Explain the need for and benefits of Kubernetes for an organization. Elucidate the features, architecture, use cases, installation roadmap, and the 30-60-90 day plan in Kubernetes. Use the neat tabular format to compare Kubernetes with docker swarm based on various parameters. Familiarize your viewers with the various components of Kubernetes. Elaborate on what is Kubelet, Kubectl, and Kubeadm with the help of labeled diagrams. This presentation acquaints your audience with the significance of Kubernetes in management, scaling, automating, and deploying computer applications. Hit the download icon and start personalization. https://bit.ly/2L0Ojdu
OneShare is a self-service platform for development and testing in the cloud. It allows teams to quickly provision virtual environments in Microsoft Azure for building, testing, and managing software projects. Using OneShare, teams can reduce costs by paying only for resources used and accelerate development cycles by automating environment setup. The platform provides tools for continuous integration and delivery, cost monitoring, and team collaboration to improve agility for software teams.
Comment déployer et gérer dans le cloud Azure les environnements de développe...Microsoft Technet France
The document discusses OneShare, a self-service platform for development and testing in the cloud. It aims to provide agile teams with on-demand access to environments and tools through a portal. Teams can provision infrastructure from templates, access ALM tools, and gain insights into resource usage and costs. The platform utilizes Microsoft Azure and seeks to accelerate software delivery through flexibility, cost savings, and productivity gains compared to traditional development approaches.
A tutorial about the API for the description of a monitoring infrastructure currently discussed inside the OCCI working group.
The slides start by giving the basic concepts, proceed with a description of the entities that implement the monitoring infrastructure, and conclude with a step by step definition of a non-trivial monitoring infrastructure.
Monitoring a virtual network infrastructure - An IaaS perspectiveAugusto Ciuffoletti
The document discusses the challenges of providing network resources as part of an Infrastructure as a Service (IaaS) cloud computing model. While IaaS has traditionally focused on storage and computing resources, the networking capabilities now exist to provision virtual network infrastructure as well. However, IaaS providers still typically only offer flat local area networks rather than composite network topologies that some users require. The key technology that enables virtual private networks is virtual bridging using VLAN tagging, which allows flexible virtual network configurations. For network monitoring in IaaS, a proxy that interacts with users is proposed to dynamically configure monitoring while maintaining provider control over network devices.
The document discusses the Open Cloud Computing Interface (OCCI), which aims to provide an open standard interface for cloud computing. It describes OCCI's goals of allowing interoperability between different cloud providers and preventing vendor lock-in. The core OCCI model defines basic resource and link entity types and supports extensions for additional types and functionality. OCCI uses a RESTful API and represents entities with URIs to allow their creation, retrieval, updating and deletion. Implementations of OCCI have been made for various programming languages and cloud platforms.
Automated Provisioning, Management & Cost Control for Kubernetes ClustersWeaveworks
In today’s economic climate, IT departments are feeling the pressure to reduce costs which can have a significant effect on development teams, and more specifically, Kubernetes strategies. For many organizations, there is a good chance that many Kubernetes resources are overprovisioned, and it’s often difficult to visualize which processes are responsible for this unnecessary spend.
Weaveworks has joined forces with KubeCost to show you how to “do more with less” by easily integrating a Kubernetes FinOps solution into your existing workflows and seamlessly automating the provisioning and management of FinOps enabled Kubernetes clusters from a single UI / dashboard.
Join this webinar to discover best practices for monitoring and reducing Kubernetes spend, while balancing cost, performance, and reliability.
What you’ll learn:
- Best practices for implementing a FinOps strategy in your organization.
- Cluster management and templating capabilities using Weave GitOps for automating FinOps.
- How to use predefined, automated policies for reliable cost control across your Kubernetes environment.
Comparative Analysis of IT Monitoring Toolsapprize360
This document provides a comparative analysis of IT monitoring platforms from CA Technologies, SolarWinds, IBM, and Nagios. It finds that CA Nimsoft Monitor version 7.5 had the fastest time to begin monitoring devices, being able to monitor 100 devices within 61 minutes of downloading and installing the software. In comparison, it took over 3 hours for Nagios XI and over 2 hours for some SolarWinds products to complete the same tasks. The analysis concludes that CA Nimsoft Monitor offers a single, unified monitoring solution while competitors require multiple individual products, and that CA Nimsoft Monitor's installation and configuration process is much easier and faster than the alternatives.
Migrating large, complex, multi-tiered applications to Kubernetes can be a challenging task. In the talk, we share the experience of migrating our service-based, unified monitoring solution, NetEye 4 (https://www.wuerth-phoenix.com/en/solutions/it-system-management/unified-monitoring/), to a more modern micro-service oriented solution like Kubernetes, with the ultimate goal of providing a monitoring solution as a Service for large and multi-tenant infrastructures
Currently, NetEye 4 is built on top of the Red Hat cluster technology, which provides a set of features to implement resilient applications. With this technology, each tier of NetEye 4 is indeed high-available and distributed across multiple physical servers.
However, the burden to obtain a high-available, highly performing and scalable solution is high: it requires custom implementations to leverage the full set of functionalities offered by the infrastructure, which is not always available out-of-the-box.
Can Kubernetes be the possible solution to these problems? Which complexity is hidden under the hood of Kubernetes? Is Kubernetes complexity justified to fulfill our vision of offering unified monitoring as a Service and optimizing scalability in large environments? To answer these questions, we decide to use a product-testing method to explore potential solutions.
Four considerations when monitoring microservicesJason Bloomberg
The adoption of microservices add a new layer of complexity to an already complex application environment. When application issues arise, it becomes difficult to pinpoint the source and, too often, you find yourself in lengthy war rooms or assigning experts to triage every issue. As a result, brand loyalty, customer satisfaction and innovation are negatively impacted. The old approach to monitoring application performance just isn’t working. A new approach is needed. In this session we will discuss four areas that you should consider which will change the way you think about monitoring microservices
Continuous Delivery of a Cloud Deployment at a Large Telecommunications ProviderM Kevin McHugh
This document discusses how a large telecommunications provider implemented continuous delivery for a cloud deployment. It defines continuous delivery as automating the process of software delivery through techniques like continuous integration, automated testing, and continuous deployment. It then describes the specific components and tools used in the telecom provider's implementation, including adopting agile methodology, integrating rational team concert, automated testing with a REST API, and using SmartCloud Orchestrator for automated builds and deployment.
Automating it management with Puppet + ServiceNowPuppet
As the leading IT Service Management and IT Operations Management platform in the marketplace, ServiceNow is used by many organizations to address everything from self service IT requests to Change, Incident and Problem Management. The strength of the platform is in the workflows and processes that are built around the shared data model, represented in the CMDB. This provides the ‘single source of truth’ for the organization.
Puppet Enterprise is a leading automation platform focused on the IT Configuration Management and Compliance space. Puppet Enterprise has a unique perspective on the state of systems being managed, constantly being updated and kept accurate as part of the regular Puppet operation. Puppet Enterprise is the automation engine ensuring that the environment stays consistent and in compliance.
In this webinar, we will explore how to maximize the value of both solutions, with Puppet Enterprise automating the actions required to drive a change, and ServiceNow governing the process around that change, from definition to approval. We will introduce and demonstrate several published integration points between the two solutions, in the areas of Self-Service Infrastructure, Enriched Change Management and Automated Incident Registration.
A Comparative Study of Different types of Models in Software Development Life...IRJET Journal
This document compares and contrasts three common software development models: the waterfall model, iterative enhancement model, and prototyping model. It discusses the key stages and processes in each model, including requirements analysis, design, implementation, testing, and maintenance. The waterfall model is described as the classic sequential model, while the iterative and prototyping models allow for more flexibility and user feedback. The document analyzes the advantages and disadvantages of each approach and concludes each model tries to improve on the limitations of previous ones. The iterative model is seen as overcoming issues of the waterfall by allowing feedback, while the prototyping model is useful for complex or unestablished requirements.
The document summarizes a MuleSoft meetup event that took place in Princeton, NJ on September 23rd, 2023. The meetup agenda included an introduction by the organizers, a presentation and demo on troubleshooting with Anypoint Monitoring by the speaker Beauty Mishra, and a Q&A session. Key points covered in the presentation included an overview of Anypoint Monitoring features for apps running on CloudHub or on-premises servers, how to enable automatic monitoring, configure alerts, and use built-in and custom dashboards. The meetup concluded with a request for feedback and suggestions for future meetup topics.
Práticas, Técnicas e Ferramentas para Continuous Delivery com ALMMarcelo Sousa Ancelmo
Palestra feita na trilha de DevOps no TDC2014 em São Paulo.
Como estruturar uma estratégia de Continuous Delivery suportada por ALM, promovendo visibilidade, colaboração e controle
Mis on andmekeskuse uus standard - hüperkonvergents?
Kui kõiki kesksüsteeme ei ole võimalik pilve viia ja serverikeskuse kasv suurendab halduse keerukust, on väljapääs serverikeskuse konvergents. Simplivity Omnicube on konvergentsi uus tase. Millised on serverikeskuse kasvuga seotud põhiprobleemid ja kuidas neid lahendada? Kuidas korraldada Disaster Recovery ja Backup?
The document outlines an agenda for a conference on innovation, digitization and sustainability with AI. The agenda includes sessions on exploring ChatGPT and future language technology, AWS expanding in the Norwegian market and how to get started, digital twins with opportunities and risks, and using AI for football, environment and sustainability. There will be breaks between sessions and a social event from 19:00.
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 presentation is to reflect on the amazing advancement of the open source community in the field of Cloud Computing and how does it now allow us to build reliable software components quickly within truly agile infrastructure.
SlideTeam presents Kubernetes Docker Container Implementation Ppt PowerPoint Presentation Slide Templates. This PPT slideshow is an ideal virtual expression of the fundamentals of Kubernetes. The smart data-visualizations make this PowerPoint presentation easy-to-understand and perfect to introduce your audience to the container orchestration system. Use our PPT theme to communicate the definition and need for containers or virtual private servers. Communicate the container, and microservices architecture using cutting-edge graphics. Explain the need for and benefits of Kubernetes for an organization. Elucidate the features, architecture, use cases, installation roadmap, and the 30-60-90 day plan in Kubernetes. Use the neat tabular format to compare Kubernetes with docker swarm based on various parameters. Familiarize your viewers with the various components of Kubernetes. Elaborate on what is Kubelet, Kubectl, and Kubeadm with the help of labeled diagrams. This presentation acquaints your audience with the significance of Kubernetes in management, scaling, automating, and deploying computer applications. Hit the download icon and start personalization. https://bit.ly/2L0Ojdu
OneShare is a self-service platform for development and testing in the cloud. It allows teams to quickly provision virtual environments in Microsoft Azure for building, testing, and managing software projects. Using OneShare, teams can reduce costs by paying only for resources used and accelerate development cycles by automating environment setup. The platform provides tools for continuous integration and delivery, cost monitoring, and team collaboration to improve agility for software teams.
Comment déployer et gérer dans le cloud Azure les environnements de développe...Microsoft Technet France
The document discusses OneShare, a self-service platform for development and testing in the cloud. It aims to provide agile teams with on-demand access to environments and tools through a portal. Teams can provision infrastructure from templates, access ALM tools, and gain insights into resource usage and costs. The platform utilizes Microsoft Azure and seeks to accelerate software delivery through flexibility, cost savings, and productivity gains compared to traditional development approaches.
For a beginner, this is a good quality pictorial representation of DevOps and DevOps Center of Excellence.
Opex Software focuses on consulting, implementation and development of DevOps tools and platforms. Have helped small and large data centers! This presentation talks about Continuous Integration, Continuous Delivery at a high level. For detailed presentations and flows, please ping us.
Thanks again, Enjoy!
DevOps and Safety Critical Systems discusses applying DevOps practices like continuous deployment to safety critical systems. It proposes "partial continuous deployment" which involves:
1. Identifying and isolating safety critical portions of a system's architecture.
2. Applying continuous deployment practices to non-safety critical portions.
3. Continuing traditional testing methods for safety critical portions.
It discusses past efforts in smart grid security controls and hardening deployment pipelines that provide foundations for this approach. Key steps include explicitly defining safety requirements, analyzing architectures to identify minimum required safe components, and refactoring to separate safe and non-safe concerns. Regulatory approval is viewed as a major gate to implementing partial continuous deployment for real safety
Automate Cloud and Application Security Deployments with Barracuda and Puppet...Claire Priester Papas
This document discusses automating cloud and application security deployments with Barracuda and Puppet. It provides an agenda that covers DevSecOps, why automation matters, and a Q&A. Barracuda provides security solutions that can be automated with Puppet to provision, configure, and manage infrastructure and applications. The webinar highlights how Puppet supports cloud deployment best practices and security controls to enable DevSecOps workflows that move fast while staying secure.
PuppetConf 2016: Puppet and vRealize Automation: The Next Generation – Ganesh...Puppet
Here are the slides from Ganesh Subramaniam's PuppetConf 2016 presentation called Puppet and vRealize Automation: The Next Generation. Watch the videos at https://www.youtube.com/playlist?list=PLV86BgbREluVjwwt-9UL8u2Uy8xnzpIqa
Similar to Automated deployment of a microservice based monitoring architecture (20)
Slides for the presentation given at the Webist 2021 conference
Abstract:
A research team that wants to validate a new IoT solution has to implement a testbed. It is a complex step
since it must provide a realistic environment, and this may require skills that are not present in the team. This
paper explores the requirements of an IoT testbed and proposes an open-source solution based on low-cost
and widely available components and technologies. The testbed implements an architecture consisting of a
collector managing several edge devices. Security levels and duty-cycle are tunable depending on the specific
application. After analyzing the testbed requirements, the paper illustrates a template that uses WiFi for the
link layer, HTTPS for structured communication, an ESP8266 board for edge units, and a RaspberryPi for the
collector.
Lezione tenuta nel corso di Mobile and Cyber Physical Systems della Laurea Magistrale di Informatica a Pisa.
- Le App per l'integrazione con altri servizi: ThingTweet e ThingHTTPi
- Le App per l'innesco di azioni: TimeControl, TweetControl e React
- Esercizi pratici in Python
Lezione tenuta nel corso di Mobile and Cyber Physical Systems della Laurea Magistrale di Informatica a Pisa.
- Introduzione a ThingSpeak
- Pubblicazione e recupero di dati
- Pubblicazione e recupero di comandi CallBack
- Esercizi pratici in Python
Slides of the presentation at IEEE WiMob/SEUNet 2017, in Rome.
We exploit an overlooked feature of the ESP8266 WiFi chip, i.e. the AT commands interpreter, to implement a sensor/actuator that meets the above specifications. To test our design, we implement a library that provides a transparent wrapper for AT commands. Hardware and software are available on bitbucket.
The document describes an OCCI extension for monitoring cloud resources from both an administrator and user perspective. It proposes representing monitoring entities like sensors and collectors as OCCI resource and link types. Sensors would aggregate and deliver measurements, while collectors produce measurements. These would be further described through mixins that detail their specific monitoring functionality. The proposal aims to provide on-demand, scalable monitoring as a service to users through a standardized and customizable OCCI interface.
The extension of the OCCI framework to describe a monitoring infrastructure.
A demo explains how the infrastructure is generated starting from the OCCI specification.
The source of the demo (in Java) is available in the repository of the OCCI working group.
The document discusses extending the OCCI API with monitoring capabilities. It proposes adding two new types: Collector and Sensor. The Collector would be a link that extracts operational parameters from a source resource and delivers them to a target resource. The Sensor would be a resource that processes or aggregates output from one or more Collectors, such as by filtering, interpolating, or combining monitoring data. Plugins would provide different options for parameters, transport methods, and ways to aggregate and process data.
Collision avoidance using a wandering token in the PTP protocolAugusto Ciuffoletti
Slides presented during the 2010 WIGOWIN Workshop at the Department of Computer Science in Pisa - May 26.
Full paper available at http://eprints.adm.unipi.it
Algorithms based on the circulation of a unique token are often indicated in the coordination of distributed systems. We introduce the design of the token passing operation at application level, that exhibits the requirements of security, since the token is a sensitive resource, and scalability, since the token passing protocol must not implement security at expense of scalability. These
characteristics make our solution suitable for large scale distributed infrastructures.
1) The document describes a "wandering token" approach for coordinating access to shared resources among thousands of agents in a scalable way.
2) A simulation of the approach for a video on demand application showed that it protected the resource from overload while still granting regular access.
3) The wandering token circulates randomly among members, with a randomized timer governing when new tokens are generated to replace lost tokens. This provides a robust, distributed solution to coordinating access.
The paper explores network virtualization issues related with the Cloud Computing paradigm (mainly intended as IaaS). Finally, we consider this framework from a network monitoring perspective.
The paper is an outcome of the CoreGRID working group at ERCIM.
Grid Infrastructure Architecture A Modular Approach from CoreGRIDAugusto Ciuffoletti
The document discusses a modular approach to grid infrastructure architecture proposed by CoreGRID. It identifies five key functional components of a grid middleware: 1) a workflow analyzer for user interfaces and task monitoring, 2) a checkpoint manager for fault tolerance, 3) a user/account manager for authentication and accounting, 4) a resource monitor for observing resource performance, and 5) a grid information service as the backbone. These components interact through exchanging data structures published via the grid information service while addressing issues like scalability, fault tolerance and security.
The document summarizes research on scalable concurrency control in dynamic distributed systems using a multi-token approach. The approach proposes using a mesh overlay topology and random routing of tokens to control access to a shared resource among a large number of dynamic nodes. Experimental results showed the process converges quickly but with more tokens and worse performance than expected, requiring further tuning of the control loop dynamics.
Prototype Implementation of a Demand Driven Network Monitoring ArchitectureAugusto Ciuffoletti
The document summarizes a prototype implementation of an on-demand network monitoring architecture. The architecture features clients that submit monitoring requests, sensors that perform the monitoring, and agents that route requests and streams. The prototype implements the key components in Java and uses SOAP, UDP, and LDAP. It was developed over three months as a proof of concept for an on-demand approach to network monitoring at Internet scale.
How GenAI Can Improve Supplier Performance Management.pdfZycus
Data Collection and Analysis with GenAI enables organizations to gather, analyze, and visualize vast amounts of supplier data, identifying key performance indicators and trends. Predictive analytics forecast future supplier performance, mitigating risks and seizing opportunities. Supplier segmentation allows for tailored management strategies, optimizing resource allocation. Automated scorecards and reporting provide real-time insights, enhancing transparency and tracking progress. Collaboration is fostered through GenAI-powered platforms, driving continuous improvement. NLP analyzes unstructured feedback, uncovering deeper insights into supplier relationships. Simulation and scenario planning tools anticipate supply chain disruptions, supporting informed decision-making. Integration with existing systems enhances data accuracy and consistency. McKinsey estimates GenAI could deliver $2.6 trillion to $4.4 trillion in economic benefits annually across industries, revolutionizing procurement processes and delivering significant ROI.
Transforming Product Development using OnePlan To Boost Efficiency and Innova...OnePlan Solutions
Ready to overcome challenges and drive innovation in your organization? Join us in our upcoming webinar where we discuss how to combat resource limitations, scope creep, and the difficulties of aligning your projects with strategic goals. Discover how OnePlan can revolutionize your product development processes, helping your team to innovate faster, manage resources more effectively, and deliver exceptional results.
WMF 2024 - Unlocking the Future of Data Powering Next-Gen AI with Vector Data...Luigi Fugaro
Vector databases are transforming how we handle data, allowing us to search through text, images, and audio by converting them into vectors. Today, we'll dive into the basics of this exciting technology and discuss its potential to revolutionize our next-generation AI applications. We'll examine typical uses for these databases and the essential tools
developers need. Plus, we'll zoom in on the advanced capabilities of vector search and semantic caching in Java, showcasing these through a live demo with Redis libraries. Get ready to see how these powerful tools can change the game!
The Power of Visual Regression Testing_ Why It Is Critical for Enterprise App...kalichargn70th171
Visual testing plays a vital role in ensuring that software products meet the aesthetic requirements specified by clients in functional and non-functional specifications. In today's highly competitive digital landscape, users expect a seamless and visually appealing online experience. Visual testing, also known as automated UI testing or visual regression testing, verifies the accuracy of the visual elements that users interact with.
The Comprehensive Guide to Validating Audio-Visual Performances.pdfkalichargn70th171
Ensuring the optimal performance of your audio-visual (AV) equipment is crucial for delivering exceptional experiences. AV performance validation is a critical process that verifies the quality and functionality of your AV setup. Whether you're a content creator, a business conducting webinars, or a homeowner creating a home theater, validating your AV performance is essential.
Superpower Your Apache Kafka Applications Development with Complementary Open...Paul Brebner
Kafka Summit talk (Bangalore, India, May 2, 2024, https://events.bizzabo.com/573863/agenda/session/1300469 )
Many Apache Kafka use cases take advantage of Kafka’s ability to integrate multiple heterogeneous systems for stream processing and real-time machine learning scenarios. But Kafka also exists in a rich ecosystem of related but complementary stream processing technologies and tools, particularly from the open-source community. In this talk, we’ll take you on a tour of a selection of complementary tools that can make Kafka even more powerful. We’ll focus on tools for stream processing and querying, streaming machine learning, stream visibility and observation, stream meta-data, stream visualisation, stream development including testing and the use of Generative AI and LLMs, and stream performance and scalability. By the end you will have a good idea of the types of Kafka “superhero” tools that exist, which are my favourites (and what superpowers they have), and how they combine to save your Kafka applications development universe from swamploads of data stagnation monsters!
Photoshop Tutorial for Beginners (2024 Edition)alowpalsadig
Photoshop Tutorial for Beginners (2024 Edition)
Explore the evolution of programming and software development and design in 2024. Discover emerging trends shaping the future of coding in our insightful analysis."
Here's an overview:Introduction: The Evolution of Programming and Software DevelopmentThe Rise of Artificial Intelligence and Machine Learning in CodingAdopting Low-Code and No-Code PlatformsQuantum Computing: Entering the Software Development MainstreamIntegration of DevOps with Machine Learning: MLOpsAdvancements in Cybersecurity PracticesThe Growth of Edge ComputingEmerging Programming Languages and FrameworksSoftware Development Ethics and AI RegulationSustainability in Software EngineeringThe Future Workforce: Remote and Distributed TeamsConclusion: Adapting to the Changing Software Development LandscapeIntroduction: The Evolution of Programming and Software Development
Photoshop Tutorial for Beginners (2024 Edition)Explore the evolution of programming and software development and design in 2024. Discover emerging trends shaping the future of coding in our insightful analysis."Here's an overview:Introduction: The Evolution of Programming and Software DevelopmentThe Rise of Artificial Intelligence and Machine Learning in CodingAdopting Low-Code and No-Code PlatformsQuantum Computing: Entering the Software Development MainstreamIntegration of DevOps with Machine Learning: MLOpsAdvancements in Cybersecurity PracticesThe Growth of Edge ComputingEmerging Programming Languages and FrameworksSoftware Development Ethics and AI RegulationSustainability in Software EngineeringThe Future Workforce: Remote and Distributed TeamsConclusion: Adapting to the Changing Software Development LandscapeIntroduction: The Evolution of Programming and Software Development
The importance of developing and designing programming in 2024
Programming design and development represents a vital step in keeping pace with technological advancements and meeting ever-changing market needs. This course is intended for anyone who wants to understand the fundamental importance of software development and design, whether you are a beginner or a professional seeking to update your knowledge.
Course objectives:
1. **Learn about the basics of software development:
- Understanding software development processes and tools.
- Identify the role of programmers and designers in software projects.
2. Understanding the software design process:
- Learn about the principles of good software design.
- Discussing common design patterns such as Object-Oriented Design.
3. The importance of user experience (UX) in modern software:
- Explore how user experience can improve software acceptance and usability.
- Tools and techniques to analyze and improve user experience.
4. Increase efficiency and productivity through modern development tools:
- Access to the latest programming tools and languages used in the industry.
- Study live examples of applications
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.
Nashik's top web development company, Upturn India Technologies, crafts innovative digital solutions for your success. Partner with us and achieve your goals
Stork Product Overview: An AI-Powered Autonomous Delivery FleetVince Scalabrino
Imagine a world where instead of blue and brown trucks dropping parcels on our porches, a buzzing drove of drones delivered our goods. Now imagine those drones are controlled by 3 purpose-built AI designed to ensure all packages were delivered as quickly and as economically as possible That's what Stork is all about.
Enhanced Screen Flows UI/UX using SLDS with Tom KittPeter Caitens
Join us for an engaging session led by Flow Champion, Tom Kitt. This session will dive into a technique of enhancing the user interfaces and user experiences within Screen Flows using the Salesforce Lightning Design System (SLDS). This technique uses Native functionality, with No Apex Code, No Custom Components and No Managed Packages required.
Orca: Nocode Graphical Editor for Container OrchestrationPedro J. Molina
Tool demo on CEDI/SISTEDES/JISBD2024 at A Coruña, Spain. 2024.06.18
"Orca: Nocode Graphical Editor for Container Orchestration"
by Pedro J. Molina PhD. from Metadev
A neural network is a machine learning program, or model, that makes decisions in a manner similar to the human brain, by using processes that mimic the way biological neurons work together to identify phenomena, weigh options and arrive at conclusions.
🏎️Tech Transformation: DevOps Insights from the Experts 👩💻campbellclarkson
Connect with fellow Trailblazers, learn from industry experts Glenda Thomson (Salesforce, Principal Technical Architect) and Will Dinn (Judo Bank, Salesforce Development Lead), and discover how to harness DevOps tools with Salesforce.
Secure-by-Design Using Hardware and Software Protection for FDA ComplianceICS
This webinar explores the “secure-by-design” approach to medical device software development. During this important session, we will outline which security measures should be considered for compliance, identify technical solutions available on various hardware platforms, summarize hardware protection methods you should consider when building in security and review security software such as Trusted Execution Environments for secure storage of keys and data, and Intrusion Detection Protection Systems to monitor for threats.
2. Cloud Forward
2015
Augusto Ciuffoletti
Introducing two topics
The title:
Automated deployment of a microservice-based
monitoring infrastructure
Microservices
Monitoring on demand
Let us see how the two stories merge...
3. Cloud Forward
2015
Augusto Ciuffoletti
Introducing two topics
The title:
Automated deployment of a microservice-based
monitoring infrastructure
Microservices
Monitoring on demand
Let us see how the two stories merge...
4. Cloud Forward
2015
Augusto Ciuffoletti
Introducing two topics
The title:
Automated deployment of a microservice-based
monitoring infrastructure
Microservices
Monitoring on demand
Let us see how the two stories merge...
5. Cloud Forward
2015
Augusto Ciuffoletti
Introducing two topics
The title:
Automated deployment of a microservice-based
monitoring infrastructure
Microservices
Monitoring on demand
Let us see how the two stories merge...
6. Cloud Forward
2015
Augusto Ciuffoletti
Number one: Microservices
A design paradigm for distributed system
a book in O’Reilly "animal series" by S Newman
Principles:
each component in the system is designed to provide
one small, well defined service
each component is a stand alone entity that interacts
with others across a network with a well defined
interface
7. Cloud Forward
2015
Augusto Ciuffoletti
Number one: Microservices
A design paradigm for distributed system
a book in O’Reilly "animal series" by S Newman
Principles:
each component in the system is designed to provide
one small, well defined service
each component is a stand alone entity that interacts
with others across a network with a well defined
interface
8. Cloud Forward
2015
Augusto Ciuffoletti
Number one: Microservices
A design paradigm for distributed system
a book in O’Reilly "animal series" by S Newman
Principles:
each component in the system is designed to provide
one small, well defined service
each component is a stand alone entity that interacts
with others across a network with a well defined
interface
9. Cloud Forward
2015
Augusto Ciuffoletti
Number one: Microservices
A design paradigm for distributed system
a book in O’Reilly "animal series" by S Newman
Principles:
each component in the system is designed to provide
one small, well defined service
each component is a stand alone entity that interacts
with others across a network with a well defined
interface
10. Cloud Forward
2015
Augusto Ciuffoletti
Number one: Microservices
A design paradigm for distributed system
a book in O’Reilly "animal series" by S Newman
Principles:
each component in the system is designed to provide
one small, well defined service
each component is a stand alone entity that interacts
with others across a network with a well defined
interface
11. Cloud Forward
2015
Augusto Ciuffoletti
Reasons to adopt the microservices
paradigm
simplifies maintenance
e.g., upgrade one single component
agility in deployment
e.g., to scale up or down
each component may use a different technology
e.g., for technical or performance reasons
simplifies development
e.g., each component developed by a distinct team
robustness
e.g., if one component fails there is a chance that the
system still works
12. Cloud Forward
2015
Augusto Ciuffoletti
Reasons to adopt the microservices
paradigm
simplifies maintenance
e.g., upgrade one single component
agility in deployment
e.g., to scale up or down
each component may use a different technology
e.g., for technical or performance reasons
simplifies development
e.g., each component developed by a distinct team
robustness
e.g., if one component fails there is a chance that the
system still works
13. Cloud Forward
2015
Augusto Ciuffoletti
Reasons to adopt the microservices
paradigm
simplifies maintenance
e.g., upgrade one single component
agility in deployment
e.g., to scale up or down
each component may use a different technology
e.g., for technical or performance reasons
simplifies development
e.g., each component developed by a distinct team
robustness
e.g., if one component fails there is a chance that the
system still works
14. Cloud Forward
2015
Augusto Ciuffoletti
Reasons to adopt the microservices
paradigm
simplifies maintenance
e.g., upgrade one single component
agility in deployment
e.g., to scale up or down
each component may use a different technology
e.g., for technical or performance reasons
simplifies development
e.g., each component developed by a distinct team
robustness
e.g., if one component fails there is a chance that the
system still works
15. Cloud Forward
2015
Augusto Ciuffoletti
Reasons to adopt the microservices
paradigm
simplifies maintenance
e.g., upgrade one single component
agility in deployment
e.g., to scale up or down
each component may use a different technology
e.g., for technical or performance reasons
simplifies development
e.g., each component developed by a distinct team
robustness
e.g., if one component fails there is a chance that the
system still works
16. Cloud Forward
2015
Augusto Ciuffoletti
Reasons to adopt the microservices
paradigm
simplifies maintenance
e.g., upgrade one single component
agility in deployment
e.g., to scale up or down
each component may use a different technology
e.g., for technical or performance reasons
simplifies development
e.g., each component developed by a distinct team
robustness
e.g., if one component fails there is a chance that the
system still works
17. Cloud Forward
2015
Augusto Ciuffoletti
Reasons to adopt the microservices
paradigm
simplifies maintenance
e.g., upgrade one single component
agility in deployment
e.g., to scale up or down
each component may use a different technology
e.g., for technical or performance reasons
simplifies development
e.g., each component developed by a distinct team
robustness
e.g., if one component fails there is a chance that the
system still works
18. Cloud Forward
2015
Augusto Ciuffoletti
Reasons to adopt the microservices
paradigm
simplifies maintenance
e.g., upgrade one single component
agility in deployment
e.g., to scale up or down
each component may use a different technology
e.g., for technical or performance reasons
simplifies development
e.g., each component developed by a distinct team
robustness
e.g., if one component fails there is a chance that the
system still works
19. Cloud Forward
2015
Augusto Ciuffoletti
Reasons to adopt the microservices
paradigm
simplifies maintenance
e.g., upgrade one single component
agility in deployment
e.g., to scale up or down
each component may use a different technology
e.g., for technical or performance reasons
simplifies development
e.g., each component developed by a distinct team
robustness
e.g., if one component fails there is a chance that the
system still works
20. Cloud Forward
2015
Augusto Ciuffoletti
Reasons to adopt the microservices
paradigm
simplifies maintenance
e.g., upgrade one single component
agility in deployment
e.g., to scale up or down
each component may use a different technology
e.g., for technical or performance reasons
simplifies development
e.g., each component developed by a distinct team
robustness
e.g., if one component fails there is a chance that the
system still works
21. Cloud Forward
2015
Augusto Ciuffoletti
Number two: Cloud monitoring
A cloud user wants to have a functional feedback from
cloud sourced resources:
not necessarily to verify service quality
control a scalable resource,
provide feedback to the users,
trigger compensating actions
NIST indicates monitoring as one of the distinctive
features of cloud computing
22. Cloud Forward
2015
Augusto Ciuffoletti
Number two: Cloud monitoring
A cloud user wants to have a functional feedback from
cloud sourced resources:
not necessarily to verify service quality
control a scalable resource,
provide feedback to the users,
trigger compensating actions
NIST indicates monitoring as one of the distinctive
features of cloud computing
23. Cloud Forward
2015
Augusto Ciuffoletti
Number two: Cloud monitoring
A cloud user wants to have a functional feedback from
cloud sourced resources:
not necessarily to verify service quality
control a scalable resource,
provide feedback to the users,
trigger compensating actions
NIST indicates monitoring as one of the distinctive
features of cloud computing
24. Cloud Forward
2015
Augusto Ciuffoletti
Number two: Cloud monitoring
A cloud user wants to have a functional feedback from
cloud sourced resources:
not necessarily to verify service quality
control a scalable resource,
provide feedback to the users,
trigger compensating actions
NIST indicates monitoring as one of the distinctive
features of cloud computing
25. Cloud Forward
2015
Augusto Ciuffoletti
Number two: Cloud monitoring
A cloud user wants to have a functional feedback from
cloud sourced resources:
not necessarily to verify service quality
control a scalable resource,
provide feedback to the users,
trigger compensating actions
NIST indicates monitoring as one of the distinctive
features of cloud computing
26. Cloud Forward
2015
Augusto Ciuffoletti
Number two: Cloud monitoring
A cloud user wants to have a functional feedback from
cloud sourced resources:
not necessarily to verify service quality
control a scalable resource,
provide feedback to the users,
trigger compensating actions
NIST indicates monitoring as one of the distinctive
features of cloud computing
27. Cloud Forward
2015
Augusto Ciuffoletti
Our option: on demand monitoring
Provide monitoring as part of the service
Give the user wide possibilities to configure a
monitoring infrastructure
Which metrics are captured and how data are
preprocessed and retrieved
Scale from simple to complex infrastructures
Do not overkill the problem in simple cases
Cope with complex infrastructures
Resource agnostic
Basic functionalities and unlimited pluggable
extensions
28. Cloud Forward
2015
Augusto Ciuffoletti
Our option: on demand monitoring
Provide monitoring as part of the service
Give the user wide possibilities to configure a
monitoring infrastructure
Which metrics are captured and how data are
preprocessed and retrieved
Scale from simple to complex infrastructures
Do not overkill the problem in simple cases
Cope with complex infrastructures
Resource agnostic
Basic functionalities and unlimited pluggable
extensions
29. Cloud Forward
2015
Augusto Ciuffoletti
Our option: on demand monitoring
Provide monitoring as part of the service
Give the user wide possibilities to configure a
monitoring infrastructure
Which metrics are captured and how data are
preprocessed and retrieved
Scale from simple to complex infrastructures
Do not overkill the problem in simple cases
Cope with complex infrastructures
Resource agnostic
Basic functionalities and unlimited pluggable
extensions
30. Cloud Forward
2015
Augusto Ciuffoletti
Our option: on demand monitoring
Provide monitoring as part of the service
Give the user wide possibilities to configure a
monitoring infrastructure
Which metrics are captured and how data are
preprocessed and retrieved
Scale from simple to complex infrastructures
Do not overkill the problem in simple cases
Cope with complex infrastructures
Resource agnostic
Basic functionalities and unlimited pluggable
extensions
31. Cloud Forward
2015
Augusto Ciuffoletti
Our option: on demand monitoring
Provide monitoring as part of the service
Give the user wide possibilities to configure a
monitoring infrastructure
Which metrics are captured and how data are
preprocessed and retrieved
Scale from simple to complex infrastructures
Do not overkill the problem in simple cases
Cope with complex infrastructures
Resource agnostic
Basic functionalities and unlimited pluggable
extensions
32. Cloud Forward
2015
Augusto Ciuffoletti
Our option: on demand monitoring
Provide monitoring as part of the service
Give the user wide possibilities to configure a
monitoring infrastructure
Which metrics are captured and how data are
preprocessed and retrieved
Scale from simple to complex infrastructures
Do not overkill the problem in simple cases
Cope with complex infrastructures
Resource agnostic
Basic functionalities and unlimited pluggable
extensions
33. Cloud Forward
2015
Augusto Ciuffoletti
Our option: on demand monitoring
Provide monitoring as part of the service
Give the user wide possibilities to configure a
monitoring infrastructure
Which metrics are captured and how data are
preprocessed and retrieved
Scale from simple to complex infrastructures
Do not overkill the problem in simple cases
Cope with complex infrastructures
Resource agnostic
Basic functionalities and unlimited pluggable
extensions
34. Cloud Forward
2015
Augusto Ciuffoletti
Our option: on demand monitoring
Provide monitoring as part of the service
Give the user wide possibilities to configure a
monitoring infrastructure
Which metrics are captured and how data are
preprocessed and retrieved
Scale from simple to complex infrastructures
Do not overkill the problem in simple cases
Cope with complex infrastructures
Resource agnostic
Basic functionalities and unlimited pluggable
extensions
35. Cloud Forward
2015
Augusto Ciuffoletti
Find a match
Monitoring is by nature split into small components
(remember Nagios)
monitoring probes are small components, possibly
embedded
monitoring data crosses a pipe of processors
(anonymization, aggregation etc)
data is finally published using an endpoint reachable
from the outside (database, web service)
Each component is supported by a specific
technology
e.g., network monitoring vs storage monitoring
The on demand nature requires agility in deployment
the cloud user that obtains a new resource may want
to monitor it
There is a match between
microservices and on demand monitoring
36. Cloud Forward
2015
Augusto Ciuffoletti
Find a match
Monitoring is by nature split into small components
(remember Nagios)
monitoring probes are small components, possibly
embedded
monitoring data crosses a pipe of processors
(anonymization, aggregation etc)
data is finally published using an endpoint reachable
from the outside (database, web service)
Each component is supported by a specific
technology
e.g., network monitoring vs storage monitoring
The on demand nature requires agility in deployment
the cloud user that obtains a new resource may want
to monitor it
There is a match between
microservices and on demand monitoring
37. Cloud Forward
2015
Augusto Ciuffoletti
Find a match
Monitoring is by nature split into small components
(remember Nagios)
monitoring probes are small components, possibly
embedded
monitoring data crosses a pipe of processors
(anonymization, aggregation etc)
data is finally published using an endpoint reachable
from the outside (database, web service)
Each component is supported by a specific
technology
e.g., network monitoring vs storage monitoring
The on demand nature requires agility in deployment
the cloud user that obtains a new resource may want
to monitor it
There is a match between
microservices and on demand monitoring
38. Cloud Forward
2015
Augusto Ciuffoletti
Find a match
Monitoring is by nature split into small components
(remember Nagios)
monitoring probes are small components, possibly
embedded
monitoring data crosses a pipe of processors
(anonymization, aggregation etc)
data is finally published using an endpoint reachable
from the outside (database, web service)
Each component is supported by a specific
technology
e.g., network monitoring vs storage monitoring
The on demand nature requires agility in deployment
the cloud user that obtains a new resource may want
to monitor it
There is a match between
microservices and on demand monitoring
39. Cloud Forward
2015
Augusto Ciuffoletti
Find a match
Monitoring is by nature split into small components
(remember Nagios)
monitoring probes are small components, possibly
embedded
monitoring data crosses a pipe of processors
(anonymization, aggregation etc)
data is finally published using an endpoint reachable
from the outside (database, web service)
Each component is supported by a specific
technology
e.g., network monitoring vs storage monitoring
The on demand nature requires agility in deployment
the cloud user that obtains a new resource may want
to monitor it
There is a match between
microservices and on demand monitoring
40. Cloud Forward
2015
Augusto Ciuffoletti
Find a match
Monitoring is by nature split into small components
(remember Nagios)
monitoring probes are small components, possibly
embedded
monitoring data crosses a pipe of processors
(anonymization, aggregation etc)
data is finally published using an endpoint reachable
from the outside (database, web service)
Each component is supported by a specific
technology
e.g., network monitoring vs storage monitoring
The on demand nature requires agility in deployment
the cloud user that obtains a new resource may want
to monitor it
There is a match between
microservices and on demand monitoring
41. Cloud Forward
2015
Augusto Ciuffoletti
Find a match
Monitoring is by nature split into small components
(remember Nagios)
monitoring probes are small components, possibly
embedded
monitoring data crosses a pipe of processors
(anonymization, aggregation etc)
data is finally published using an endpoint reachable
from the outside (database, web service)
Each component is supported by a specific
technology
e.g., network monitoring vs storage monitoring
The on demand nature requires agility in deployment
the cloud user that obtains a new resource may want
to monitor it
There is a match between
microservices and on demand monitoring
42. Cloud Forward
2015
Augusto Ciuffoletti
Find a match
Monitoring is by nature split into small components
(remember Nagios)
monitoring probes are small components, possibly
embedded
monitoring data crosses a pipe of processors
(anonymization, aggregation etc)
data is finally published using an endpoint reachable
from the outside (database, web service)
Each component is supported by a specific
technology
e.g., network monitoring vs storage monitoring
The on demand nature requires agility in deployment
the cloud user that obtains a new resource may want
to monitor it
There is a match between
microservices and on demand monitoring
43. Cloud Forward
2015
Augusto Ciuffoletti
Find a match
Monitoring is by nature split into small components
(remember Nagios)
monitoring probes are small components, possibly
embedded
monitoring data crosses a pipe of processors
(anonymization, aggregation etc)
data is finally published using an endpoint reachable
from the outside (database, web service)
Each component is supported by a specific
technology
e.g., network monitoring vs storage monitoring
The on demand nature requires agility in deployment
the cloud user that obtains a new resource may want
to monitor it
There is a match between
microservices and on demand monitoring
45. Cloud Forward
2015
Augusto Ciuffoletti
A monitoring infrastructure
Adding a monitoring infrastructure:
probes that collect monitoring data (collectors)
a device that processes monitoring data (sensor)
46. Cloud Forward
2015
Augusto Ciuffoletti
A monitoring infrastructure
Adding a monitoring infrastructure:
probes that collect monitoring data (collectors)
a device that processes monitoring data (sensor)
47. Cloud Forward
2015
Augusto Ciuffoletti
A monitoring infrastructure
Adding a monitoring infrastructure:
probes that collect monitoring data (collectors)
a device that processes monitoring data (sensor)
50. Cloud Forward
2015
Augusto Ciuffoletti
Open Cloud Computing Interface basics
The interface is REST, therefore web-oriented
The items accessed across the interface are entities
One type of entity is the resource
Another is the link, that connects two resources
A type is characterized by standard features of the
instances
attributes whose values define instances
actions that model dynamic change
The interface is extensible:
a type can be subtyped, thus adding new attributes
to the standard ones
an instance can be modified using mixins
51. Cloud Forward
2015
Augusto Ciuffoletti
Open Cloud Computing Interface basics
The interface is REST, therefore web-oriented
The items accessed across the interface are entities
One type of entity is the resource
Another is the link, that connects two resources
A type is characterized by standard features of the
instances
attributes whose values define instances
actions that model dynamic change
The interface is extensible:
a type can be subtyped, thus adding new attributes
to the standard ones
an instance can be modified using mixins
52. Cloud Forward
2015
Augusto Ciuffoletti
Open Cloud Computing Interface basics
The interface is REST, therefore web-oriented
The items accessed across the interface are entities
One type of entity is the resource
Another is the link, that connects two resources
A type is characterized by standard features of the
instances
attributes whose values define instances
actions that model dynamic change
The interface is extensible:
a type can be subtyped, thus adding new attributes
to the standard ones
an instance can be modified using mixins
53. Cloud Forward
2015
Augusto Ciuffoletti
Open Cloud Computing Interface basics
The interface is REST, therefore web-oriented
The items accessed across the interface are entities
One type of entity is the resource
Another is the link, that connects two resources
A type is characterized by standard features of the
instances
attributes whose values define instances
actions that model dynamic change
The interface is extensible:
a type can be subtyped, thus adding new attributes
to the standard ones
an instance can be modified using mixins
54. Cloud Forward
2015
Augusto Ciuffoletti
Open Cloud Computing Interface basics
The interface is REST, therefore web-oriented
The items accessed across the interface are entities
One type of entity is the resource
Another is the link, that connects two resources
A type is characterized by standard features of the
instances
attributes whose values define instances
actions that model dynamic change
The interface is extensible:
a type can be subtyped, thus adding new attributes
to the standard ones
an instance can be modified using mixins
55. Cloud Forward
2015
Augusto Ciuffoletti
Open Cloud Computing Interface basics
The interface is REST, therefore web-oriented
The items accessed across the interface are entities
One type of entity is the resource
Another is the link, that connects two resources
A type is characterized by standard features of the
instances
attributes whose values define instances
actions that model dynamic change
The interface is extensible:
a type can be subtyped, thus adding new attributes
to the standard ones
an instance can be modified using mixins
56. Cloud Forward
2015
Augusto Ciuffoletti
Open Cloud Computing Interface basics
The interface is REST, therefore web-oriented
The items accessed across the interface are entities
One type of entity is the resource
Another is the link, that connects two resources
A type is characterized by standard features of the
instances
attributes whose values define instances
actions that model dynamic change
The interface is extensible:
a type can be subtyped, thus adding new attributes
to the standard ones
an instance can be modified using mixins
57. Cloud Forward
2015
Augusto Ciuffoletti
Open Cloud Computing Interface basics
The interface is REST, therefore web-oriented
The items accessed across the interface are entities
One type of entity is the resource
Another is the link, that connects two resources
A type is characterized by standard features of the
instances
attributes whose values define instances
actions that model dynamic change
The interface is extensible:
a type can be subtyped, thus adding new attributes
to the standard ones
an instance can be modified using mixins
58. Cloud Forward
2015
Augusto Ciuffoletti
Open Cloud Computing Interface basics
The interface is REST, therefore web-oriented
The items accessed across the interface are entities
One type of entity is the resource
Another is the link, that connects two resources
A type is characterized by standard features of the
instances
attributes whose values define instances
actions that model dynamic change
The interface is extensible:
a type can be subtyped, thus adding new attributes
to the standard ones
an instance can be modified using mixins
59. Cloud Forward
2015
Augusto Ciuffoletti
Open Cloud Computing Interface basics
The interface is REST, therefore web-oriented
The items accessed across the interface are entities
One type of entity is the resource
Another is the link, that connects two resources
A type is characterized by standard features of the
instances
attributes whose values define instances
actions that model dynamic change
The interface is extensible:
a type can be subtyped, thus adding new attributes
to the standard ones
an instance can be modified using mixins
60. Cloud Forward
2015
Augusto Ciuffoletti
An OCCI model for monitoring
A Sensor is a subtype of the Resource type
A Collector is a subtype of the Link type
Add Mixins to specify the type of activity
Legenda:
the sensor (red) is an OCCI resource
the collectors (blue) are OCCI links
computing boxes and the network are OCCI
resources too
61. Cloud Forward
2015
Augusto Ciuffoletti
An OCCI model for monitoring
A Sensor is a subtype of the Resource type
A Collector is a subtype of the Link type
Add Mixins to specify the type of activity
Legenda:
the sensor (red) is an OCCI resource
the collectors (blue) are OCCI links
computing boxes and the network are OCCI
resources too
62. Cloud Forward
2015
Augusto Ciuffoletti
An OCCI model for monitoring
A Sensor is a subtype of the Resource type
A Collector is a subtype of the Link type
Add Mixins to specify the type of activity
Legenda:
the sensor (red) is an OCCI resource
the collectors (blue) are OCCI links
computing boxes and the network are OCCI
resources too
63. Cloud Forward
2015
Augusto Ciuffoletti
An OCCI model for monitoring
A Sensor is a subtype of the Resource type
A Collector is a subtype of the Link type
Add Mixins to specify the type of activity
Legenda:
the sensor (red) is an OCCI resource
the collectors (blue) are OCCI links
computing boxes and the network are OCCI
resources too
64. Cloud Forward
2015
Augusto Ciuffoletti
An OCCI model for monitoring
A Sensor is a subtype of the Resource type
A Collector is a subtype of the Link type
Add Mixins to specify the type of activity
Legenda:
the sensor (red) is an OCCI resource
the collectors (blue) are OCCI links
computing boxes and the network are OCCI
resources too
65. Cloud Forward
2015
Augusto Ciuffoletti
An OCCI model for monitoring
A Sensor is a subtype of the Resource type
A Collector is a subtype of the Link type
Add Mixins to specify the type of activity
Legenda:
the sensor (red) is an OCCI resource
the collectors (blue) are OCCI links
computing boxes and the network are OCCI
resources too
66. Cloud Forward
2015
Augusto Ciuffoletti
An OCCI model for monitoring
A Sensor is a subtype of the Resource type
A Collector is a subtype of the Link type
Add Mixins to specify the type of activity
Legenda:
the sensor (red) is an OCCI resource
the collectors (blue) are OCCI links
computing boxes and the network are OCCI
resources too
67. Cloud Forward
2015
Augusto Ciuffoletti
An OCCI model for monitoring
A Sensor is a subtype of the Resource type
A Collector is a subtype of the Link type
Add Mixins to specify the type of activity
Legenda:
the sensor (red) is an OCCI resource
the collectors (blue) are OCCI links
computing boxes and the network are OCCI
resources too
68. Cloud Forward
2015
Augusto Ciuffoletti
How do we do that?
We want to study the big arrow in the figure
How do we implement a monitoring infrastructure starting
form OCCI entities
69. Cloud Forward
2015
Augusto Ciuffoletti
How do we do that?
We want to study the big arrow in the figure
How do we implement a monitoring infrastructure starting
form OCCI entities
70. Cloud Forward
2015
Augusto Ciuffoletti
Vintage programming but...
For an early prototype we selected seasoned
technologies: Java/Unix sockets/Unix Pipes
not bound to specific programming tools
better solutions do exist
As a virtualization platform we selected Docker
demo is easely reproduceable/shareable
efficient to run on a single laptop
upgradeable to a real deployment
71. Cloud Forward
2015
Augusto Ciuffoletti
Vintage programming but...
For an early prototype we selected seasoned
technologies: Java/Unix sockets/Unix Pipes
not bound to specific programming tools
better solutions do exist
As a virtualization platform we selected Docker
demo is easely reproduceable/shareable
efficient to run on a single laptop
upgradeable to a real deployment
72. Cloud Forward
2015
Augusto Ciuffoletti
Vintage programming but...
For an early prototype we selected seasoned
technologies: Java/Unix sockets/Unix Pipes
not bound to specific programming tools
better solutions do exist
As a virtualization platform we selected Docker
demo is easely reproduceable/shareable
efficient to run on a single laptop
upgradeable to a real deployment
73. Cloud Forward
2015
Augusto Ciuffoletti
Vintage programming but...
For an early prototype we selected seasoned
technologies: Java/Unix sockets/Unix Pipes
not bound to specific programming tools
better solutions do exist
As a virtualization platform we selected Docker
demo is easely reproduceable/shareable
efficient to run on a single laptop
upgradeable to a real deployment
74. Cloud Forward
2015
Augusto Ciuffoletti
Vintage programming but...
For an early prototype we selected seasoned
technologies: Java/Unix sockets/Unix Pipes
not bound to specific programming tools
better solutions do exist
As a virtualization platform we selected Docker
demo is easely reproduceable/shareable
efficient to run on a single laptop
upgradeable to a real deployment
75. Cloud Forward
2015
Augusto Ciuffoletti
Vintage programming but...
For an early prototype we selected seasoned
technologies: Java/Unix sockets/Unix Pipes
not bound to specific programming tools
better solutions do exist
As a virtualization platform we selected Docker
demo is easely reproduceable/shareable
efficient to run on a single laptop
upgradeable to a real deployment
76. Cloud Forward
2015
Augusto Ciuffoletti
Vintage programming but...
For an early prototype we selected seasoned
technologies: Java/Unix sockets/Unix Pipes
not bound to specific programming tools
better solutions do exist
As a virtualization platform we selected Docker
demo is easely reproduceable/shareable
efficient to run on a single laptop
upgradeable to a real deployment
77. Cloud Forward
2015
Augusto Ciuffoletti
Deploying a demo infrastructure
The minimal architecture (4 dockers):
one HTTP server to host the OCCI entities
descriptions
one dashboard to display monitoring data
one monitored compute resource
one sensor resource
In OCCI view
One compute resource
One sensor resource
One collector link
78. Cloud Forward
2015
Augusto Ciuffoletti
Deploying a demo infrastructure
The minimal architecture (4 dockers):
one HTTP server to host the OCCI entities
descriptions
one dashboard to display monitoring data
one monitored compute resource
one sensor resource
In OCCI view
One compute resource
One sensor resource
One collector link
79. Cloud Forward
2015
Augusto Ciuffoletti
Deploying a demo infrastructure
The minimal architecture (4 dockers):
one HTTP server to host the OCCI entities
descriptions
one dashboard to display monitoring data
one monitored compute resource
one sensor resource
In OCCI view
One compute resource
One sensor resource
One collector link
80. Cloud Forward
2015
Augusto Ciuffoletti
Deploying a demo infrastructure
The minimal architecture (4 dockers):
one HTTP server to host the OCCI entities
descriptions
one dashboard to display monitoring data
one monitored compute resource
one sensor resource
In OCCI view
One compute resource
One sensor resource
One collector link
81. Cloud Forward
2015
Augusto Ciuffoletti
Deploying a demo infrastructure
The minimal architecture (4 dockers):
one HTTP server to host the OCCI entities
descriptions
one dashboard to display monitoring data
one monitored compute resource
one sensor resource
In OCCI view
One compute resource
One sensor resource
One collector link
82. Cloud Forward
2015
Augusto Ciuffoletti
Deploying a demo infrastructure
The minimal architecture (4 dockers):
one HTTP server to host the OCCI entities
descriptions
one dashboard to display monitoring data
one monitored compute resource
one sensor resource
In OCCI view
One compute resource
One sensor resource
One collector link
83. Cloud Forward
2015
Augusto Ciuffoletti
Deploying a demo infrastructure
The minimal architecture (4 dockers):
one HTTP server to host the OCCI entities
descriptions
one dashboard to display monitoring data
one monitored compute resource
one sensor resource
In OCCI view
One compute resource
One sensor resource
One collector link
84. Cloud Forward
2015
Augusto Ciuffoletti
Deploying a demo infrastructure
The minimal architecture (4 dockers):
one HTTP server to host the OCCI entities
descriptions
one dashboard to display monitoring data
one monitored compute resource
one sensor resource
In OCCI view
One compute resource
One sensor resource
One collector link
85. Cloud Forward
2015
Augusto Ciuffoletti
Deploying a demo infrastructure
The minimal architecture (4 dockers):
one HTTP server to host the OCCI entities
descriptions
one dashboard to display monitoring data
one monitored compute resource
one sensor resource
In OCCI view
One compute resource
One sensor resource
One collector link