OpenShift is a Platform-as-a-Service that provides development environments on demand using containers. It automates application lifecycles including build, deploy, and retirement. OpenShift uses containers to package applications and dependencies in a portable way. Red Hat addresses concerns around adopting containers at scale through OpenShift, which provides security, scalability, integration, management and certification capabilities. OpenShift runs on a user's choice of infrastructure and orchestrates applications across nodes using Kubernetes.
Logs/Metrics Gathering With OpenShift EFK StackJosef Karásek
This document summarizes a presentation about logs and metrics gathering with the OpenShift EFK stack. It introduces the OpenShift logging team and their objectives of collecting distributed logs in a common data model with security and scalability. It describes the main components of Fluendt for collection and normalization and Elasticsearch for storage. It provides examples of using the logging stack with OpenShift, OpenStack, and oVirt and advice for custom application logging.
OpenShift 4 provides a fully automated installation and day-2 operations experience. It features over-the-air updates, hybrid and multi-cluster management through operators, and services for developers like OpenShift Service Mesh and Serverless. The operating system is Red Hat Enterprise Linux CoreOS, which is immutable and tightly integrated with OpenShift.
This document provides an overview of Red Hat's OpenShift Platform-as-a-Service (PaaS). OpenShift simplifies and automates the development, deployment and scaling of applications. It allows developers to focus on coding instead of managing infrastructure. OpenShift runs applications securely in isolated containers (gears) on top of Red Hat Enterprise Linux. Developers can use integrated tools or a web console to develop, build and deploy applications. OpenShift then automatically scales applications based on demand. The open source OpenShift Origin project allows organizations to run their own private PaaS or contribute to the community.
Building Cloud-Native App Series - Part 11 of 11
Microservices Architecture Series
Service Mesh - Observability
- Zipkin
- Prometheus
- Grafana
- Kiali
OpenShift is a Platform-as-a-Service that provides development environments on demand using containers. It automates application lifecycles including build, deploy, and retirement. OpenShift uses containers to package applications and dependencies in a portable way. Red Hat addresses concerns around adopting containers at scale through OpenShift, which provides security, scalability, integration, management and certification capabilities. OpenShift runs on a user's choice of infrastructure and orchestrates applications across nodes using Kubernetes.
Logs/Metrics Gathering With OpenShift EFK StackJosef Karásek
This document summarizes a presentation about logs and metrics gathering with the OpenShift EFK stack. It introduces the OpenShift logging team and their objectives of collecting distributed logs in a common data model with security and scalability. It describes the main components of Fluendt for collection and normalization and Elasticsearch for storage. It provides examples of using the logging stack with OpenShift, OpenStack, and oVirt and advice for custom application logging.
OpenShift 4 provides a fully automated installation and day-2 operations experience. It features over-the-air updates, hybrid and multi-cluster management through operators, and services for developers like OpenShift Service Mesh and Serverless. The operating system is Red Hat Enterprise Linux CoreOS, which is immutable and tightly integrated with OpenShift.
This document provides an overview of Red Hat's OpenShift Platform-as-a-Service (PaaS). OpenShift simplifies and automates the development, deployment and scaling of applications. It allows developers to focus on coding instead of managing infrastructure. OpenShift runs applications securely in isolated containers (gears) on top of Red Hat Enterprise Linux. Developers can use integrated tools or a web console to develop, build and deploy applications. OpenShift then automatically scales applications based on demand. The open source OpenShift Origin project allows organizations to run their own private PaaS or contribute to the community.
Building Cloud-Native App Series - Part 11 of 11
Microservices Architecture Series
Service Mesh - Observability
- Zipkin
- Prometheus
- Grafana
- Kiali
Apache Kafka is a distributed streaming platform used for building real-time data pipelines and streaming apps. It provides a unified, scalable, and durable platform for handling real-time data feeds. Kafka works by accepting streams of records from one or more producers and organizing them into topics. It allows both storing and forwarding of these streams to consumers. Producers write data to topics which are replicated across clusters for fault tolerance. Consumers can then read the data from the topics in the order it was produced. Major companies like LinkedIn, Yahoo, Twitter, and Netflix use Kafka for applications like metrics, logging, stream processing and more.
Kubernetes 101 - an Introduction to Containers, Kubernetes, and OpenShiftDevOps.com
Administrators and developers are increasingly seeking ways to improve application time to market and improve maintainability. Containers and Red Hat® OpenShift® have quickly become the de facto solution for agile development and application deployment.
Red Hat Training has developed a course that provides the gateway to container adoption by understanding the potential of DevOps using a container-based architecture. Orchestrating a container-based architecture with Kubernetes and Red Hat® OpenShift® improves application reliability and scalability, decreases developer overhead, and facilitates continuous integration and continuous deployment.
In this webinar, our expert will cover:
An overview of container and OpenShift architecture.
How to manage containers and container images.
Deploying containerized applications with Red Hat OpenShift.
An outline of Red Hat OpenShift training offerings.
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.
OpenShift Virtualization - VM and OS Image LifecycleMihai Criveti
1. Select "Create Virtual Machine" from the Workloads menu.
2. On the General tab, choose the source of the virtual machine such as a Container image, URL, or existing disk. Then select the Operating System.
3. Configure resources for the virtual machine including CPU, memory, and storage on the Hardware tab.
4. Review and create the virtual machine. The new virtual machine will be added to the list and can be managed like other workloads.
OpenShift 4, the smarter Kubernetes platformKangaroot
OpenShift 4 introduces automated installation, patching, and upgrades for every layer of the container stack from the operating system through application services.
Cloud Native Applications on OpenShiftSerhat Dirik
This document discusses cloud native development and DevOps using OpenShift Container Platform. It begins by defining cloud native as involving both application architecture and the development, deployment and management processes used. It then discusses how containers evolve application delivery and how container platforms are part of the DevOps tool kit. The document outlines the path to DevOps, emphasizing culture, automation and using the right platform. It also notes that DevOps and containers often go hand in hand, with many DevOps adopters using containers. The document then discusses various capabilities of OpenShift and how it supports cloud native development.
The document provides an introduction to Red Hat OpenShift, including:
- An overview of the differences between virtual machines and container technologies like Docker.
- The evolution of container technologies and standards like Kubernetes, CRI, and CNI.
- Why Kubernetes is used for container orchestration and why Red Hat OpenShift is a popular Kubernetes distribution.
- Key features of Red Hat OpenShift like source-to-image builds, integrated monitoring, security, and log aggregation with EFK.
This document provides an overview of cloud native concepts including:
- Cloud native is defined as applications optimized for modern distributed systems capable of scaling to thousands of nodes.
- The pillars of cloud native include devops, continuous delivery, microservices, and containers.
- Common use cases for cloud native include development, operations, legacy application refactoring, migration to cloud, and building new microservice applications.
- While cloud native adoption is growing, challenges include complexity, cultural changes, lack of training, security concerns, and monitoring difficulties.
This document provides an overview of Kubernetes, a container orchestration system. It begins with background on Docker containers and orchestration tools prior to Kubernetes. It then covers key Kubernetes concepts including pods, labels, replication controllers, and services. Pods are the basic deployable unit in Kubernetes, while replication controllers ensure a specified number of pods are running. Services provide discovery and load balancing for pods. The document demonstrates how Kubernetes can be used to scale, upgrade, and rollback deployments through replication controllers and services.
Hands-On Introduction to Kubernetes at LISA17Ryan Jarvinen
This document provides an agenda and instructions for a hands-on introduction to Kubernetes tutorial. The tutorial will cover Kubernetes basics like pods, services, deployments and replica sets. It includes steps for setting up a local Kubernetes environment using Minikube and demonstrates features like rolling updates, rollbacks and self-healing. Attendees will learn how to develop container-based applications locally with Kubernetes and deploy changes to preview them before promoting to production.
This presentation about DevOps will help you understand what is DevOps, how is DevOps different from traditional IT, benefits of DevOps, the lifecycle of DevOps and tools used in DevOps processes. DevOps is one of the most trending IT jobs. It is a collaboration between development and operation teams which enables continuous delivery of applications and services to our end users. However, if you want to become a DevOps engineer, you must have knowledge of various DevOps tools (like Git, Maven, Selenium, Jenkins, Docker, Ansible, Nagios etc.) to achieve automation at each stage which helps in gaining Continuous Development, Continuous Integration, Continuous Testing and Continuous Monitoring in order to deliver a quality product to the client at a very fast pace. Now, let us get started and understand DevOps and does the various DevOps tools work.
Below are the topics explained in this DevOps presentation:
1. What is DevOps?
2. Benefits of DevOps
3. Lifecycle of DevOps
4. Tools in DevOps
Why learn DevOps?
Simplilearn’s DevOps training course is designed to help you become a DevOps practitioner and apply the latest in DevOps methodology to automate your software development lifecycle right out of the class. You will master configuration management; continuous integration deployment, delivery, and monitoring using DevOps tools such as Git, Docker, Jenkins, Puppet, and Nagios in a practical, hands-on and interactive approach. The DevOps training course focuses heavily on the use of Docker containers, a technology that is revolutionizing the way apps are deployed in the cloud today and is a critical skillset to master in the cloud age.
After completing the DevOps training course you will achieve hands-on expertise in various aspects of the DevOps delivery model. The practical learning outcomes of this Devops training course are:
An understanding of DevOps and the modern DevOps toolsets
The ability to automate all aspects of a modern code delivery and deployment pipeline using:
1. Source code management tools
2. Build tools
3. Test automation tools
4. Containerization through Docker
5. Configuration management tools
6. Monitoring tools
Who should take this course?
DevOps career opportunities are thriving worldwide. DevOps was featured as one of the 11 best jobs in America for 2017, according to CBS News, and data from Payscale.com shows that DevOps Managers earn as much as $122,234 per year, with DevOps engineers making as much as $151,461. DevOps jobs are the third-highest tech role ranked by employer demand on Indeed.com but have the second-highest talent deficit.
1. This DevOps training course will be of benefit the following professional roles:
2. Software Developers
3. Technical Project Managers
4. Architects
5. Operations Support
6. Deployment engineers
7. IT managers
8. Development managers
Learn more at https://www.simplilearn.com/cloud-computing/devops-practitioner-certification-training
VxRail Appliance - Modernize your infrastructure and accelerate IT transforma...Maichino Sepede
An overview of the VxRail Appliance, including what’s new with VxRail on the 14th generation PowerEdge server, and advancements in the VxRail 4.5 software.
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 Certification Training: https://www.edureka.co/kubernetes-certification **
This Edureka tutorial on "Kubernetes Architecture" will give you an introduction to popular DevOps tool - Kubernetes, and will deep dive into Kubernetes Architecture and its working. The following topics are covered in this training session:
1. What is Kubernetes
2. Features of Kubernetes
3. Kubernetes Architecture and Its Components
4. Components of Master Node and Worker Node
5. ETCD
6. Network Setup Requirements
DevOps Tutorial Blog Series: https://goo.gl/P0zAfF
Kubernetes has two simple but powerful network concepts: every Pod is connected to the same network, and Services let you talk to a Pod by name. Bryan will take you through how these concepts are implemented - Pod Networks via the Container Network Interface (CNI), Service Discovery via kube-dns and Service virtual IPs, then on to how Services are exposed to the rest of the world.
Red Hat OpenShift V3 Overview and Deep DiveGreg Hoelzer
OpenShift is a platform as a service product from Red Hat that allows developers to easily deploy and manage applications using containers. It provides developers with a common platform to build, deploy and update applications quickly using containers. For IT operations, OpenShift improves efficiency and infrastructure utilization through automated provisioning and management of application services. Some key customers highlighted include a large enterprise software company, a major online travel agency, and a leading financial analytics software provider.
This document discusses OpenShift Container Platform, a platform as a service (PaaS) that provides a full development and deployment platform for applications. It allows developers to easily manage application dependencies and development environments across basic infrastructure, public clouds, and production servers. OpenShift provides container orchestration using Kubernetes along with developer tools and a user experience to support DevOps practices like continuous integration/delivery.
223: Modernization and Migrating from the ESB to ContainersTrevor Dolby
Migrating to ACE v12 and modernising to containers was the topic of the TechCon 2021 virtual experience. It discussed migrating existing ACE/IIB/WMB deployments and assets to ACE V12/11 using the mqsiextractcomponents command. This allows existing BAR files to run unchanged on new integration nodes and independent integration servers alongside existing deployments, enabling staged migration. It also covered modernizing integration by moving to containers and taking advantage of new features in ACE like the development experience and serverless capabilities.
In this session, Diógenes gives an introduction of the basic concepts that make OpenShift, giving special attention to its relationship with Linux containers and Kubernetes.
Kubernetes for Beginners: An Introductory GuideBytemark
Kubernetes is an open-source tool for managing containerized workloads and services. It allows for deploying, maintaining, and scaling applications across clusters of servers. Kubernetes operates at the container level to automate tasks like deployment, availability, and load balancing. It uses a master-slave architecture with a master node controlling multiple worker nodes that host application pods, which are groups of containers that share resources. Kubernetes provides benefits like self-healing, high availability, simplified maintenance, and automatic scaling of containerized applications.
Jeremy Cohoe presented on using the ELK (Elasticsearch, Logstash, Kibana) stack for log analysis. He began with an overview of what ELK is and its components - Logstash parses logs, Elasticsearch is the database, and Kibana provides the GUI. Cohoe then demonstrated using ELK to monitor 802.11 client probes with a software defined radio and parse Flex pager signals. Finally, he discussed implementing ELK in production for a Linux central syslog system, including scaling out with Redis, common plugins, and cluster monitoring tools.
Near Real time Indexing Kafka Messages to Apache Blur using Spark StreamingDibyendu Bhattacharya
My presentation at recently concluded Apache Big Data Conference Europe about the Reliable Low Level Kafka Spark Consumer I developed and an use case of real time indexing to Apache Blur using this consumer
Apache Kafka is a distributed streaming platform used for building real-time data pipelines and streaming apps. It provides a unified, scalable, and durable platform for handling real-time data feeds. Kafka works by accepting streams of records from one or more producers and organizing them into topics. It allows both storing and forwarding of these streams to consumers. Producers write data to topics which are replicated across clusters for fault tolerance. Consumers can then read the data from the topics in the order it was produced. Major companies like LinkedIn, Yahoo, Twitter, and Netflix use Kafka for applications like metrics, logging, stream processing and more.
Kubernetes 101 - an Introduction to Containers, Kubernetes, and OpenShiftDevOps.com
Administrators and developers are increasingly seeking ways to improve application time to market and improve maintainability. Containers and Red Hat® OpenShift® have quickly become the de facto solution for agile development and application deployment.
Red Hat Training has developed a course that provides the gateway to container adoption by understanding the potential of DevOps using a container-based architecture. Orchestrating a container-based architecture with Kubernetes and Red Hat® OpenShift® improves application reliability and scalability, decreases developer overhead, and facilitates continuous integration and continuous deployment.
In this webinar, our expert will cover:
An overview of container and OpenShift architecture.
How to manage containers and container images.
Deploying containerized applications with Red Hat OpenShift.
An outline of Red Hat OpenShift training offerings.
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.
OpenShift Virtualization - VM and OS Image LifecycleMihai Criveti
1. Select "Create Virtual Machine" from the Workloads menu.
2. On the General tab, choose the source of the virtual machine such as a Container image, URL, or existing disk. Then select the Operating System.
3. Configure resources for the virtual machine including CPU, memory, and storage on the Hardware tab.
4. Review and create the virtual machine. The new virtual machine will be added to the list and can be managed like other workloads.
OpenShift 4, the smarter Kubernetes platformKangaroot
OpenShift 4 introduces automated installation, patching, and upgrades for every layer of the container stack from the operating system through application services.
Cloud Native Applications on OpenShiftSerhat Dirik
This document discusses cloud native development and DevOps using OpenShift Container Platform. It begins by defining cloud native as involving both application architecture and the development, deployment and management processes used. It then discusses how containers evolve application delivery and how container platforms are part of the DevOps tool kit. The document outlines the path to DevOps, emphasizing culture, automation and using the right platform. It also notes that DevOps and containers often go hand in hand, with many DevOps adopters using containers. The document then discusses various capabilities of OpenShift and how it supports cloud native development.
The document provides an introduction to Red Hat OpenShift, including:
- An overview of the differences between virtual machines and container technologies like Docker.
- The evolution of container technologies and standards like Kubernetes, CRI, and CNI.
- Why Kubernetes is used for container orchestration and why Red Hat OpenShift is a popular Kubernetes distribution.
- Key features of Red Hat OpenShift like source-to-image builds, integrated monitoring, security, and log aggregation with EFK.
This document provides an overview of cloud native concepts including:
- Cloud native is defined as applications optimized for modern distributed systems capable of scaling to thousands of nodes.
- The pillars of cloud native include devops, continuous delivery, microservices, and containers.
- Common use cases for cloud native include development, operations, legacy application refactoring, migration to cloud, and building new microservice applications.
- While cloud native adoption is growing, challenges include complexity, cultural changes, lack of training, security concerns, and monitoring difficulties.
This document provides an overview of Kubernetes, a container orchestration system. It begins with background on Docker containers and orchestration tools prior to Kubernetes. It then covers key Kubernetes concepts including pods, labels, replication controllers, and services. Pods are the basic deployable unit in Kubernetes, while replication controllers ensure a specified number of pods are running. Services provide discovery and load balancing for pods. The document demonstrates how Kubernetes can be used to scale, upgrade, and rollback deployments through replication controllers and services.
Hands-On Introduction to Kubernetes at LISA17Ryan Jarvinen
This document provides an agenda and instructions for a hands-on introduction to Kubernetes tutorial. The tutorial will cover Kubernetes basics like pods, services, deployments and replica sets. It includes steps for setting up a local Kubernetes environment using Minikube and demonstrates features like rolling updates, rollbacks and self-healing. Attendees will learn how to develop container-based applications locally with Kubernetes and deploy changes to preview them before promoting to production.
This presentation about DevOps will help you understand what is DevOps, how is DevOps different from traditional IT, benefits of DevOps, the lifecycle of DevOps and tools used in DevOps processes. DevOps is one of the most trending IT jobs. It is a collaboration between development and operation teams which enables continuous delivery of applications and services to our end users. However, if you want to become a DevOps engineer, you must have knowledge of various DevOps tools (like Git, Maven, Selenium, Jenkins, Docker, Ansible, Nagios etc.) to achieve automation at each stage which helps in gaining Continuous Development, Continuous Integration, Continuous Testing and Continuous Monitoring in order to deliver a quality product to the client at a very fast pace. Now, let us get started and understand DevOps and does the various DevOps tools work.
Below are the topics explained in this DevOps presentation:
1. What is DevOps?
2. Benefits of DevOps
3. Lifecycle of DevOps
4. Tools in DevOps
Why learn DevOps?
Simplilearn’s DevOps training course is designed to help you become a DevOps practitioner and apply the latest in DevOps methodology to automate your software development lifecycle right out of the class. You will master configuration management; continuous integration deployment, delivery, and monitoring using DevOps tools such as Git, Docker, Jenkins, Puppet, and Nagios in a practical, hands-on and interactive approach. The DevOps training course focuses heavily on the use of Docker containers, a technology that is revolutionizing the way apps are deployed in the cloud today and is a critical skillset to master in the cloud age.
After completing the DevOps training course you will achieve hands-on expertise in various aspects of the DevOps delivery model. The practical learning outcomes of this Devops training course are:
An understanding of DevOps and the modern DevOps toolsets
The ability to automate all aspects of a modern code delivery and deployment pipeline using:
1. Source code management tools
2. Build tools
3. Test automation tools
4. Containerization through Docker
5. Configuration management tools
6. Monitoring tools
Who should take this course?
DevOps career opportunities are thriving worldwide. DevOps was featured as one of the 11 best jobs in America for 2017, according to CBS News, and data from Payscale.com shows that DevOps Managers earn as much as $122,234 per year, with DevOps engineers making as much as $151,461. DevOps jobs are the third-highest tech role ranked by employer demand on Indeed.com but have the second-highest talent deficit.
1. This DevOps training course will be of benefit the following professional roles:
2. Software Developers
3. Technical Project Managers
4. Architects
5. Operations Support
6. Deployment engineers
7. IT managers
8. Development managers
Learn more at https://www.simplilearn.com/cloud-computing/devops-practitioner-certification-training
VxRail Appliance - Modernize your infrastructure and accelerate IT transforma...Maichino Sepede
An overview of the VxRail Appliance, including what’s new with VxRail on the 14th generation PowerEdge server, and advancements in the VxRail 4.5 software.
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 Certification Training: https://www.edureka.co/kubernetes-certification **
This Edureka tutorial on "Kubernetes Architecture" will give you an introduction to popular DevOps tool - Kubernetes, and will deep dive into Kubernetes Architecture and its working. The following topics are covered in this training session:
1. What is Kubernetes
2. Features of Kubernetes
3. Kubernetes Architecture and Its Components
4. Components of Master Node and Worker Node
5. ETCD
6. Network Setup Requirements
DevOps Tutorial Blog Series: https://goo.gl/P0zAfF
Kubernetes has two simple but powerful network concepts: every Pod is connected to the same network, and Services let you talk to a Pod by name. Bryan will take you through how these concepts are implemented - Pod Networks via the Container Network Interface (CNI), Service Discovery via kube-dns and Service virtual IPs, then on to how Services are exposed to the rest of the world.
Red Hat OpenShift V3 Overview and Deep DiveGreg Hoelzer
OpenShift is a platform as a service product from Red Hat that allows developers to easily deploy and manage applications using containers. It provides developers with a common platform to build, deploy and update applications quickly using containers. For IT operations, OpenShift improves efficiency and infrastructure utilization through automated provisioning and management of application services. Some key customers highlighted include a large enterprise software company, a major online travel agency, and a leading financial analytics software provider.
This document discusses OpenShift Container Platform, a platform as a service (PaaS) that provides a full development and deployment platform for applications. It allows developers to easily manage application dependencies and development environments across basic infrastructure, public clouds, and production servers. OpenShift provides container orchestration using Kubernetes along with developer tools and a user experience to support DevOps practices like continuous integration/delivery.
223: Modernization and Migrating from the ESB to ContainersTrevor Dolby
Migrating to ACE v12 and modernising to containers was the topic of the TechCon 2021 virtual experience. It discussed migrating existing ACE/IIB/WMB deployments and assets to ACE V12/11 using the mqsiextractcomponents command. This allows existing BAR files to run unchanged on new integration nodes and independent integration servers alongside existing deployments, enabling staged migration. It also covered modernizing integration by moving to containers and taking advantage of new features in ACE like the development experience and serverless capabilities.
In this session, Diógenes gives an introduction of the basic concepts that make OpenShift, giving special attention to its relationship with Linux containers and Kubernetes.
Kubernetes for Beginners: An Introductory GuideBytemark
Kubernetes is an open-source tool for managing containerized workloads and services. It allows for deploying, maintaining, and scaling applications across clusters of servers. Kubernetes operates at the container level to automate tasks like deployment, availability, and load balancing. It uses a master-slave architecture with a master node controlling multiple worker nodes that host application pods, which are groups of containers that share resources. Kubernetes provides benefits like self-healing, high availability, simplified maintenance, and automatic scaling of containerized applications.
Jeremy Cohoe presented on using the ELK (Elasticsearch, Logstash, Kibana) stack for log analysis. He began with an overview of what ELK is and its components - Logstash parses logs, Elasticsearch is the database, and Kibana provides the GUI. Cohoe then demonstrated using ELK to monitor 802.11 client probes with a software defined radio and parse Flex pager signals. Finally, he discussed implementing ELK in production for a Linux central syslog system, including scaling out with Redis, common plugins, and cluster monitoring tools.
Near Real time Indexing Kafka Messages to Apache Blur using Spark StreamingDibyendu Bhattacharya
My presentation at recently concluded Apache Big Data Conference Europe about the Reliable Low Level Kafka Spark Consumer I developed and an use case of real time indexing to Apache Blur using this consumer
The document discusses various components of the ELK stack including Elasticsearch, Logstash, Kibana, and how they work together. It provides descriptions of each component, what they are used for, and key features of Kibana such as its user interface, visualization capabilities, and why it is used.
Centralized Logging System Using ELK StackRohit Sharma
Centralized Logging System using ELK Stack
The document discusses setting up a centralized logging system (CLS) using the ELK stack. The ELK stack consists of Logstash to capture and filter logs, Elasticsearch to index and store logs, and Kibana to visualize logs. Logstash agents on each server ship logs to Logstash, which filters and sends logs to Elasticsearch for indexing. Kibana queries Elasticsearch and presents logs through interactive dashboards. A CLS provides benefits like log analysis, auditing, compliance, and a single point of control. The ELK stack is an open-source solution that is scalable, customizable, and integrates with other tools.
The Why and How of HPC-Cloud Hybrids with OpenStack - Lev Lafayette, Universi...OpenStack
Audience Level
Intermediate
Synopsis
High performance computing and cloud computing have traditionally been seen as separate solutions to separate problems, dealing with issues of performance and flexibility respectively. In a diverse research environment however, both sets of compute requirements can occur. In addition to the administrative benefits in combining both requirements into a single unified system, opportunities are provided for incremental expansion.
The deployment of the Spartan cloud-HPC hybrid system at the University of Melbourne last year is an example of such a design. Despite its small size, it has attracted international attention due to its design features. This presentation, in addition to providing a grounding on why one would wish to build an HPC-cloud hybrid system and the results of the deployment, provides a complete technical overview of the design from the ground up, as well as problems encountered and planned future developments.
Speaker Bio
Lev Lafayette is the HPC and Training Officer at the University of Melbourne. Prior to that he worked at the Victorian Partnership for Advanced Computing for several years in a similar role.
- Prashant Agrawal has over 5 years of experience as a Big Data Analyst with expertise in log analytics, search engine solutions, and ETL using tools like Spark, Elasticsearch, Logstash, and Kibana.
- He has strong skills in distributed computing systems like Hadoop, Spark, and working with Hortonworks Data Platform clusters.
- His projects include log analytics and visualization using ELK, data lake modules in Spark, Spark ETL, and developing a big data platform for predictive analysis of system logs.
The document discusses Microsoft's ALM Search service architecture and design. It describes plans for the search indexing and query pipelines, including using Elastic Search for indexing and querying across artifacts. It addresses security, performance, deployment topology, and futures like semantic search and integration with on-premise systems. Key points include indexing millions of files in hours, scaling out the indexing pipeline, and supporting cross-account and public repository search.
Polylog: A Log-Based Architecture for Distributed SystemsLongtail Video
The talk focuses on a log-based architecture ("The Polylog") we've developed to handle data change capture in order to easily build new services and databases based on other service's full datasets. Some of the tools we'll cover include Debezium for database change capture, Kafka for storing the logs, and the Denormalizer, which is an in-house tool we built to do left joins on streams.
Serverless frameworks are changing the way we do computing. In open source container world, Kubernetes is playing a pivotal role in manifesting this. This presentation will go deep into various features of Kubernetes to create serverless functions.
Also includes a comparative study of various serverless frameworks such as Kubeless, Fission and Funktion are available in open source world. Will conclude with an implementation demo and some real world use cases.
Presented in serverless summit 2017: www.inserverless.com
Kubernetes for FaaS (Function as a Service) - Serverless evolution, some basic constructs, kubenetes features, comparisons - from Serverless conference 2017 Bangalore.
This document discusses Scality's experiences building their first Node.js project. It summarizes that the project was building a TiVo-like cloud service for 25 million users, which required high parallelism and throughput of terabytes per second. It also discusses lessons learned around logging performance, optimizing the event loop and buffers, and useful Node.js tools.
This document compares 4 APIs for working with semantic web and RDF in the .NET Framework: SemWeb, ROWLEX, Intellidimension Semantics.SDK, and LinqToRdf. It reviews their storage options, SPARQL support, performance, IDE integration, documentation, and licensing. SemWeb provides the most complete functionality with full SPARQL and storage backends but has poor documentation. Intellidimension and ROWLEX provide good documentation but more limited functionality.
Microservices add complexity to monitoring that was not present with monolithic architectures. While microservices provide benefits, they also introduce significant monitoring challenges around communication between services. Prometheus has emerged as a powerful open source solution for monitoring microservices as it was designed to address issues of scale and flexibility that monitoring microservices requires.
Search Architecture at Evernote: Presented by Christian Kohlschütter, EvernoteLucidworks
Evernote stores over 3 billion notes from over 100 million users worldwide. To improve search performance and allow upgrades to newer Lucene versions, Evernote rearchitected their search system. They separated search code from the data storage, allowed multiple Lucene versions to run concurrently on each machine, and automatically migrated each user's index to the default version without downtime. This reduced disk I/O by 81% and allowed compression techniques to further reduce storage needs by terabytes and input/output by petabytes each week.
Presented on Tuesday, August 7, at the 2018 LRCN (Librarians' Registration Council of Nigeria) National Workshop on Electronic Resource Management Systems in Libraries, held at the University of Nigeria, Nsukka, Enugu State, Nigeria
A presentation at Twitter's official developer conference, Chirp, about why we use the Scala programming language and how we build services in it. Provides a tour of a number of libraries and tools, both developed at Twitter and otherwise.
Scabi is a simple, light-weight Cluster Computing and Storage framework for BigData processing written purely in Java. Scabi provides high performance computing and storage with ease of use. Users can get started on using Scabi within a few minutes. Scabi is free of cost to use. https://www.github.com/dilshadmustafa/scabi
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELijaia
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Road construction is not as easy as it seems to be, it includes various steps and it starts with its designing and
structure including the traffic volume consideration. Then base layer is done by bulldozers and levelers and after
base surface coating has to be done. For giving road a smooth surface with flexibility, Asphalt concrete is used.
Asphalt requires an aggregate sub base material layer, and then a base layer to be put into first place. Asphalt road
construction is formulated to support the heavy traffic load and climatic conditions. It is 100% recyclable and
saving non renewable natural resources.
With the advancement of technology, Asphalt technology gives assurance about the good drainage system and with
skid resistance it can be used where safety is necessary such as outsidethe schools.
The largest use of Asphalt is for making asphalt concrete for road surfaces. It is widely used in airports around the
world due to the sturdiness and ability to be repaired quickly, it is widely used for runways dedicated to aircraft
landing and taking off. Asphalt is normally stored and transported at 150’C or 300’F temperature
Blood finder application project report (1).pdfKamal Acharya
Blood Finder is an emergency time app where a user can search for the blood banks as
well as the registered blood donors around Mumbai. This application also provide an
opportunity for the user of this application to become a registered donor for this user have
to enroll for the donor request from the application itself. If the admin wish to make user
a registered donor, with some of the formalities with the organization it can be done.
Specialization of this application is that the user will not have to register on sign-in for
searching the blood banks and blood donors it can be just done by installing the
application to the mobile.
The purpose of making this application is to save the user’s time for searching blood of
needed blood group during the time of the emergency.
This is an android application developed in Java and XML with the connectivity of
SQLite database. This application will provide most of basic functionality required for an
emergency time application. All the details of Blood banks and Blood donors are stored
in the database i.e. SQLite.
This application allowed the user to get all the information regarding blood banks and
blood donors such as Name, Number, Address, Blood Group, rather than searching it on
the different websites and wasting the precious time. This application is effective and
user friendly.
Tools & Techniques for Commissioning and Maintaining PV Systems W-Animations ...Transcat
Join us for this solutions-based webinar on the tools and techniques for commissioning and maintaining PV Systems. In this session, we'll review the process of building and maintaining a solar array, starting with installation and commissioning, then reviewing operations and maintenance of the system. This course will review insulation resistance testing, I-V curve testing, earth-bond continuity, ground resistance testing, performance tests, visual inspections, ground and arc fault testing procedures, and power quality analysis.
Fluke Solar Application Specialist Will White is presenting on this engaging topic:
Will has worked in the renewable energy industry since 2005, first as an installer for a small east coast solar integrator before adding sales, design, and project management to his skillset. In 2022, Will joined Fluke as a solar application specialist, where he supports their renewable energy testing equipment like IV-curve tracers, electrical meters, and thermal imaging cameras. Experienced in wind power, solar thermal, energy storage, and all scales of PV, Will has primarily focused on residential and small commercial systems. He is passionate about implementing high-quality, code-compliant installation techniques.
A high-Speed Communication System is based on the Design of a Bi-NoC Router, ...DharmaBanothu
The Network on Chip (NoC) has emerged as an effective
solution for intercommunication infrastructure within System on
Chip (SoC) designs, overcoming the limitations of traditional
methods that face significant bottlenecks. However, the complexity
of NoC design presents numerous challenges related to
performance metrics such as scalability, latency, power
consumption, and signal integrity. This project addresses the
issues within the router's memory unit and proposes an enhanced
memory structure. To achieve efficient data transfer, FIFO buffers
are implemented in distributed RAM and virtual channels for
FPGA-based NoC. The project introduces advanced FIFO-based
memory units within the NoC router, assessing their performance
in a Bi-directional NoC (Bi-NoC) configuration. The primary
objective is to reduce the router's workload while enhancing the
FIFO internal structure. To further improve data transfer speed,
a Bi-NoC with a self-configurable intercommunication channel is
suggested. Simulation and synthesis results demonstrate
guaranteed throughput, predictable latency, and equitable
network access, showing significant improvement over previous
designs
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...PriyankaKilaniya
Energy efficiency has been important since the latter part of the last century. The main object of this survey is to determine the energy efficiency knowledge among consumers. Two separate districts in Bangladesh are selected to conduct the survey on households and showrooms about the energy and seller also. The survey uses the data to find some regression equations from which it is easy to predict energy efficiency knowledge. The data is analyzed and calculated based on five important criteria. The initial target was to find some factors that help predict a person's energy efficiency knowledge. From the survey, it is found that the energy efficiency awareness among the people of our country is very low. Relationships between household energy use behaviors are estimated using a unique dataset of about 40 households and 20 showrooms in Bangladesh's Chapainawabganj and Bagerhat districts. Knowledge of energy consumption and energy efficiency technology options is found to be associated with household use of energy conservation practices. Household characteristics also influence household energy use behavior. Younger household cohorts are more likely to adopt energy-efficient technologies and energy conservation practices and place primary importance on energy saving for environmental reasons. Education also influences attitudes toward energy conservation in Bangladesh. Low-education households indicate they primarily save electricity for the environment while high-education households indicate they are motivated by environmental concerns.
Open Channel Flow: fluid flow with a free surfaceIndrajeet sahu
Open Channel Flow: This topic focuses on fluid flow with a free surface, such as in rivers, canals, and drainage ditches. Key concepts include the classification of flow types (steady vs. unsteady, uniform vs. non-uniform), hydraulic radius, flow resistance, Manning's equation, critical flow conditions, and energy and momentum principles. It also covers flow measurement techniques, gradually varied flow analysis, and the design of open channels. Understanding these principles is vital for effective water resource management and engineering applications.
Applications of artificial Intelligence in Mechanical Engineering.pdfAtif Razi
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
Accident detection system project report.pdfKamal Acharya
The Rapid growth of technology and infrastructure has made our lives easier. The
advent of technology has also increased the traffic hazards and the road accidents take place
frequently which causes huge loss of life and property because of the poor emergency facilities.
Many lives could have been saved if emergency service could get accident information and
reach in time. Our project will provide an optimum solution to this draw back. A piezo electric
sensor can be used as a crash or rollover detector of the vehicle during and after a crash. With
signals from a piezo electric sensor, a severe accident can be recognized. According to this
project when a vehicle meets with an accident immediately piezo electric sensor will detect the
signal or if a car rolls over. Then with the help of GSM module and GPS module, the location
will be sent to the emergency contact. Then after conforming the location necessary action will
be taken. If the person meets with a small accident or if there is no serious threat to anyone’s
life, then the alert message can be terminated by the driver by a switch provided in order to
avoid wasting the valuable time of the medical rescue team.
6. 1. Long (grows with the number of nodes)
2. Tedious (which log files to read?)
3. Inaccurate (am I reading the right information?)
4. Cumbersome & complex (how to correlate
events between nodes?)
5. Etc.
Manual Parsing of logs is:
9. 1. Fluentd is an open source data collector for unified logging layer.
2. Fluentd allows you to unify data collection and consumption for a better use and
understanding of data.
3. Deployed as a DaemonSet
a. An OpenShift object which ensures that all nodes run a copy of a pod.
4. The service reads log entries from the /var/log/messages and
/var/log/containers/container.log files or from journal if logging driver is set to journald
Overview of Fluentd
11. The configuration file consists of the following directives:
1. source directives determine the input sources.
2. match directives determine the output destinations.
3. filter directives determine the event processing pipelines.
4. system directives set system wide configuration.
5. label directives group the output and filter for internal routing
6. @include directives include other files.
Overview of Fluentd
13. 1. Elasticsearch is a search server based on Lucene.
2. It provides a distributed, multitenant-capable full-text search engine with a RESTful web
interface and schema-free JSON documents.
Overview of ElasticSearch
14. 1. Easy to scale (Distributed)
2. Everything is one JSON call away (RESTful API)
3. Unleashed power of Lucene under the hood
4. Multi-tenancy
5. Configurable and Extensible
6. Document Oriented
7. Schema free
8. Conflict management
Why ElasticSearch?
15. 1. Cluster
2. Node
3. Index
4. Document
5. Shards
6. Replica
7. SearchGuard
Few Concepts
17. 1. Kibana is the web interface that reads logs entries from the Elasticsearch database.
2. It can create visualization graphs, charts, time tables, and reports, using time-based
and non-time-based events.
3. You can visualize the cluster data, export CSV files, create dashboards, and run
advanced requests.
4. Use the route to access the Kibana web console
Kibana
19. 1. Curator is the service that removes old indexes from Elasticsearch on a per-project basis.
2. The pod reads its configuration from a YAML file structured as follows:
3. For example:
Curator
PROJECT_NAME:
ACTION:
UNIT: VALUE
...
logging-devel:
# Deleteindexesin thelogging-devel project that areolder than oneday.
delete:
days: 1
20. 1. For simple installation, specify the below variable in the ansible inventory file:
2. Use the below playbook to start the installation:
Installation
openshift_logging_install_logging=true
# ansible-playbook -i hosts /usr/share/ansible/openshift-
ansible/playbooks/byo/openshift-cluster/openshift-logging.yml
21. openshift_logging_install_logging=true *1
openshift_hosted_logging_deployer_prefix=registry.lab.example.com:5000/openshift3/ *2
openshift_logging_use_ops=false *3
openshift_logging_kibana_hostname=kibana.apps.lab.example.com *4
openshift_logging_fluentd_memory_limit='128Mi' *5
openshift_logging_es_memory_limit='8Gi' *6
Ansible Variables
1. Set to trueto install logging. Set to falseto uninstall logging.
2. TheURL of thecustom registry for offlinedeployment.
3. Set to trueto configureasecond Elasticsearch cluster and Kibanafor operationslogs.
4. Theexternal host namefor web clientsto reach Kibana.
5. Thememory limit for Fluentd pods.
6. Theamount of RAM to reserveper Elasticsearch instance
22. openshift_logging_es_allow_external=True *1
openshift_logging_es_hostname=elasticsearch.apps.lab.example.com *2
openshift_logging_image_version=latest *3
openshift_hosted_logging_deployer_version=latest *4
openshift_hosted_logging_storage_kind=nfs *5
openshift_hosted_logging_storage_access_modes=['ReadWriteOnce'] *6
Ansible Variables
1. Set to trueto exposeElasticsearch asaroute.
2. Theexternal facing host nameto usefor therouteand theTLSserver certificate.
3. Theimageversion for thelogging imagesto use.
4. Theimageversion for thedeployer imagesto use.
5. Thestorageback end to use.
6. Thevolumeaccessmode.