Istio is an open platform to connect, manage, and secure microservices.
This is presented at Bangalore Docker meetup #35.
https://www.meetup.com/Docker-Bangalore/events/244197013/
Istio is an open platform for providing a service mesh on Kubernetes clusters. It consists of three main components: Envoy proxies that mediate service-to-service communication, Pilot that configures the proxies, and Mixer that enforces policies and collects telemetry data. Istio injects Envoy sidecar proxies into applications so they can provide features like load balancing, authentication, failure recovery, and observability without requiring code changes. This provides a way to manage microservices that is more robust and flexible than using an API gateway alone.
This document provides an overview of service mesh and Istio on Kubernetes. It discusses microservices and the need for visibility, monitoring, and traffic management which a service mesh can provide. It then describes Kubernetes, Istio architecture including Pilot, Envoy proxy, and Mixer components. It covers how Istio provides mutual TLS, ingress/egress traffic routing, request routing to service versions, observability with metrics and tracing, and application resilience through features like timeouts and retries. The document concludes with instructions for deploying Kubernetes and getting started with Istio.
Istio is a service mesh—a modernized service networking layer that provides a transparent and language-independent way to flexibly and easily automate application network functions. Istio is designed to run in a variety of environments: on-premise, cloud-hosted, in Kubernetes containers.
This document discusses Istio, an open source service mesh that provides traffic management, telemetry and security for microservices applications on Kubernetes. It introduces key Istio concepts like the sidecar proxy Envoy, the control plane components Pilot, Mixer and Citadel, and how they work together to provide service discovery, load balancing, failure recovery, access control and other capabilities across microservices. The presentation concludes with an offer to demonstrate Istio's features in more depth.
CI:CD in Lightspeed with kubernetes and argo cdBilly Yuen
Enterprises have benefited greatly from the elastic scalability and multi-region availability by moving to AWS, but the fundamental deployment model remains the same.
At Intuit, we have adopted k8s as our new saas platform and re-invented our CI/CD pipeline to take full advantage of k8s. In this presentation, we will discuss our journey from Spinnaker to Argo CD.
1. Reduce CI/CD time from 60 minutes to 10 minutes.
2. Reduce production release (or rollback) from 10 minutes to 2 minutes.
3. Enable concurrent deployment using spinnaker and argo cd as HA/DR to safely adopt the new platform with no downtime.
4. Be compatible with the existing application monitoring toolset.
An in depth overview of Kubernetes and it's various components.
NOTE: This is a fixed version of a previous presentation (a draft was uploaded with some errors)
Kubecost provides real-time cost visibility and insights for teams using Kubernetes, helping you continuously reduce your cloud costs. Infracost shows cloud cost estimates for Terraform. It lets DevOps, SRE and engineers see a cost breakdown and understand costs before making changes, either in the terminal or pull requests.
The document discusses Istio, an open source service mesh that provides traffic management, service migration and monitoring for microservices. It provides an overview of key Istio concepts like the control plane, data plane and components like Envoy, Pilot and Mixer. It also includes steps to install Istio on GKE and deploy a sample Bookinfo application to demonstrate traffic routing and load balancing capabilities.
Kubernetes is an open source container orchestration system that automates the deployment, maintenance, and scaling of containerized applications. It groups related containers into logical units called pods and handles scheduling pods onto nodes in a compute cluster while ensuring their desired state is maintained. Kubernetes uses concepts like labels and pods to organize containers that make up an application for easy management and discovery.
In this session, we will discuss the architecture of a Kubernetes cluster. we will go through all the master and worker components of a kubernetes cluster. We will also discuss the basic terminology of Kubernetes cluster such as Pods, Deployments, Service etc. We will also cover networking inside Kuberneets. In the end, we will discuss options available for the setup of a Kubernetes cluster.
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.
We are more than thrilled to announce the second meetup on 10 December 2022 where we discuss GitOps, ArgoCD and their fundamentals. Inviting SREs, DevOps engineers, developers & platform engineers from all around the world.
Agenda:-
1. GitOps Overview
2. Why and What is GitOps
3. Opensource GitOps tools
4. What is ArgoCD, Architecture
5. Let's Get our hands dirty on ArgoCD
6. Q&A
This document provides an overview of Kubernetes including:
- Kubernetes is an open source system for managing containerized applications and services across clusters of hosts. It provides tools to deploy, maintain, and scale applications.
- Kubernetes objects include pods, services, deployments, jobs, and others to define application components and how they relate.
- The Kubernetes architecture consists of a control plane running on the master including the API server, scheduler and controller manager. Nodes run the kubelet and kube-proxy to manage pods and services.
- Kubernetes can be deployed on AWS using tools like CloudFormation templates to automate cluster creation and management for high availability and scalability.
Microservices, Containers and Docker
This document provides an overview of microservices, containers, and Docker. It begins by defining microservices as an architectural style where applications are composed of independent, interchangeable components. It discusses benefits of the microservices style such as independent deployability, efficient scaling, and design autonomy. The document then introduces containers as a way to package applications and their dependencies to run uniformly across various environments. It compares containers to virtual machines. Finally, it describes Docker as an open source tool that automates deployment of applications into containers, providing portability and management of containers. The document concludes by discussing the need for container orchestration at scale.
Traditional virtualization technologies have been used by cloud infrastructure providers for many years in providing isolated environments for hosting applications. These technologies make use of full-blown operating system images for creating virtual machines (VMs). According to this architecture, each VM needs its own guest operating system to run application processes. More recently, with the introduction of the Docker project, the Linux Container (LXC) virtualization technology became popular and attracted the attention. Unlike VMs, containers do not need a dedicated guest operating system for providing OS-level isolation, rather they can provide the same level of isolation on top of a single operating system instance.
An enterprise application may need to run a server cluster to handle high request volumes. Running an entire server cluster on Docker containers, on a single Docker host could introduce the risk of single point of failure. Google started a project called Kubernetes to solve this problem. Kubernetes provides a cluster of Docker hosts for managing Docker containers in a clustered environment. It provides an API on top of Docker API for managing docker containers on multiple Docker hosts with many more features.
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.
The presentation from our online webinar "Design patterns for microservice architecture".
Full video from webinar available here: https://www.youtube.com/watch?v=826aAmG06KM
If you’re a CTO or a Lead Developer and you’re planning to design service-oriented architecture, it’s definitely a webinar tailored to your needs. Adrian Zmenda, our Lead Dev, will explain:
- when microservice architecture is a safe bet and what are some good alternatives
- what are the pros and cons of the most popular design patterns (API Gateway, Backend for Frontend and more)
- how to ensure that the communication between services is done right and what to do in case of connection issues
- why we’ve decided to use a monorepo (monolithic repository)
- what we’ve learned from using the remote procedure call framework gRPC
- how to monitor the efficiency of individual services and whole SOA-based systems.
Istio is a service mesh, and it's a cool new project from Google, IBM, Lyft and others. This talk describes at a high level how Istio works as a sidecar, and how it works great with Weave Cloud, which provides visualization to understand what's going on when you deploy Istio, and long-term Prometheus metrics storage with its built-in Prometheus service.
This is a small introduction to microservices. you can find the differences between microservices and monolithic applications. You will find the pros and cons of microservices. you will also find the challenges (Business/ technical) that you may face while implementing microservices.
Observability in Java: Getting Started with OpenTelemetryDevOps.com
Our software is more complex than ever: applications must be reliable, predictable, and easy to use to meet modern expectations. As developers, this means our responsibilities have grown while the things we can control have stayed the same. In order to better understand our systems and create truly modern software, we need observability.
This workshop will walk through what observability means for Java developers and how to achieve it in our systems with the least amount of work using the open source observability project OpenTelemetry.
Service Mesh with Apache Kafka, Kubernetes, Envoy, Istio and LinkerdKai Wähner
Microservice architectures are not free lunch! Microservices need to be decoupled, flexible, operationally transparent, data aware and elastic. Most material from last years only discusses point-to-point architectures with inflexible and non-scalable technologies like REST / HTTP. This video takes a look at cutting edge technologies like Apache Kafka, Kubernetes, Envoy, Linkerd and Istio to implement a cloud-native service mesh to solve these challenges and bring microservices to the next level of scale, speed and efficiency.
Key takeaways:
- Apache Kafka decouples services, including event streams and request-response
- Kubernetes provides a cloud-native infrastructure for the Kafka ecosystem
- Service Mesh helps with security and observability at ecosystem / organization scale
- Envoy and Istio sit in the layer above Kafka and are orthogonal to the goals Kafka addresses
Blog post: http://www.kai-waehner.de/blog/2019/09/24/cloud-native-apache-kafka-kubernetes-envoy-istio-linkerd-service-mesh
Video recording of this slide deck: https://youtu.be/Us_C4RFOUrA
OpenTelemetry is a set of APIs, SDKs, tooling and integrations that are designed for the creation and management of telemetry data such as traces, metrics, and logs. It aims to enable effective observability by making high-quality, portable telemetry ubiquitous and vendor-agnostic. The OpenTelemetry Collector is an independent process that acts as a "universal agent" to collect, process, and export telemetry data in a highly performant and stable manner, supporting multiple types of telemetry through customizable pipelines consisting of receivers, processors, and exporters.
Kubernetes: A Short Introduction (2019)Megan O'Keefe
Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery called pods. Kubernetes can manage pods across a cluster of machines, providing scheduling, deployment, scaling, load balancing, volume mounting and networking. It is widely used by companies like Google, CERN and in large projects like processing images and analyzing particle interactions. Kubernetes is portable, can span multiple cloud providers, and continues growing to support new workloads and use cases.
ArgoCD is a Continuous Delivery and Deployment tool based on GitOps principles. It helps to automate deployment to Kubernetes cluster from github. We will look into how to adopt and use argoCD for continuous deployment.
Managing Microservices traffic using IstioArun prasath
This document summarizes managing microservices traffic using Istio. It discusses the challenges of managing microservices like traffic management, observability, and security. It then introduces Istio as an open platform that provides traffic management, policy enforcement, metrics, logs, traces, and security for microservices without requiring code changes. It describes Istio's architecture including Pilot and Mixer and how to install Istio on Kubernetes. Finally, it outlines some of Istio's key capabilities like traffic management, policy enforcement, and collecting metrics, logs, and traces.
This webinar discusses moving from monolithic applications to microservices architectures. The speakers are Dimitris Moraitis from Mist.io and DeWayne Filppi from Cloudify. The agenda includes why organizations adopt microservices, architecture principles, and a case study of Mist.io's migration to microservices and Kubernetes. Mist.io saw benefits including 50% reduced costs, improved scalability and reliability, and streamlined development and testing. The webinar concludes with demonstrations and a question and answer session.
Kubecost provides real-time cost visibility and insights for teams using Kubernetes, helping you continuously reduce your cloud costs. Infracost shows cloud cost estimates for Terraform. It lets DevOps, SRE and engineers see a cost breakdown and understand costs before making changes, either in the terminal or pull requests.
The document discusses Istio, an open source service mesh that provides traffic management, service migration and monitoring for microservices. It provides an overview of key Istio concepts like the control plane, data plane and components like Envoy, Pilot and Mixer. It also includes steps to install Istio on GKE and deploy a sample Bookinfo application to demonstrate traffic routing and load balancing capabilities.
Kubernetes is an open source container orchestration system that automates the deployment, maintenance, and scaling of containerized applications. It groups related containers into logical units called pods and handles scheduling pods onto nodes in a compute cluster while ensuring their desired state is maintained. Kubernetes uses concepts like labels and pods to organize containers that make up an application for easy management and discovery.
In this session, we will discuss the architecture of a Kubernetes cluster. we will go through all the master and worker components of a kubernetes cluster. We will also discuss the basic terminology of Kubernetes cluster such as Pods, Deployments, Service etc. We will also cover networking inside Kuberneets. In the end, we will discuss options available for the setup of a Kubernetes cluster.
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.
We are more than thrilled to announce the second meetup on 10 December 2022 where we discuss GitOps, ArgoCD and their fundamentals. Inviting SREs, DevOps engineers, developers & platform engineers from all around the world.
Agenda:-
1. GitOps Overview
2. Why and What is GitOps
3. Opensource GitOps tools
4. What is ArgoCD, Architecture
5. Let's Get our hands dirty on ArgoCD
6. Q&A
This document provides an overview of Kubernetes including:
- Kubernetes is an open source system for managing containerized applications and services across clusters of hosts. It provides tools to deploy, maintain, and scale applications.
- Kubernetes objects include pods, services, deployments, jobs, and others to define application components and how they relate.
- The Kubernetes architecture consists of a control plane running on the master including the API server, scheduler and controller manager. Nodes run the kubelet and kube-proxy to manage pods and services.
- Kubernetes can be deployed on AWS using tools like CloudFormation templates to automate cluster creation and management for high availability and scalability.
Microservices, Containers and Docker
This document provides an overview of microservices, containers, and Docker. It begins by defining microservices as an architectural style where applications are composed of independent, interchangeable components. It discusses benefits of the microservices style such as independent deployability, efficient scaling, and design autonomy. The document then introduces containers as a way to package applications and their dependencies to run uniformly across various environments. It compares containers to virtual machines. Finally, it describes Docker as an open source tool that automates deployment of applications into containers, providing portability and management of containers. The document concludes by discussing the need for container orchestration at scale.
Traditional virtualization technologies have been used by cloud infrastructure providers for many years in providing isolated environments for hosting applications. These technologies make use of full-blown operating system images for creating virtual machines (VMs). According to this architecture, each VM needs its own guest operating system to run application processes. More recently, with the introduction of the Docker project, the Linux Container (LXC) virtualization technology became popular and attracted the attention. Unlike VMs, containers do not need a dedicated guest operating system for providing OS-level isolation, rather they can provide the same level of isolation on top of a single operating system instance.
An enterprise application may need to run a server cluster to handle high request volumes. Running an entire server cluster on Docker containers, on a single Docker host could introduce the risk of single point of failure. Google started a project called Kubernetes to solve this problem. Kubernetes provides a cluster of Docker hosts for managing Docker containers in a clustered environment. It provides an API on top of Docker API for managing docker containers on multiple Docker hosts with many more features.
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.
The presentation from our online webinar "Design patterns for microservice architecture".
Full video from webinar available here: https://www.youtube.com/watch?v=826aAmG06KM
If you’re a CTO or a Lead Developer and you’re planning to design service-oriented architecture, it’s definitely a webinar tailored to your needs. Adrian Zmenda, our Lead Dev, will explain:
- when microservice architecture is a safe bet and what are some good alternatives
- what are the pros and cons of the most popular design patterns (API Gateway, Backend for Frontend and more)
- how to ensure that the communication between services is done right and what to do in case of connection issues
- why we’ve decided to use a monorepo (monolithic repository)
- what we’ve learned from using the remote procedure call framework gRPC
- how to monitor the efficiency of individual services and whole SOA-based systems.
Istio is a service mesh, and it's a cool new project from Google, IBM, Lyft and others. This talk describes at a high level how Istio works as a sidecar, and how it works great with Weave Cloud, which provides visualization to understand what's going on when you deploy Istio, and long-term Prometheus metrics storage with its built-in Prometheus service.
This is a small introduction to microservices. you can find the differences between microservices and monolithic applications. You will find the pros and cons of microservices. you will also find the challenges (Business/ technical) that you may face while implementing microservices.
Observability in Java: Getting Started with OpenTelemetryDevOps.com
Our software is more complex than ever: applications must be reliable, predictable, and easy to use to meet modern expectations. As developers, this means our responsibilities have grown while the things we can control have stayed the same. In order to better understand our systems and create truly modern software, we need observability.
This workshop will walk through what observability means for Java developers and how to achieve it in our systems with the least amount of work using the open source observability project OpenTelemetry.
Service Mesh with Apache Kafka, Kubernetes, Envoy, Istio and LinkerdKai Wähner
Microservice architectures are not free lunch! Microservices need to be decoupled, flexible, operationally transparent, data aware and elastic. Most material from last years only discusses point-to-point architectures with inflexible and non-scalable technologies like REST / HTTP. This video takes a look at cutting edge technologies like Apache Kafka, Kubernetes, Envoy, Linkerd and Istio to implement a cloud-native service mesh to solve these challenges and bring microservices to the next level of scale, speed and efficiency.
Key takeaways:
- Apache Kafka decouples services, including event streams and request-response
- Kubernetes provides a cloud-native infrastructure for the Kafka ecosystem
- Service Mesh helps with security and observability at ecosystem / organization scale
- Envoy and Istio sit in the layer above Kafka and are orthogonal to the goals Kafka addresses
Blog post: http://www.kai-waehner.de/blog/2019/09/24/cloud-native-apache-kafka-kubernetes-envoy-istio-linkerd-service-mesh
Video recording of this slide deck: https://youtu.be/Us_C4RFOUrA
OpenTelemetry is a set of APIs, SDKs, tooling and integrations that are designed for the creation and management of telemetry data such as traces, metrics, and logs. It aims to enable effective observability by making high-quality, portable telemetry ubiquitous and vendor-agnostic. The OpenTelemetry Collector is an independent process that acts as a "universal agent" to collect, process, and export telemetry data in a highly performant and stable manner, supporting multiple types of telemetry through customizable pipelines consisting of receivers, processors, and exporters.
Kubernetes: A Short Introduction (2019)Megan O'Keefe
Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery called pods. Kubernetes can manage pods across a cluster of machines, providing scheduling, deployment, scaling, load balancing, volume mounting and networking. It is widely used by companies like Google, CERN and in large projects like processing images and analyzing particle interactions. Kubernetes is portable, can span multiple cloud providers, and continues growing to support new workloads and use cases.
ArgoCD is a Continuous Delivery and Deployment tool based on GitOps principles. It helps to automate deployment to Kubernetes cluster from github. We will look into how to adopt and use argoCD for continuous deployment.
Managing Microservices traffic using IstioArun prasath
This document summarizes managing microservices traffic using Istio. It discusses the challenges of managing microservices like traffic management, observability, and security. It then introduces Istio as an open platform that provides traffic management, policy enforcement, metrics, logs, traces, and security for microservices without requiring code changes. It describes Istio's architecture including Pilot and Mixer and how to install Istio on Kubernetes. Finally, it outlines some of Istio's key capabilities like traffic management, policy enforcement, and collecting metrics, logs, and traces.
This webinar discusses moving from monolithic applications to microservices architectures. The speakers are Dimitris Moraitis from Mist.io and DeWayne Filppi from Cloudify. The agenda includes why organizations adopt microservices, architecture principles, and a case study of Mist.io's migration to microservices and Kubernetes. Mist.io saw benefits including 50% reduced costs, improved scalability and reliability, and streamlined development and testing. The webinar concludes with demonstrations and a question and answer session.
This document provides an overview of JavaScript for enterprise applications. It discusses why JavaScript has a reputation for being weak and dynamic, and responses to common accusations about JavaScript. It also covers JavaScript paradigms like structured programming, object-oriented programming, functional programming, and event-driven programming. Additionally, it summarizes Node.js runtime, ES6 features, generators, Ramda.js, communicating sequential processes, Koa.js, PM2 process manager, and building hybrid mobile apps with Cordova.
Migrating from oracle soa suite to microservices on kubernetesKonveyor Community
Watch presentation recording: https://youtu.be/cxH6WjDZc2c
In this session, we’ll explore how Randoli helped a Postal Technology company migrate their payment gateway applications off Oracle SOA Suite to Camel/Springboot on Kubernetes.
The primary drivers for the migration were: move to cloud-native technologies in keeping with the organizational digital transformation mandate; move away from an outdated centralized platform to a decentralized architecture for efficiency, scalability, and manageability; and very high licensing costs of the existing platform.
We’ll discuss:
- The high-level approach we took during the migration including architecture and design decisions.
- How we used Camel/Springboot to implement the services.
- Why and how we used Drools for implementing business rules.
- The test-driven approach using Camel testing framework and how it helped reduce issues.
- CI/CD and build process on Kubernetes.
- How we tackled logging, monitoring, and tracing challenges.
Presenter: Rajith Attapattu, Managing Partner & CTO @ Randoli Inc.
A presentation to explain the microservices architecture, the pro and the cons, with a view on how to migrate from a monolith to a SOA architecture. Also, we'll show the benefits of the microservices architecture also for the frontend side with the microfrontend architecture.
A presentation on clearly defining a microservice architecture, culture, and discovering how to determine whether it is a step in the right direction for your system. I discuss about the decisions that lead us to take on a microservice architecture approach at Sprout, and the challenges we are facing as a startup learning a new method for making apps.
Viktor Turskyi "Effective NodeJS Application Development"Fwdays
For 15 years in development, I managed to take part in the creation of a large number of various projects. I have already made a number of talks on the working architecture of Web applications, but this is only part of the efficient development puzzle. We will consider the whole process from the start of the project to its launch in production. I’ll tell you how we approach the ideas of the “12 Factor App”, how we use the docker, discuss environment deployment issues, security issues, testing issues, discuss the nuances of SDLC and much more.
This document provides an overview of Kubernetes and microservices architectures. It discusses the differences between monolithic and microservices applications and the advantages and disadvantages of each. It then introduces Kubernetes, including its origins at Google, components like the master, nodes, and objects. It covers management techniques like imperative commands, imperative object configuration, and declarative object configuration. Finally, it discusses key Kubernetes concepts like pods, services, and deployments. It also compares manually hosting a Kubernetes cluster to using Azure Kubernetes Service.
This document provides an overview of Azure Dev Spaces, which allows developers to share an Azure Kubernetes Service (AKS) cluster for building and testing applications. It discusses challenges with manually hosting Kubernetes clusters and benefits of AKS, which simplifies Kubernetes deployment and management. Azure Dev Spaces enables developers to test code end-to-end on an AKS cluster without needing to replicate or simulate dependencies. It also allows easy onboarding of new team members with minimal machine setup required. The document concludes with a demonstration of Azure Dev Spaces.
1. Microservices architecture breaks down an application into isolated, collaborating services that communicate with each other. This allows for independent scaling and technology choices for each service.
2. Reasons for the rise of microservices include the startup boom in the late 2000s, growth of cloud services, and increased comfort with distributed systems.
3. Examples of applications that can benefit from a microservices architecture include online shopping sites, food delivery apps, and laundry services, by decomposing them into independent services like product info, pricing, orders, inventory, and reviews.
Network Automation Journey, A systems engineer NetOps perspectiveWalid Shaari
Network devices play a crucial role; they are not just in the Data Center. It's the Wifi, VOIP, WAN and recently underlays and overlays. Network teams are essential for operations. It's about time we highlight to the configuration management community the importance of Network teams and include them in our discussions. This talk describes the personal experience of systems engineer on how to kickstart a network team into automation. Most importantly, how and where to start, challenges faced, and progress made. The network team in question uses multi-vendor network devices in a large traditional enterprise.
NetDevOps, we do not hear that term as frequent as we should. Every time we hear about automation, or configuration management, it is usually the application, if not, it is the systems that host the applications. How about the network systems and devices that interconnect and protects our services? This talk aims to describe the journey a systems engineer had as part of an automation assignment with the network management team. Building from lessons learned and challenges faced with system automation, how one can kickstart an automation project and gain small wins quickly. Where and how to start the journey? What to avoid? What to prioritise? How to overcome the lack of network skills for the automation engineer and lack of automation and Linux/Unix skills for network engineers. What challenges were faced and how to overcome them? What fights to give up? Where do I see network automation and configuration management as a systems engineer? What are the status quo and future expectations?
Microservices , Docker , CI/CD , Kubernetes Seminar - Sri Lanka Mario Ishara Fernando
This document discusses microservices and containers. It provides an overview of microservices architecture compared to monolithic architecture, highlighting that microservices are composed of many small, independent services with separate deployments and databases. It then discusses containers and how Docker is used to package and run applications in isolated containers. Finally, it introduces Kubernetes as a container orchestration system to manage and scale multiple containerized applications across a cluster of machines.
Netflix Container Scheduling and Execution - QCon New York 2016aspyker
Scheduling a Fuller House: Container Management At Netflix
Customers from over all over the world streamed Forty Two Billion hours of Netflix content last year. Various Netflix batch jobs and an increasing number of service applications use containers for their processing. In this talk Netflix will present a deep dive on the motivations and the technology powering container deployment on top of the AWS EC2 service. The talk will cover our approach to cloud resource management and scheduling with the open source Fenzo library, along with details on docker execution engine as a part of project Titus. As well, the talk will share some of the results so far, lessons learned, and end with a brief look at the developer experience for containers.
This document discusses monolithic architectures and microservices architectures. It begins with an overview of what monoliths and microservices are. It then discusses some common issues with monoliths like lack of scalability and difficulty of changes. It provides examples of when monoliths may still be preferable and signs of a well-designed monolith. It then discusses microservices in more detail and their pros and cons. Two case studies are presented for gradually migrating parts of a monolith to microservices through either a phased or "big bang" approach. Distributed systems challenges are also covered. The document concludes by recommending starting with monoliths and refactoring later as needs dictate.
2017 Microservices Practitioner Virtual Summit: Microservices at Squarespace ...Ambassador Labs
This talk covers the past, present, and future of Microservices at Squarespace. We begin with our journey to microservices, and describe the platform that made this possible. We introduce our idea of the “Pillars of Microservices”, everything a developer needs to have a successful production service. For each pillar we describe why we think it is important and discuss the implementation and how we utilize it in our environment. Next, we look to the future evolution of our microservices environment including how we are using containerization and Kubernetes to overcome some of the problems we’ve faced with more static infrastructure.
This document discusses microservices architecture and its application to libraries. It begins by defining microservices and noting that libraries can benefit from a microservices approach to allow for increased innovation. It then covers traditional monolithic architectures and some of their limitations for scaling. The remainder of the document discusses moving from monolithic to microservices, including using containerization and DevOps practices. It provides examples of how microservices were used for complex workflows like audio/video ingest. It also covers testing, deployment strategies, security considerations and integrating microservices with existing systems.
Ledingkart Meetup #1: Monolithic to microservices in actionMukesh Singh
This document summarizes a talk about moving from a monolithic architecture to microservices. It discusses what microservices are, examples of large companies that adopted microservices like Amazon and Netflix, and the monolithic problems at Lendingkart. It then describes how Lendingkart broke up its monolith into multiple microservices for different functions. Some challenges of microservices like distributed tracing and increased operations overhead are also outlined. Best practices for adopting microservices like incremental adoption and clear interfaces are also provided.
[WSO2Con Asia 2018] Microservices, Containers, and BeyondWSO2
Microservices, containers, and serverless technologies can help build scalable distributed systems. Microservices break applications into independently deployable components organized around business capabilities. Containers provide isolation and repeatability. Kubernetes orchestrates groups of containers into pods and services. Service meshes like Istio help govern microservices through sidecar proxies. Serverless platforms automate resource management so code runs without servers. Knative in particular helps scale microservices to zero or many instances.
Log analysis challenges include searching logs across multiple services and servers. The ELK stack provides a solution with Logstash to centralize log collection, Elasticsearch for storage and search, and Kibana for visualization. Logstash uses input, filter, and output plugins to collect, parse, and forward logs. Example configurations show using stdin and filters to parse OpenStack logs before outputting to Elasticsearch and Kibana for analysis and dashboards.
Heat is an OpenStack template-based orchestration service that allows users to describe infrastructure and applications in text files called Heat Orchestration Templates (HOT) and automate the deployment of multi-component, multi-tier applications across OpenStack and other platforms. Heat provides the ability to define infrastructure resources like servers, networks, routers, and security groups and specify relationships between resources. It comprises several Python applications that work together to provision and manage OpenStack resources through a REST API according to the templates.
Docker - Demo on PHP Application deployment Arun prasath
Docker is an open-source project to easily create lightweight, portable, self-sufficient containers from any application. The same container that a developer builds and tests on a laptop can run at scale, in production, on VMs, bare metal, OpenStack clusters, public clouds and more.
In this demo, I will show how to build a Apache image from a Dockerfile and deploy a PHP application which is present in an external folder using custom configuration files.
HP CloudSystem Matrix is Infrastructure-as-a-Service (IaaS) for private and hybrid cloud environments, allowing users to provision infrastructure in minutes for physical and virtual. This offering includes a self-service infrastructure portal for quick auto-provisioning, along with built-in lifecycle management to optimize infrastructure, manage the resource pools, and help ensure uptime. Using included Cloud APIs, you can easily customize the operating environment to your specific requirements, enabling chargeback and billing integration, integration into approval processes, and other process automation tasks. Matrix is integrated by design with broad support of heterogeneous environments, and it offers cloud-bursting to a variety of public cloud providers including HP Cloud Services. The core elements of a CloudSystem Matrix solution are:
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ARCHITECTING TENANT BASED QOS IN MULTI-TENANT CLOUD PLATFORMSArun prasath
Achieving QOS in a multi-tenant cloud platforms is still a difficult task and many companies follow different approaches to solve this problem. Here in this document I tried architecting a simple solution for achieving different QOS for different tenants in a Multi-tenant cloud environment based on my experiments with containers , docker and cgroup on Openstack.
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The document provides a software requirements specification for a toll application. It includes sections on introduction, overall description, and specific requirements. The introduction describes the methodology, purpose, scope and overview of the toll application. The overall description covers the product perspective, functions, interfaces, users, constraints, architecture and use case model. The specific requirements section details use case reports, activity diagrams and sequence diagrams. The toll application is meant to enable automatic payment at toll gates by tracking a user's GPS location and deducting payment when they cross virtual toll fences.
This document describes a toll application that allows automatic payment of tolls using a mobile phone. The application allows users to register identities online, install an Android app, and purchase credits. When the app detects the user crossing a toll fence via GPS, funds are automatically deducted from the user's account. The proposed system eliminates physical toll booths and allows borderless travel. The document outlines the existing toll collection system, proposed toll application modules and interfaces, workflow, and concludes with potential future enhancements.
Not So Common Memory Leaks in Java WebinarTier1 app
This SlideShare presentation is from our May webinar, “Not So Common Memory Leaks & How to Fix Them?”, where we explored lesser-known memory leak patterns in Java applications. Unlike typical leaks, subtle issues such as thread local misuse, inner class references, uncached collections, and misbehaving frameworks often go undetected and gradually degrade performance. This deck provides in-depth insights into identifying these hidden leaks using advanced heap analysis and profiling techniques, along with real-world case studies and practical solutions. Ideal for developers and performance engineers aiming to deepen their understanding of Java memory management and improve application stability.
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Adobe Lightroom Classic is a desktop-based software application for editing and managing digital photos. It focuses on providing users with a powerful and comprehensive set of tools for organizing, editing, and processing their images on their computer. Unlike the newer Lightroom, which is cloud-based, Lightroom Classic stores photos locally on your computer and offers a more traditional workflow for professional photographers.
Here's a more detailed breakdown:
Key Features and Functions:
Organization:
Lightroom Classic provides robust tools for organizing your photos, including creating collections, using keywords, flags, and color labels.
Editing:
It offers a wide range of editing tools for making adjustments to color, tone, and more.
Processing:
Lightroom Classic can process RAW files, allowing for significant adjustments and fine-tuning of images.
Desktop-Focused:
The application is designed to be used on a computer, with the original photos stored locally on the hard drive.
Non-Destructive Editing:
Edits are applied to the original photos in a non-destructive way, meaning the original files remain untouched.
Key Differences from Lightroom (Cloud-Based):
Storage Location:
Lightroom Classic stores photos locally on your computer, while Lightroom stores them in the cloud.
Workflow:
Lightroom Classic is designed for a desktop workflow, while Lightroom is designed for a cloud-based workflow.
Connectivity:
Lightroom Classic can be used offline, while Lightroom requires an internet connection to sync and access photos.
Organization:
Lightroom Classic offers more advanced organization features like Collections and Keywords.
Who is it for?
Professional Photographers:
PCMag notes that Lightroom Classic is a popular choice among professional photographers who need the flexibility and control of a desktop-based application.
Users with Large Collections:
Those with extensive photo collections may prefer Lightroom Classic's local storage and robust organization features.
Users who prefer a traditional workflow:
Users who prefer a more traditional desktop workflow, with their original photos stored on their computer, will find Lightroom Classic a good fit.
This presentation explores code comprehension challenges in scientific programming based on a survey of 57 research scientists. It reveals that 57.9% of scientists have no formal training in writing readable code. Key findings highlight a "documentation paradox" where documentation is both the most common readability practice and the biggest challenge scientists face. The study identifies critical issues with naming conventions and code organization, noting that 100% of scientists agree readable code is essential for reproducible research. The research concludes with four key recommendations: expanding programming education for scientists, conducting targeted research on scientific code quality, developing specialized tools, and establishing clearer documentation guidelines for scientific software.
Presented at: The 33rd International Conference on Program Comprehension (ICPC '25)
Date of Conference: April 2025
Conference Location: Ottawa, Ontario, Canada
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Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)Andre Hora
Exceptions allow developers to handle error cases expected to occur infrequently. Ideally, good test suites should test both normal and exceptional behaviors to catch more bugs and avoid regressions. While current research analyzes exceptions that propagate to tests, it does not explore other exceptions that do not reach the tests. In this paper, we provide an empirical study to explore how frequently exceptional behaviors are tested in real-world systems. We consider both exceptions that propagate to tests and the ones that do not reach the tests. For this purpose, we run an instrumented version of test suites, monitor their execution, and collect information about the exceptions raised at runtime. We analyze the test suites of 25 Python systems, covering 5,372 executed methods, 17.9M calls, and 1.4M raised exceptions. We find that 21.4% of the executed methods do raise exceptions at runtime. In methods that raise exceptions, on the median, 1 in 10 calls exercise exceptional behaviors. Close to 80% of the methods that raise exceptions do so infrequently, but about 20% raise exceptions more frequently. Finally, we provide implications for researchers and practitioners. We suggest developing novel tools to support exercising exceptional behaviors and refactoring expensive try/except blocks. We also call attention to the fact that exception-raising behaviors are not necessarily “abnormal” or rare.
Why Orangescrum Is a Game Changer for Construction Companies in 2025Orangescrum
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Maxon Cinema 4D 2025 is the latest version of the Maxon's 3D software, released in September 2024, and it builds upon previous versions with new tools for procedural modeling and animation, as well as enhancements to particle, Pyro, and rigid body simulations. CG Channel also mentions that Cinema 4D 2025.2, released in April 2025, focuses on spline tools and unified simulation enhancements.
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Boolean System: Modernized boolean system for precise 3D modeling.
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Learning Panel: Intuitive learning panel for new users.
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In essence, Cinema 4D 2025 is a major update that provides artists with more powerful tools and workflows for creating 3D content, particularly in the fields of motion graphics, VFX, and visualization.
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Here's a more detailed explanation:
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Explaining GitHub Actions Failures with Large Language Models Challenges, In...ssuserb14185
GitHub Actions (GA) has become the de facto tool that developers use to automate software workflows, seamlessly building, testing, and deploying code. Yet when GA fails, it disrupts development, causing delays and driving up costs. Diagnosing failures becomes especially challenging because error logs are often long, complex and unstructured. Given these difficulties, this study explores the potential of large language models (LLMs) to generate correct, clear, concise, and actionable contextual descriptions (or summaries) for GA failures, focusing on developers’ perceptions of their feasibility and usefulness. Our results show that over 80% of developers rated LLM explanations positively in terms of correctness for simpler/small logs. Overall, our findings suggest that LLMs can feasibly assist developers in understanding common GA errors, thus, potentially reducing manual analysis. However, we also found that improved reasoning abilities are needed to support more complex CI/CD scenarios. For instance, less experienced developers tend to be more positive on the described context, while seasoned developers prefer concise summaries. Overall, our work offers key insights for researchers enhancing LLM reasoning, particularly in adapting explanations to user expertise.
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Join Ajay Sarpal and Miray Vu to learn about key Marketo Engage enhancements. Discover improved in-app Salesforce CRM connector statistics for easy monitoring of sync health and throughput. Explore new Salesforce CRM Synch Dashboards providing up-to-date insights into weekly activity usage, thresholds, and limits with drill-down capabilities. Learn about proactive notifications for both Salesforce CRM sync and product usage overages. Get an update on improved Salesforce CRM synch scale and reliability coming in Q2 2025.
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Mastering Fluent Bit: Ultimate Guide to Integrating Telemetry Pipelines with ...Eric D. Schabell
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Landscape of Requirements Engineering for/by AI through Literature ReviewHironori Washizaki
Hironori Washizaki, "Landscape of Requirements Engineering for/by AI through Literature Review," RAISE 2025: Workshop on Requirements engineering for AI-powered SoftwarE, 2025.
1. Istio
Arun Prasath
Senior Operations Engineer
Endurance International Group
@ bingoarun
@ bingoarunprasath
Docker meetup #35
Bangalore
November 25, 2017
@ bingoarun
2. A bit of history...
● Monolithic applications
● Hard to deploy
● Hard to manage
● Hard to scale
● Mostly deployed on a hardware
● Hard to solve bottleneck issues
3. Example - Bookinfo application
Product page
Details Reviews
Ratings
One single linux process (behind tomcat or httpd)
4. Migrating to cloud – The wrong way
Openstack VM / EC2 / GCE instance
One big VM
5. Migrating to the cloud – The correct way
Load balancer
Multiple small Cloud VMs based on need
Better than running on hardware or one big VM. Still not very
efficient..
Product page
Details Reviews
Ratings
6. Kubernetes to the rescue
Kubernetes master
node
Worker node Worker node Worker node
7. But things get complex...
More applications on Kubernetes, varying workloads different needs...
Worker node Worker node Worker node
9. Istio
● An open platform to connect, manage, and
secure microservices.
● Istio provides an easy way to create a network
of deployed services with load balancing,
service-to-service authentication, monitoring,
and more, without requiring any changes in
service code.
21. Metrics Logs and Traces
● Distributed Tracing
● Collecting Metrics and Logs
● Collecting Metrics for TCP services
● Querying Metrics from Prometheus
● Visualizing Metrics with Grafana
● Generating a Service Graph
#11: Why Envoy proxy ?
Middle proxy is not very suitable for retries, not much client side benefits..
Control over source and destination
Envoy programmed from control plane - yaml