Exploring the debugging and profiling tools for AWS Lambda. We use the v8-profiler for NodeJS with IOpipe to see deep into a serverless application and trace function calls. https://www.iopipe.com
This is a Lightning Talk exploring the value of bringing Serverless development to your operations and developer teams, and how it fits with DevOps culture.
This talk will offer an introduction to Serverless applications, practical options for replacing infrastructure with Serverless, and will explore developer culture.
This document discusses infrastructure as code using tools like Jenkins, Ansible, and CloudFormation. It provides an overview of infrastructure as code and defines it as treating infrastructure resources as code that can be shared, changed, tested, and versioned. It then covers specific tools like Ansible for configuration management and CloudFormation for defining AWS infrastructure in templates. The goal is to discuss how infrastructure as code can be used to provision resources with code and implement continuous integration/delivery practices for infrastructure changes.
What does programming without servers look like? What are the possibilities? And how does it work? Wojciech Gawroński (Pattern Match) told us about it during the third meeting of Serverless User Group Poland, which took place on 27/09/2018 in Warsaw.
Wojtek's social media:
LinkedIN https://www.linkedin.com/in/afronski/
www https://pattern-match.com/
Serverless UG Poland
Facebook https://bit.ly/2zHuJeo
Serverless technologies and capabilities are here and are accessible now more than ever.
The power of infinite scale and system capabilities has never been more accessible. This also affects traditional front end development as serverless technologies allow for easy construction of backend support for any frontend with ease and simplicity.
In this talk, we will demonstrate how to build a fully functional Graphql endpoint for FE applications using Apollo Server and Client libraries, utilizing different cloud providers. We will also demonstrate the usage of Servless.com framework to set up the required infrastructure as code to simplify and support this setup
The video of the presentation (Hebrew):
https://youtu.be/8ba4cpdtK-8
This document discusses the importance of infrastructure as code (IaC) through a story of a company that struggled to deploy a new application. The company took 4 weeks and 2 days to deploy the application to production due to manually configuring environments. IaC advocates treating infrastructure like code that can be version controlled, tested, and deployed automatically. The document demonstrates deploying a load balancer and servers on DigitalOcean using Terraform as the IaC tool. Benefits of IaC include reuse, automation, version control, testing, documentation, and collaboration.
This document discusses functional programming in serverless environments. It begins by defining serverless computing and Function as a Service (FaaS). It then explores why serverless is useful from the perspectives of costs, architecture, and operations. The document examines using different programming languages like F# within serverless and the importance of tooling and context. It describes experiments running programs on AWS Lambda to measure predictability and constraints. Finally it provides references for further reading on serverless computing topics.
This is a Lightning Talk exploring the value of bringing Serverless development to your operations and developer teams, and how it fits with DevOps culture.
This talk will offer an introduction to Serverless applications, practical options for replacing infrastructure with Serverless, and will explore developer culture.
This document discusses infrastructure as code using tools like Jenkins, Ansible, and CloudFormation. It provides an overview of infrastructure as code and defines it as treating infrastructure resources as code that can be shared, changed, tested, and versioned. It then covers specific tools like Ansible for configuration management and CloudFormation for defining AWS infrastructure in templates. The goal is to discuss how infrastructure as code can be used to provision resources with code and implement continuous integration/delivery practices for infrastructure changes.
What does programming without servers look like? What are the possibilities? And how does it work? Wojciech Gawroński (Pattern Match) told us about it during the third meeting of Serverless User Group Poland, which took place on 27/09/2018 in Warsaw.
Wojtek's social media:
LinkedIN https://www.linkedin.com/in/afronski/
www https://pattern-match.com/
Serverless UG Poland
Facebook https://bit.ly/2zHuJeo
Serverless technologies and capabilities are here and are accessible now more than ever.
The power of infinite scale and system capabilities has never been more accessible. This also affects traditional front end development as serverless technologies allow for easy construction of backend support for any frontend with ease and simplicity.
In this talk, we will demonstrate how to build a fully functional Graphql endpoint for FE applications using Apollo Server and Client libraries, utilizing different cloud providers. We will also demonstrate the usage of Servless.com framework to set up the required infrastructure as code to simplify and support this setup
The video of the presentation (Hebrew):
https://youtu.be/8ba4cpdtK-8
This document discusses the importance of infrastructure as code (IaC) through a story of a company that struggled to deploy a new application. The company took 4 weeks and 2 days to deploy the application to production due to manually configuring environments. IaC advocates treating infrastructure like code that can be version controlled, tested, and deployed automatically. The document demonstrates deploying a load balancer and servers on DigitalOcean using Terraform as the IaC tool. Benefits of IaC include reuse, automation, version control, testing, documentation, and collaboration.
This document discusses functional programming in serverless environments. It begins by defining serverless computing and Function as a Service (FaaS). It then explores why serverless is useful from the perspectives of costs, architecture, and operations. The document examines using different programming languages like F# within serverless and the importance of tooling and context. It describes experiments running programs on AWS Lambda to measure predictability and constraints. Finally it provides references for further reading on serverless computing topics.
CI/CD Using Ansible and Jenkins for InfrastructureFaisal Shaikh
This document discusses using Ansible and Jenkins for continuous integration and delivery (CI/CD). It defines continuous integration and provides examples of tools that can be used including Ansible, Jenkins, monitoring systems, and application tests. It describes how to automate builds in Jenkins using the Jenkins Job Builder to configure jobs through YAML files for version control and reuse. Finally, it provides references to Jenkins plugins and the Jenkins Job Builder project.
Serverless compute with Azure Functions abstracts away infrastructure management and allows developers to focus on writing code for triggered operations. Azure Functions supports bindings to data sources and services that avoid writing boilerplate integration code, and can be deployed and managed via the Azure Functions runtime, CLI tools, templates and samples on GitHub.
Infrastructure as Code on Azure - NET Conf AR v2018 Victor Silva
This document discusses Infrastructure as Code and tools for implementing it on Azure like Ansible, Azure Cloud Shell, ARM Templates, and PowerShell DSC. It defines Infrastructure as Code as managing infrastructure through declarative configuration files. The presentation includes demos of creating a Playbook with Ansible, managing Azure resources with Cloud Shell, building a DSC configuration to create a web server, and using Azure Automation. Automating infrastructure tasks through these tools provides benefits like extensibility, reusability, consistency and accelerating deployments.
This document discusses continuous delivery in AWS. It defines continuous integration as regularly merging code changes into a central repository, after which automated builds and tests run. Continuous delivery is described as automatically building, testing, and preparing code changes for release to production. Benefits of continuous integration and continuous delivery include automating the software release process, improving developer productivity, and finding and addressing bugs earlier. The document provides links to additional resources on these topics.
This document discusses principles for achieving high availability in Drupal applications. It recommends using version control for all code and configuration, deploying artifacts rather than code directly, and configuring infrastructure and monitoring automation through tools like Chef and Puppet. It also stresses the importance of redundancy across multiple availability zones for critical services and caching, dealing with issues like unique IDs, replication conflicts, and cache flushing across nodes. The document advocates measuring systems thoroughly with logging, metrics and alerts, and contributing optimization work back to the open source community.
Building cloud native apps with .net core 3.0 and kubernetesNilesh Gule
Slide deck of the demo for Dotnet Conf Singapore 2019 event. the talk demonstrated new features in .Net core for building Cloud native applications including Health endpoints, worker services and configuration support for Kubernetes
This document discusses infrastructure as code and tools like Ansible, Puppet, and Chef that allow infrastructure to be coded and version controlled. It provides examples of using Ansible to configure Apache on an EC2 instance and testing infrastructure code with AnsibleSpec and GitHub CI/CD pipelines. Infrastructure as code aims to provision infrastructure in a code-driven and repeatable way rather than manually configuring systems.
Slide deck from the session on Serverless containers at Global Azure Bootcamp Virtual Singapore event. The session covered Serverless offerings on Azure with Logic Apps and Azure Functions. Deployed Azure Functions on containers with Azure Kubernetes Service (AKS) cluster. Scaled containers in serverless environment using Virtual Node addon for AKS and Azure Container Instances (ACI)
Implementation of the Continuous Integration based on Atlassian BambooАнете Аннемария
This document discusses continuous integration with Atlassian Bamboo. It describes using Bamboo to automatically run tests, build, and deploy code. It outlines the common CI process and how to configure a Bamboo project and plan mapped to a code repository. Bamboo is used to unify the deployment process across environments and minimize human errors during production deployments. Benefits of Bamboo include integrating unit tests, building/deploying without direct server access, and permission control.
The document discusses design patterns for scalable APIs based on Docker containers. It describes several common patterns including sidecar, ambassador, adapter, leader election, work queue, and scatter/gather. The patterns provide benefits like simplified problems, easy testing, resource isolation, and failure containment.
Azure DevOps Multistage YAML Pipelines – Top 10 FeaturesMarc Müller
The document discusses Azure DevOps pipelines and how they can be used to implement continuous delivery of applications and infrastructure to Azure. It covers key concepts like stages, jobs, and tasks in a pipeline. It also describes how pipelines can use templates, variables, secrets, and service connections to deploy apps, infrastructure resources, databases, and run tests on Azure. Secret management using Azure KeyVault is discussed along with the use of container jobs and hosted agents.
Containers and Developer Defined Data Centers - Evan Powell - Keynote in Bang...CodeOps Technologies LLP
DevOps and Containers go hand in hand. DevOps industry is expected to benefit significantly benefit from the container eco-system and technology. This keynote talks about the challenges and opportunities around deploying containers into production use cases.
The document discusses Cloud Foundry route services, which allow requests to applications to be forwarded through an external service. A route service can be used for offloading authentication, rate limiting, inspecting requests, or integrating with other systems. It describes how route services work by intercepting requests from the router. The usage and configuration of route services is also covered, including creating user-provided and service broker types. Examples of rate limiting and reverse proxy route services are provided.
The document discusses infrastructure as code using ARM templates on Azure. ARM templates allow infrastructure to be defined in code and treated like application code in version control. Key points covered include:
- ARM templates are JSON files that define Azure resources and deployment parameters
- Templates support parameters, variables, functions and outputs to define flexible and repeatable deployments
- Common elements like resources, properties, and tags can be authored in templates
- Templates are deployed via tools like Powershell or Azure CLI to create the defined infrastructure
The document provides an overview of the Azure CLI, including:
- The Azure CLI allows creation and management of Azure resources from the command line across platforms.
- It can be installed via several options and authenticated interactively or non-interactively.
- Resources can be created, queries performed, and configurations scoped via the CLI.
- Interactive mode aids command discovery and the Cloud Shell integrates it in the Azure portal.
- The open source project is on GitHub for contribution and support.
Ansible is a popular choice for automating infrastructure provisioning, config management, deployments, etc. Shippable provides a perfect complement with native CI, release management functionality as well as the ability to create event-driven workflows across ansible playbooks and other DevOps tools and activities.
This talk was presented by Shippable's co-founder and VP Product Management Manisha Sahasrabudhe at AnsibleFest 2017.
Scaling Your First 1000 Containers with DockerAtlassian
Deploying large numbers of containers to production can be a difficult proposition if you don’t approach the problem with the right strategy – one that's appropriate for both your developers and the size of your operations team. Choosing a strategy lets you codify your deployment patterns in a repeatable manner and reuse them over hundreds of deployments without incurring unnecessary cost and complexity.
Using Atlassian’s PaaS as a model, we will discuss important milestones as you scale from a single container to tens, hundreds, and eventually to a thousand containers. At what points should you begin to embrace log aggregation? How about monitoring and metrics collection? Orchestration and clustering solutions? Learn how to incorporate ever more sophisticated third-party solutions as you go, to achieve cost-effective and stable management of your containers in production.
In this session, we will understand how to create your first pipeline and build an environment to restore dependencies and how to run tests in Azure DevOps followed by building an image and pushing it to container registry.
Containing Chaos with Kubernetes - Terrence Ryan, Google - DevOpsDays Tel Avi...DevOpsDays Tel Aviv
The document discusses Kubernetes and container orchestration. It begins with an introduction to the problem of managing containers and microservices across multiple machines. It then covers key Kubernetes concepts like pods, controllers, services, labels and selectors. It also demonstrates Kubernetes in action and discusses options for hosting Kubernetes clusters, particularly Google Container Engine which provides a hosted Kubernetes environment.
NFV workloads pose challenges for IIAS providers. Learn how hardware performance enhancements (DPA&EPA) by Intel, integrated with virtualization providers, can be an NFV enabler, and how advanced orchestration by TOSCA and Cloudify can put the right VNF on the right hardware and coordinate complex deployments.
CI/CD Using Ansible and Jenkins for InfrastructureFaisal Shaikh
This document discusses using Ansible and Jenkins for continuous integration and delivery (CI/CD). It defines continuous integration and provides examples of tools that can be used including Ansible, Jenkins, monitoring systems, and application tests. It describes how to automate builds in Jenkins using the Jenkins Job Builder to configure jobs through YAML files for version control and reuse. Finally, it provides references to Jenkins plugins and the Jenkins Job Builder project.
Serverless compute with Azure Functions abstracts away infrastructure management and allows developers to focus on writing code for triggered operations. Azure Functions supports bindings to data sources and services that avoid writing boilerplate integration code, and can be deployed and managed via the Azure Functions runtime, CLI tools, templates and samples on GitHub.
Infrastructure as Code on Azure - NET Conf AR v2018 Victor Silva
This document discusses Infrastructure as Code and tools for implementing it on Azure like Ansible, Azure Cloud Shell, ARM Templates, and PowerShell DSC. It defines Infrastructure as Code as managing infrastructure through declarative configuration files. The presentation includes demos of creating a Playbook with Ansible, managing Azure resources with Cloud Shell, building a DSC configuration to create a web server, and using Azure Automation. Automating infrastructure tasks through these tools provides benefits like extensibility, reusability, consistency and accelerating deployments.
This document discusses continuous delivery in AWS. It defines continuous integration as regularly merging code changes into a central repository, after which automated builds and tests run. Continuous delivery is described as automatically building, testing, and preparing code changes for release to production. Benefits of continuous integration and continuous delivery include automating the software release process, improving developer productivity, and finding and addressing bugs earlier. The document provides links to additional resources on these topics.
This document discusses principles for achieving high availability in Drupal applications. It recommends using version control for all code and configuration, deploying artifacts rather than code directly, and configuring infrastructure and monitoring automation through tools like Chef and Puppet. It also stresses the importance of redundancy across multiple availability zones for critical services and caching, dealing with issues like unique IDs, replication conflicts, and cache flushing across nodes. The document advocates measuring systems thoroughly with logging, metrics and alerts, and contributing optimization work back to the open source community.
Building cloud native apps with .net core 3.0 and kubernetesNilesh Gule
Slide deck of the demo for Dotnet Conf Singapore 2019 event. the talk demonstrated new features in .Net core for building Cloud native applications including Health endpoints, worker services and configuration support for Kubernetes
This document discusses infrastructure as code and tools like Ansible, Puppet, and Chef that allow infrastructure to be coded and version controlled. It provides examples of using Ansible to configure Apache on an EC2 instance and testing infrastructure code with AnsibleSpec and GitHub CI/CD pipelines. Infrastructure as code aims to provision infrastructure in a code-driven and repeatable way rather than manually configuring systems.
Slide deck from the session on Serverless containers at Global Azure Bootcamp Virtual Singapore event. The session covered Serverless offerings on Azure with Logic Apps and Azure Functions. Deployed Azure Functions on containers with Azure Kubernetes Service (AKS) cluster. Scaled containers in serverless environment using Virtual Node addon for AKS and Azure Container Instances (ACI)
Implementation of the Continuous Integration based on Atlassian BambooАнете Аннемария
This document discusses continuous integration with Atlassian Bamboo. It describes using Bamboo to automatically run tests, build, and deploy code. It outlines the common CI process and how to configure a Bamboo project and plan mapped to a code repository. Bamboo is used to unify the deployment process across environments and minimize human errors during production deployments. Benefits of Bamboo include integrating unit tests, building/deploying without direct server access, and permission control.
The document discusses design patterns for scalable APIs based on Docker containers. It describes several common patterns including sidecar, ambassador, adapter, leader election, work queue, and scatter/gather. The patterns provide benefits like simplified problems, easy testing, resource isolation, and failure containment.
Azure DevOps Multistage YAML Pipelines – Top 10 FeaturesMarc Müller
The document discusses Azure DevOps pipelines and how they can be used to implement continuous delivery of applications and infrastructure to Azure. It covers key concepts like stages, jobs, and tasks in a pipeline. It also describes how pipelines can use templates, variables, secrets, and service connections to deploy apps, infrastructure resources, databases, and run tests on Azure. Secret management using Azure KeyVault is discussed along with the use of container jobs and hosted agents.
Containers and Developer Defined Data Centers - Evan Powell - Keynote in Bang...CodeOps Technologies LLP
DevOps and Containers go hand in hand. DevOps industry is expected to benefit significantly benefit from the container eco-system and technology. This keynote talks about the challenges and opportunities around deploying containers into production use cases.
The document discusses Cloud Foundry route services, which allow requests to applications to be forwarded through an external service. A route service can be used for offloading authentication, rate limiting, inspecting requests, or integrating with other systems. It describes how route services work by intercepting requests from the router. The usage and configuration of route services is also covered, including creating user-provided and service broker types. Examples of rate limiting and reverse proxy route services are provided.
The document discusses infrastructure as code using ARM templates on Azure. ARM templates allow infrastructure to be defined in code and treated like application code in version control. Key points covered include:
- ARM templates are JSON files that define Azure resources and deployment parameters
- Templates support parameters, variables, functions and outputs to define flexible and repeatable deployments
- Common elements like resources, properties, and tags can be authored in templates
- Templates are deployed via tools like Powershell or Azure CLI to create the defined infrastructure
The document provides an overview of the Azure CLI, including:
- The Azure CLI allows creation and management of Azure resources from the command line across platforms.
- It can be installed via several options and authenticated interactively or non-interactively.
- Resources can be created, queries performed, and configurations scoped via the CLI.
- Interactive mode aids command discovery and the Cloud Shell integrates it in the Azure portal.
- The open source project is on GitHub for contribution and support.
Ansible is a popular choice for automating infrastructure provisioning, config management, deployments, etc. Shippable provides a perfect complement with native CI, release management functionality as well as the ability to create event-driven workflows across ansible playbooks and other DevOps tools and activities.
This talk was presented by Shippable's co-founder and VP Product Management Manisha Sahasrabudhe at AnsibleFest 2017.
Scaling Your First 1000 Containers with DockerAtlassian
Deploying large numbers of containers to production can be a difficult proposition if you don’t approach the problem with the right strategy – one that's appropriate for both your developers and the size of your operations team. Choosing a strategy lets you codify your deployment patterns in a repeatable manner and reuse them over hundreds of deployments without incurring unnecessary cost and complexity.
Using Atlassian’s PaaS as a model, we will discuss important milestones as you scale from a single container to tens, hundreds, and eventually to a thousand containers. At what points should you begin to embrace log aggregation? How about monitoring and metrics collection? Orchestration and clustering solutions? Learn how to incorporate ever more sophisticated third-party solutions as you go, to achieve cost-effective and stable management of your containers in production.
In this session, we will understand how to create your first pipeline and build an environment to restore dependencies and how to run tests in Azure DevOps followed by building an image and pushing it to container registry.
Containing Chaos with Kubernetes - Terrence Ryan, Google - DevOpsDays Tel Avi...DevOpsDays Tel Aviv
The document discusses Kubernetes and container orchestration. It begins with an introduction to the problem of managing containers and microservices across multiple machines. It then covers key Kubernetes concepts like pods, controllers, services, labels and selectors. It also demonstrates Kubernetes in action and discusses options for hosting Kubernetes clusters, particularly Google Container Engine which provides a hosted Kubernetes environment.
NFV workloads pose challenges for IIAS providers. Learn how hardware performance enhancements (DPA&EPA) by Intel, integrated with virtualization providers, can be an NFV enabler, and how advanced orchestration by TOSCA and Cloudify can put the right VNF on the right hardware and coordinate complex deployments.
Autoscaling OpenStack Natively with Heat, Ceilometer and LBaaSShixiong Shang
Autoscaling OpenStack Natively with Heat, Ceilometer and LBaaS workshop I delivered at OpenStack Vancouver Summit (May, 2015) jointly with Jason and Sharmin from Cisco System.
More details can be found at https://github.com/grimmtheory/autoscale
Applying DevOps to Databricks can be a daunting task. In this talk this will be broken down into bite size chunks. Common DevOps subject areas will be covered, including CI/CD (Continuous Integration/Continuous Deployment), IAC (Infrastructure as Code) and Build Agents.
We will explore how to apply DevOps to Databricks (in Azure), primarily using Azure DevOps tooling. As a lot of Spark/Databricks users are Python users, will will focus on the Databricks Rest API (using Python) to perform our tasks.
Can i service this from my raspberry piThoughtworks
Infrastructure-related skills are essential for developers in cross-functional teams who build microservices for the cloud. Becoming proficient in infrastructure development is not just about understanding the hardware and software components on top of which applications run in the cloud. It's also about being able to use the tools that provide virtual access to this infrastructure and enable us to provision, configure, monitor it, and deploy applications to it. In this talk Gesa shares how building a Kubernetes cluster of Raspberry Pis and serving applications from it can help in acquiring fundamental infrastructure skills.
Automating Software Development Life Cycle - A DevOps ApproachAkshaya Mahapatra
The document discusses DevOps and provides an overview of the key concepts. It describes how DevOps aims to bring development, operations, and business teams together through automating processes, continuous monitoring, and breaking down silos between teams. The document then covers various DevOps tools and technologies like version control systems, build tools, configuration management, virtualization, and continuous integration/deployment practices.
Integrating Infrastructure as Code into a Continuous Delivery Pipeline | AWS ...Amazon Web Services
This document discusses integrating infrastructure as code into a continuous delivery pipeline. It covers DevOps principles like collaboration, automation, and monitoring everything. It discusses benefits like increased velocity and reduced risk. Infrastructure as code is realized using tools like Ansible, Chef, and Terraform to define infrastructure in code. This allows infrastructure to be treated like code and integrated into software development pipelines for continuous integration and delivery of both application and infrastructure changes.
Cloud providers like Amazon or Goggle have great user experience to create and manage PaaS and IaaS services. But is it possible to reproduce same experience and flexibility locally, in on premise datacenter? This talk describes success story of creation private cloud based on DC/OS cluster. It is used to host and share different services like hadoop or kafka for development teams, dynamically manage services and resource pools with GKE integration.
Quilt - Distributed Load Simulation from AWSAjith Jose
A distributed load testing tool to generated 100s of thousands of audio video endpoints along with all the API calls and WebSocket connections it needs!
We designed the load generation tool as a highly scalable distributed system, as it needs a lot of computing power to simulate 100K+ automated endpoints. It starts 100s of AWS/GCP instances before starting the fire. Fully automated, Get - Set - Fire !
This document discusses using virtual platforms for system-level verification of an OMAPV2230 integrated UMTS solution chip. Virtual platforms allow validating software and firmware for the hardware board and drivers before silicon is available. This avoids potential re-spins of the silicon that could cost $1 million. The virtual platform in this case accelerated software development and reduced post-silicon bench time.
Development of a Cisco ACI device package for NGINX as a Load-BalancerFabrice Servais
This presentation summarises the development of a Cisco ACI device package for NGINX as a Load-Balancer, made as a proof-of-concept during an internship at Cisco.
Want to see the device package and its source code? Check out these Github repositories:
https://github.com/FServais/NGINX-Device-Package
https://github.com/FServais/NGINX-Agent
Bob McWhirter is a JBoss Fellow and Chief Architect of Middleware Cloud Computing. He founded The Codehaus, Drools, and TorqueBox. The document discusses BoxGrinder, a tool that can create virtual machine appliances from definition files in order to simplify deploying software to infrastructure platforms like Amazon EC2 or VMware. It describes how BoxGrinder supports both "baking" and "frying" approaches to creating VMs and walks through an example of using BoxGrinder to build a JBoss application server appliance.
OSDC 2014: Andreas Schmidt - Testing server infrastructure with serverspec NETWAYS
Companies that focus on cloud infrastructures for both developing and running their applications are likely to have the highest benefit of test driven infrastructure tools such as configuration management and their spec-oriented testing counterparts.
However many enterprises have not moved to the cloud yet.
Often limited by contracts, regulations or security considerations, they too are in need of testing their infrastructure that service providers built for them.
The talk shows approaches to infrastructure testing and demonstrates the use of serverspec (http://serverspec.org/).
This talk discusses Linux profiling using perf_events (also called "perf") based on Netflix's use of it. It covers how to use perf to get CPU profiling working and overcome common issues. The speaker will give a tour of perf_events features and show how Netflix uses it to analyze performance across their massive Amazon EC2 Linux cloud. They rely on tools like perf for customer satisfaction, cost optimization, and developing open source tools like NetflixOSS. Key aspects covered include why profiling is needed, a crash course on perf, CPU profiling workflows, and common "gotchas" to address like missing stacks, symbols, or profiling certain languages and events.
What’s Slowing Down Your Kafka Pipeline? With Ruizhe Cheng and Pete Stevenson...HostedbyConfluent
What’s Slowing Down Your Kafka Pipeline? With Ruizhe Cheng and Pete Stevenson | Current 2022
Imagine having access to metrics, events, and insights without code modification or application redeployment. Imagine visualizing delays and tracking down performance bottlenecks in your Kafka pipeline instantly with minimal performance overhead. In this session, we show all of this is possible with eBPF.
In a live demo, we will introduce an eBPF-based, always-on, CPU profiler to visualize what your Kafka applications are spending time on. We will analyze how much time the Kafka broker spends on handling different requests and responding to polling and how much time a Kafka consumer spends on polling the broker and processing the messages. Furthermore, we will see how to detect issues by measuring consumer lags in both offsets and seconds, and how to correlate the increasing consumer lag with the CPU flame graphs. We demonstrate how not only to detect issues quickly but also to pinpoint performance bottlenecks instantly in the Kafka pipeline: e.g. garbage collection and disk/network IO.
In addition, we will provide some unique insights with eBPF: e.g. topic-centric flow graphs, consumer rebalancing lags, and under-replicated partitions.
Collecting all the data with no instrumentation and low overhead is no easy task. we will conclude by revealing the magic of eBPF and discussing the design choices and technical challenges of our network traffic tracer and Java CPU profiler that empowered deep visibility into Kafka.
Immutable Server generation: The new App DeploymentAxel Fontaine
From JavaZone 2014
Video: https://vimeo.com/105851488
Abstract:
App deployment and server setup are complex, error-prone and time-consuming. They require OS installers, package managers, configuration recipes, install and deployment scripts, server tuning, hardening and more. But... Is this really necessary? Are we trapped in a mindset of doing things this way just because that's how they've always done?
What if we could start over and radically simplify all this? What if, within seconds, and with a single command, we could wrap our application into the bare minimal machine required to run it? What if this machine could then be transported and run unchanged on our laptop and in the cloud? How do the various tools like Docker and Boxfuse fit into this picture? What are their strengths and weaknesses? When should you use them?
This talk is for developers and architects wishing to radically improve and simplify how they deploy their applications. It takes Continuous Delivery to a level far beyond what you've seen today. Welcome to Immutable Server generation. This is the new black.
What is Digital Rebar Provision (and how RackN extends)?rhirschfeld
Walks through how Digital Rebar Provision rethinks bare metal automation beyond simple O/S install into an integrated workflow system for building data center underlay.
INCLUDES VIDEO OF PRESO
This document provides an overview of a presentation about quick stack building using AWS CDK and infrastructure as code. The presentation introduces AWS CDK and infrastructure as code, discusses CloudFormation and CDK, and provides tips. Slides from the presentation will be made available online later.
Similar to Debugging & Profiling of AWS Lambda: ServerlessConf - IOpipe (20)
Ops for NoOps - Operational Challenges for Serverless AppsErica Windisch
A look into the problems users are facing running serverless applications in production, solutions, and digging into the Lambda blackbox.
Presented by Erica Windisch, CTO of IOpipe, Inc. IOpipe offers Application Performance Monitoring for Serverless apps. Eric is ex-Docker, ex-Cloudscaling, builder of clouds, and destroyer of monoliths.
Register for IOpipe at www.iopipe.com!
Building Composable Serverless Apps with IOpipe Erica Windisch
This document discusses building composable serverless applications using the iopipe module.
The iopipe module allows chaining together serverless functions, code sharing, and running functions anywhere including AWS Lambda, Docker, and local CPUs. It provides tools for function composition, monitoring performance metrics, and deploying functions. Composable serverless applications can be built by connecting together inline functions, stored functions, and deployed HTTP endpoints using iopipe.
Patterns for Secure Containerized Applications (Docker)Erica Windisch
The document discusses containerization and isolation as security patterns for applications. It notes that consolidation is not actually a security pattern, and discusses hypervisors like Xen having vulnerabilities. Fragmentation through isolation into microservices is presented as a security pattern, while simply having more services is not. The document acknowledges that isolation patterns can require more work.
The Nova driver for Docker has been maturing rapidly since its mainline removal in Icehouse. During the Juno cycle, substantial improvements have been made to the driver, and greater parity has been reached with other virtualization drivers. We will explore these improvements and what they mean to deployers. Eric will additionally showcase deployment scenarios for the deployment of OpenStack itself inside and underneath of Docker for powering traditional VM-based computing, storage, and other cloud services. Finally, users should expect a preview of the planned integration with the new OpenStack Containers Service effort to provide automation of advanced containers functionality and Docker-API semantics inside of an OpenStack cloud.
Note that the included Heat templates are NOT usable. See the linked Heat resources for viable templates and examples.
Docker for Developers: Dev, Test, Deploy @ BucksCo Devops at MeetMe HQErica Windisch
The document discusses Docker's platform and ecosystem, which has grown significantly over 19 months to include over 640 contributors, 2.75 million downloads, and extensive community support and documentation. It also outlines the key components of Docker's platform, including the Docker Engine for building, shipping, and running containers, and Docker Hub for sharing images. Finally, it provides examples of how to use Docker to build, run, and manage applications and services across infrastructure.
The Docker "Gauntlet" - Introduction, Ecosystem, Deployment, OrchestrationErica Windisch
This document summarizes Docker's growth over 15 months, including its community size, downloads, projects on GitHub, enterprise support offerings, and the Docker platform which includes the Docker Engine, Docker Hub, and partnerships. It also provides overviews of key Docker technologies like libcontainer, libchan, libswarm, and how images work in Docker.
Things will Change - Usenix Keynote UCMS'14Erica Windisch
From servers and containers, to services and things. Building an Internet of Things of the clouds and infrastructure we're building today. Maps the future of configuration management and systems artifact management.
This document discusses using Docker containers and Chef configuration management together. It begins by showing how to build Docker images that include Chef using Dockerfiles. It then explains how Chef can be used to configure containers during the image build process, essentially "baking" the configuration into the images. This allows immutable infrastructure where configured containers can be started without needing to rerun Chef provisioning. The document also discusses using multi-stage Dockerfiles and Chef runs to fully configure images. It briefly covers tools for deploying Docker containers, such as using Chef on EC2 instances or with OpenStack Heat orchestration.
Practical Docker for OpenStack (Juno Summit - May 15th, 2014)Erica Windisch
This document discusses using Docker containers with OpenStack. It describes installing the Nova Docker compute driver plugin to enable launching and managing Docker containers via the OpenStack Nova API. The plugin allows spawning Docker containers from images in Glance and supports basic container operations. However, some Nova features like live migration and advanced Docker capabilities are not yet supported. Using Docker with Nova provides an alternative to Heat for container orchestration with OpenStack.
This document discusses using Chef configuration management with Docker containers. It describes using Chef at both the build stage and runtime stage of containers. At build time, Chef can configure and install applications into an image. At runtime, Chef can further configure running containers based on environment variables. Combining Chef and Docker provides immutable infrastructure, faster deployments, and testable configurations.
This document discusses using Docker containers with OpenStack. Key points include:
- A Docker plugin allows controlling Docker containers via the OpenStack Nova API and Horizon dashboard. This enables launching, terminating, rebooting and managing the lifecycle of Docker containers as if they were virtual machines.
- Heat orchestration templates can be used to define Docker resources and automate the deployment of multi-container applications on OpenStack. Heat integrates with the Docker API to start and stop containers.
- Developers can test OpenStack using Docker by running DevStack inside a container, allowing containers to be used like virtual machines for testing and development purposes.
This document discusses Docker and its integration with OpenStack. It provides five major use cases for Docker: alternative virtualization, continuous integration/delivery, scaling applications, cross-cloud deployment, and resource/security isolation. It also describes a demo of pushing a containerized application through development testing and multiple clouds without downtime. Additionally, it outlines the Docker plugin for Nova in OpenStack which enables control of Docker containers via the Nova API and Horizon UI.
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Recording:
https://www.youtube.com/live/MSdGLG2zLy8?si=INxBHTqkwHhxV5Ta&t=0
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Flutter is a popular open source, cross-platform framework developed by Google. In this webinar we'll explore Flutter and its architecture, delve into the Flutter Embedder and Flutter’s Dart language, discover how to leverage Flutter for embedded device development, learn about Automotive Grade Linux (AGL) and its consortium and understand the rationale behind AGL's choice of Flutter for next-gen IVI systems. Don’t miss this opportunity to discover whether Flutter is right for your project.
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For more info visit us https://valintry360.com/solutions/health-life-sciences
What to do when you have a perfect model for your software but you are constrained by an imperfect business model?
This talk explores the challenges of bringing modelling rigour to the business and strategy levels, and talking to your non-technical counterparts in the process.
Transform Your Communication with Cloud-Based IVR SolutionsTheSMSPoint
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Mobile App Development Company In Noida | Drona InfotechDrona Infotech
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Visit Us For : https://www.dronainfotech.com/mobile-application-development/
2. Erica Windisch
CTO & Founder IOpipe, Inc.
Former maintainer of Docker &
OpenStack Building cloud, ops, and
infrastructure tooling for over 15
years.
17. Things that don’t work:
Linux eBPF!
$ iosnoop
Tracing block I/O. Ctrl-C to end.
/usr/bin/iosnoop: line 172: cd: /sys/kernel/debug/tracing: Permission denied
ERROR: accessing tracing. Root user? Kernel has FTRACE?
debugfs mounted? (mount -t debugfs debugfs /sys/kernel/debug)
18. Things that don’t work:
Linux eBPF!
λ$ ls -l /sys
⨯ Error: function response: Command failed: ls -l /sys
ls: cannot access /sys: No such file or directory
24. Lambda Limitations
✤ Event-loop is out of our direct control
✤ Process command-line flags inaccessible
✤ Ptrace disabled!
✤ Linux kernel perf features not available on Lambda.
✤ Local dev+test is an evolving story
✤ Many languages, requiring different implementations
✤ Debugger breakpoints in prod aren’t generally viable