Criu texas-linux-fest-2014

When you hear words such as Kubernetes or OpenShift you immediately start thinking about long running processes you can easily scale at will. However, Kubernetes includes a lesser known feature which allows you to run pretty much anything from simple tasks up to highly-complicated ones. During this presentation, the author of the Job resource in Kubernetes will guide you through several techniques for performing anything ranging from simple Pi calculations to rendering a movie. No matter if you're a data scientist running large scale calculations across several data centers or a hobby programmer running simple day-to-day tasks, this presentation is to teach you how to efficiently use Kubernetes Jobs on their own or as the building blocks of something bigger. This presentation will feature a number of live demos to help illustrate the various ways that you can put Jobs to work. Don’t miss out on learning about one of the coolest features of Kubernetes! Sched Link: http://sched.co/6BUw

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The last couple of years have seen an increasing interest in Docker and related technologies. One of these technologies is CoreOS, a new operating system built from the ground up for running Docker containers at scale. In this talk we will learn about CoreOS main concepts and tools. We will get our hands dirty as we work together toward a goal of running a CoreOS cluster on AWS (using Ansible) and running docker containers on it. The talk will conclude with a discussion on the place of Ansible (and configuration management tools in general) in the "next-generation" stack.

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This talk will start with a deep dive and hands on examples of BPF, possibly the most promising low level technology to address challenges in application and network security, tracing, and visibility. We will discuss how BPF evolved from a simple bytecode language to filter raw sockets for tcpdump to the a JITable virtual machine capable of universally extending and instrumenting both the Linux kernel and user space applications. The introduction is followed by a concrete example of how the Cilium open source project applies BPF to solve networking, security, and load balancing for highly distributed applications. We will discuss and demonstrate how Cilium with the help of BPF can be combined with distributed system orchestration such as Docker to simplify security, operations, and troubleshooting of distributed applications.

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Apache Hadoop at Yahoo is a massive platform with 36 different clusters spread across YARN, Apache HBase, and Apache Storm deployments, totaling 60,000 servers made up of 100s of different hardware configurations accumulated over generations, presenting unique operational challenges and a variety of unforeseen corner cases. In this talk, we will share methods, tips and tricks to deal with large scale kernel upgrade on heterogeneous platforms within tight timeframes with 100% uptime and no service or data loss through the Dirty COW use case (privilege escalation vulnerability found in the Linux Kernel in late 2016). We will dive deep into our three phased approach that led to eventual success of the program - pre work, kernel upgrade itself, and post work / cleanup. We will share the details on automation tools, UIs, and reporting tools developed and used to achieve the stated objectives of 800+ server upgrades per hour, track the upgrade progress, validate and report data blocks, and recover quickly from bad blocks encountered. Throughout the talk, we will highlight the importance of process management, communicating with 100s of custom teams to ensure they are onboard and aware, and successful coordination tactics with SREs and Site Operations. We will also touch upon some of the unique challenges we faced along with way such as BIOS updates necessary on over 20,000 hosts along the way, and explain system rolling upgrade support we added to HBase and Storm for avoiding service disruption to low latency customer during these upgrades.

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Konrad Wilk is a Software Development Manager at Oracle. His groupâ€™s mission is to make Linux and Xen Project virtualization better and faster. As part of this work, Konrad has been the maintainer of the Xen Project subsystem in Linux, Xen Project maintainer and now also Release Manager for the 4.5 release of the Xen Project Hypervisor. Konrad has been active in the Linux and Xen Project communities for more than 6 years and was instrumental in adding Xen Project support to the Linux Kernel.

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This talk was presented at SRE NYC Meetup on August 16, 2017 at Squarespace HQ. https://www.youtube.com/watch?v=UJ1QAKprVr4 As the engineering teams at Squarespace grow, we have been building more and more microservices. However, this has added operational strain as we try to shoehorn a growing, complex dynamic environment into our static data center infrastructure. We needed to rethink how we handle deployments, dependency management, resource allocation, monitoring, and alerting. Docker containerization and Kubernetes orchestration helps us tackle many of these problems, but the journey has been challenging. In this talk, we’ll discuss the challenges of running Kubernetes in a datacenter and how we switched to a more SLA-focused alert structure than per instance health with Prometheus and AlertManager.

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Using the NVIDIA Container Runtime, many developers and enterprises have been developing, benchmarking and deploying deep learning (DL) frameworks, HPC and other GPU accelerated containers at scale for the last two years. In this talk, we will go over the architecture of the NVIDIA Container Runtime and discuss our recent close collaboration with Docker. The result of our collaboration with Docker is a seamless native integration of the runtime enabling Docker Engine 19.03 CE and the forthcoming Docker Enterprise release to run GPU accelerated containers. We will also highlight containerized NVIDIA drivers. This new feature eliminates the overhead of provisioning GPU machines and brings GPU support on container optimized operating systems, which either lack package managers for installing software or require all applications to run in containers. In this session, you will learn how GPU accelerated containers can be easily built and deployed through the use of driver containers and native support for GPUs in Docker 19.03. The session will include a demo of running a GPU accelerated deep learning container using the new CLI options in Docker 19.03 and containerized drivers. Running NVIDIA GPU accelerated containers with Docker has never been this easy!

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Enterprise data centers have to support a diverse of set of workloads: cloud native, big data, high performance computing, and legacy applications. While cloud native applications are ideal to run in Docker clusters, bare metal and virtualization infrastructures must still be supported in the data center. The result is a proliferation of clusters and technologies running in individual silos, resulting in high management costs and low utilization. This talk describes the challenges and experiences in implementing a shared cluster infrastructure based on Kubernetes to support big data, high performance computing, and VM-based workloads. The talk will show the deployment and scaling of a high performance computing workload manager, Spark, and OpenStack, and how the VM and Docker management can be integrated together.

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Presented at LISA18: https://www.usenix.org/conference/lisa18/presentation/huynh While there are plenty of readily available metrics for monitoring Linux kernel, many gems remain hidden. With the help of recent developments in eBPF, it is now possible to run safe programs in the kernel to collect arbitrary information with little to no overhead. A few examples include: * Disk latency and io size histograms * Run queue (scheduler) latency * Page cache efficiency * Directory cache efficiency * LLC (aka L3 cache) efficiency * Kernel timer counters * System-wide TCP retransmits Practically any event from "perf list" output and any kernel function can be traced, analyzed and turned into a Prometheus metric with almost arbitrary labels attached to it. If you are already familiar with BCC tools, you may think if ebpf_exporter as bcc tools turned into prometheus metrics. In this tutorial we’ll go over eBPF basics, how to write programs and get insights into a running system.

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thredUP team shares key learnings from after-migration processes. We tell you about what technologies and solutions worked best for us and where we spent time troubleshooting and improving. In particular we have focused on development and staging experience, user authentication, cloud-native CI pipelines, applications telemetry and service mesh. We also share our experience with Kubernetes security hardening, autoscaling and tell you about a new service creation within our infrastructure.

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If you look under the hood, Linux containers are just processes with some isolation features and resource quotas sprinkled on top. In this talk, we will apply modern Linux performance tools to container analysis: get high-level resource utilization on running containers with docker stats, htop, and nsenter; dig into high-CPU issues with perf; detect slow filesystem latency with BPF-based tools; and generate flame graphs of interesting event call stacks. Sasha Goldshtein is the CTO of Sela Group, a Microsoft MVP and Regional Director, Pluralsight and O'Reilly author, and international consultant and trainer. Sasha is the author of two books and multiple online courses, and a prolific blogger. He is also an active open source contributor to projects focused on system diagnostics, performance monitoring, and tracing -- across multiple operating systems and runtimes. Sasha authored and delivered training courses on Linux performance optimization, event tracing, production debugging, mobile application development, and modern C++. Between his consulting engagements, Sasha speaks at international conferences world-wide. You can find more details on the meetup page - https://www.meetup.com/Tel-Aviv-Yafo-Linux-Kernel-Meetup/events/245319189/

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Historically, sharing a Linux server entailed all kinds of untenable compromises. In addition to the security concerns, there was simply no good way to keep one application from hogging resources and messing with the others. The classic “noisy neighbor” problem made shared systems the bargain-basement slums of the Internet, suitable only for small or throwaway projects. Serious use-cases traditionally demanded dedicated systems. Over the past decade virtualization (in conjunction with Moore’s law) has democratized the availability of what amount to dedicated systems, and the result is hundreds of thousands of websites and applications deployed into VPS or cloud instances. It’s a step in the right direction, but still has glaring flaws. Most of these websites are just piles of code sitting on a server somewhere. How did that code got there? How can it can be scaled? Secured? Maintained? It’s anybody’s guess. There simply isn’t enough SysAdmin talent in the world to meet the demands of managing all these apps with anything close to best practices without a better model. Containers are a whole new ballgame. Unlike VMs, you skip the overhead of running an entire OS for every application environment. There’s also no need to provision a whole new machine to have a place to deploy, meaning you can spin up or scale your application with orders of magnitude more speed and accuracy.

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This talk is about a new interface to get information about processes, called task_diag, which we developed. Currently /proc file system is used to get information about the processes running on the system. All information are presented as text files, which is convenient for humans, but not for programs such as ps and top. This incurs significant delays, especially on a systems with lots of containers running, which is frequently the case nowdays. Ideally, tools such top and ps would get information in binary format, and use flexible means to specify which kinds of information and for which tasks is required. Presented is a new interface with all these features, called task_diag. task_diag is based on netlink sockets and looks like socket-diag, which is used to get information about sockets. It uses the request-response model. An request specifies a set of processes and required properties for them. A response contains requested information and can be divided into a few netlink packets if it's too long. The task diag is much faster than the /proc file system. For example, when reading from /proc, ps opens, reads, and closes many files -- and iterates this for every single processes. With task_diag, it's just sending a request and getting a response. Except for ps and top, the proposed interface is to be used by CRIU, a containers checkpoint/restore and live migration mechanism. Also, developers of perf tool found that it can be useful to them and implemented a prototype which show a big performance improvements in case of using task_diag instead of procfs. Our performance measurements show that the ps tool works at least four times faster if task_diag is used instead of procfs.

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At the recent Microsoft Ignite 2023 conference, Microsoft unveiled a groundbreaking strategy that will redefine enterprise work management. The plan involves integrating Microsoft’s key planning tools, Microsoft To Do, Microsoft Planner, and Microsoft Project for the web into a unified experience called “Microsoft Planner.” What does this new strategy from Microsoft mean for current users? Join us and learn how best to take advantage of this announcement while gaining a clear path on how to elevate the current state of Microsoft Planner from a basic task manager to a comprehensive tool for Enterprise Work Management using OnePlan. Learn how OnePlan’s integration with Microsoft Planner allows for strategic alignment with business goals through advanced features like strategic planning, portfolio management, resource management, financial management, and more!

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In today's dynamic e-commerce landscape, the payment gateway emerges as a linchpin, ensuring smooth and secure transactions between buyers and sellers. In this discourse, we delve into the meticulous process of devising test cases tailored for scrutinizing payment gateways. Crafting precise test cases for payment gateways is a quintessential responsibility for testers operating within the service industry. This article meticulously explores pivotal scenarios integral to how to test payment gateways, coupled with essential guidelines for drafting effective test cases.

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Data spaces in distributed environments should be allowed to evolve in agile ways providing data space owners with large flexibility about which data they store. Agility and heterogeneity, however, jeopardize data exchanges because representations may build on varying ontologies and data consumers may not rely on the semantic correctness of their queries in the context of semantically heterogeneous, evolving data spaces. Graph data spaces are one example of a powerful model for representing and querying data whose semantics may change over time. To assert and enforce conditions on individual graph data spaces, shape languages (e.g SHACL) have been developed. We investigate the question of how querying and programming can be guarded by reasoning over SHACL constraints in a distributed setting and we sketch a picture of how a future landscape based on semantically heterogeneous data spaces might look like.

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