Notes from Root Conf Day 1 - 2017

Root Conf is a conference on DevOps and Cloud Infrastructure. 2017 edition’s theme is service reliability. Following is my notes from Day 1.

  1. State of the open source monitoring landscape

    • The speaker of the session is the co-founder of Icinga monitoring system. I missed first ten minutes of the talk.-The talk is a comparison of all available OSS options for monitoring, visualization.
    • Auto-discovery is hard.
    • As per 2015 monitoring tool usage survey, Nagios is widely used.
    • Nagios is reliable and stable.
    • Icinga 2 is a fork of Nagios, rewrite in c++. It’s modern, web 2.0 with APIs, extensions and multiple backends.
    • Sensu has limited features on OSS side and a lot of features on enterprise version. OSS version isn’t useful much.
    • Zabbix is full featured, out of box monitoring system written in C. It provides logging and graphing features. Scaling is hard since all writes are written to single Postgres DB.
    • Riemann is stream processor and written in Clojure. The DSL stream processing language needs knowledge of Clojure. The system is stateless.
    • OpenNMS is a network monitoring tool written in Java and good for auto discovery. Using plugins for a non-Java environment is slow.
    • Graphite is flexible, a popular monitoring tool for time series database.
    • Prometheus is flexible rule-based alerting and time series database metrics.
    • Elastic comes with Elastic search, log stash, and kibana. It’s picking up a lot of traction. Elastic Stack is extensible using X-PACK feature.
    • Grafana is best for visualizing time series database. Easy to get started and combine multiple backends. - - Grafana annotations easy to use and tag the events.
    • There is no one tool which fits everyone’s case. You have to start somewhere. So pick up a monitoring tool, see if it works for you else try the next one til you settle down.
  2. Deployment strategies with Kubernetes

    • This was talk with a live demo.
    • Canary deployment: Route a small amount of traffic to a new host to test functioning.
    • If new hosts don’t act normal roll back the deployment.
    • Blue Green Deployment is a procedure to minimize the downtime of the deployment. The idea is to have two set of machines with identical configuration but one with the latest code, rev 2 and other with rev 1. Once the machines with latest code act correctly, spin down the machines with rev 1 code.
    • Then a demo of kubectl with adding a new host to the cluster and roll back.
  3. A little bot for big cause

    • The talk is on a story on developing, push to GitHub, merge and release. And shit hits the fan. Now, what to do?
    • The problem is developer didn’t get the code reviewed.
    • How can automation help here?
    • Enforcing standard like I unreviewed merge is reverted using GitHub API, Slack Bot, Hubot.
    • As soon as developer opens a PR, alice, the bot adds a comment to the PR with the checklist. When the code is merged, bot verifies the checklist, if items are unchecked, the bot reverts the merge.
    • The bot can do more work. DM the bot in the slack to issue commands and bot can interact with Jenkins to roll back the deployed code.
    • The bot can receive commands via slack personal message.
  4. Necessary tooling and monitoring for performance critical applications

    • The talk is about collecting metrics for German E-commerce company Otto.
    • The company receives two orders/sec, million visitors per day.On an average, it takes eight clicks/pages to complete an order.
    • Monitor database, response time, throughput, requests/second, and measure state of the system
    • Metrics everywhere! We talk about metrics to decide and diagnose the problem.
    • Metrics is a Clojure library to measure and record the data to the external system.
    • The library offers various features like Counter, gauges, meters, timers, histogram percentile.
    • Rather than extracting data from the log file, measure details from the code and write to the data store.
    • Third party libraries are available for visualization.
    • The demo used d3.js application for annotation and visualization. In-house solution.
    • While measuring the metrics, measure from all possible places and store separately. If the web application makes a call to the recommendation engine, collect the metrics from the web application and recommendation for a single task and push to the data store.
  5. What should be PID 1 in a container?

    • In older version of Docker, Docker doesn’t reap child process correctly. As a result, for every request, docker spawns a new application and never terminated. This is called PID 1 zombie problem.
    • This will eat all available PIDs in the container.
    • Use Sysctl-a | grep pid_max to find maximum available PIDs in the container.
    • In the bare metal machine, PID 1 is systemd or any init program.
    • If the first process in the container is bash, then is PID 1 zombie process doesn’t occur.
    • Using bash is to handle all signal handlers is messy.
    • Yelp came up with Yelp/dumb-init. Now, dumb-init is PID 1 and no more zombie processes.
    • Docker-1.13, introduced the flag, --init.
    • Another solution uses system as PID 1
    • Docker allows running system without privilege mode.
    • Running system as PID 1 has other useful features like managing logs.
  6. ‘Razor’ sharp provision for bare metal servers

    • I attended only first half of the talk, fifteen minutes.
    • When you buy physical rack space in a data server how will you install the OS? You’re in Bangalore and server is in Amsterdam.
    • First OS installation on bare metal is hard.
    • There comes Network boot!
    • PXELinux is a syslinux derivative to boot OS from NIC card.
    • Once the machine comes up, DHCP request is broadcasted, and DHCP server responds.
    • Cobbler helps in managing all services running the network.
    • DHCP server, TFTP server, and config are required to complete the installation.
    • Microkernel in placed in TFTP server.
    • Razor is a tool to automate provisioning bare metal installation.
    • Razor philosophy, consume the hardware resource like the virtual resource.
    • Razor components - Nodes, Tags, Repository, policy, Brokers, Hooks
  7. FreeBSD is not a Linux distribution

    • FreeBSD is a complete OS, not a distribution
    • Who uses? NetFlix, WhatsApp, Yahoo!, NetApp and more
    • Great tools, mature release model, excellent documentation, friendly license.
    • Now a lot of forks NetBSD, FreeBSD, OpenBSD and few more
    • Good file system. UFS, and ZFS. UFS high performance and reliable. - If you don’t want to lose data use ZFS!
    • Jails - GNU/Linux copied this and called containers!
    • No GCC only llvm/clang.
    • FreeBSD is forefront in developing next generation tools.
    • Pluggable TCP stacks - BBR, RACK, CUBIC, NewReno
    • Firewalls - Ipfw , PF
    • Dummynet - live network emulation tool
    • FreeBSD can run Linux binaries in userspace. It maps GNU/Linux system call with FreeBSD.
    • It can run on 256 cores machine.
    • Hard Ware - NUMA, ARM64, Secure boot/UEFI
    • Politics - Democratically elected core team
    • Join the Mailing list and send patches, you will get a commit bit.
    • Excellent mentor program - GSoC copied our idea.
    • FreeBSD uses SVN and Git revision control.
    • Took a dig at GPLV2 and not a business friendly license.
    • Read out BSD license on the stage.

See also

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

powered by TinyLetter