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crazylion lee

Writing a Bootloader | Blog of Osanda - 1 views

osandamalith.wordpress.com/...writing-a-bootloader

bootloader linux c

shared by crazylion lee on 06 Nov 15 - No Cached
  • crazylion lee on 06 Nov 15
     
    "A bootloader is a special program that is executed each time a bootable device is initialized by the computer during its power on or reset that will load the kernel image into the memory. This application is very close to hardware and to the architecture of the CPU. All x86 PCs boot in Real Mode. In this mode you have only 16-bit instructions. Our bootloader runs in Real Mode and our bootloader is a 16-bit program."
張 旭

Active Record Basics - Ruby on Rails Guides - 0 views

guides.rubyonrails.org/active_record_basics.html

ruby rails programming development framework model database object

shared by 張 旭 on 22 Jan 14 - No Cached
  • the model - which is the layer of the system responsible for representing business data and logic.
  • Active Record facilitates the creation and use of business objects whose data requires persistent storage to a database
  • Database Table - Plural with underscores separating words
  • ...33 more annotations...
  • objects carry both persistent data and behavior which operates on that data
  • Object-Relational Mapping, commonly referred to as its abbreviation ORM, is a technique that connects the rich objects of an application to tables in a relational database management system
  • Represent associations between these models
  • Validate models before they get persisted to the database
  • The idea is that if you configure your applications in the very same way most of the times then this should be the default way.
  • Rails will pluralize your class names to find the respective database table.
  • use the ActiveRecord::Base.table_name= method to specify the table name
  • Model Class - Singular with the first letter of each word capitalized
  • Foreign keys - These fields should be named following the pattern singularized_table_name_id
  • Primary keys - By default, Active Record will use an integer column named id as the table's primary key
  • created_at
  • updated_at
  • (table_name)_count - Used to cache the number of belonging objects on associations.
  • Object Relational Mapping
  • Single Table Inheritance (STI)
  • rake db:rollback
  • ActiveRecord::Base.primary_key=
  • CRUD is an acronym for the four verbs we use to operate on data: Create, Read, Update and Delete.
  • new method will return a new object
  • create will return the object and save it to the database.
  • Using the new method, an object can be instantiated without being saved
  • user.save will commit the record to the database
  • update_all class method
  • an Active Record object can be destroyed which removes it from the database
  • Validation is a very important issue to consider when persisting to database, so the methods create, save and update take it into account when running: they return false when validation fails and they didn't actually perform any operation on database.
  • a bang counterpart
  • Active Record callbacks allow you to attach code to certain events in the life-cycle of your models
  • Rails keeps track of which files have been committed to the database and provides rollback features
  • rake db:migrate
  • class_name.yml
  • Convention over Configuration
    • 張 旭
      張 旭 on 12 Apr 16
       
      Model 是單數，Table 是複數。想象一下，處理 Object 的時候是逐一處理，但是存放的地方是放了一堆 Objects。
    • 張 旭
      張 旭 on 12 Apr 16
       
      外鍵是單數的形式，這也很好理解：因為關聯到的是一個外部的 Object
張 旭

Best practices for writing Dockerfiles | Docker Documentation - 0 views

docs.docker.com/...dockerfile_best-practices

docker system

shared by 張 旭 on 28 Sep 18 - No Cached
  • building efficient images
  • Docker builds images automatically by reading the instructions from a Dockerfile -- a text file that contains all commands, in order, needed to build a given image.
  • A Docker image consists of read-only layers each of which represents a Dockerfile instruction.
  • ...47 more annotations...
  • The layers are stacked and each one is a delta of the changes from the previous layer
  • When you run an image and generate a container, you add a new writable layer (the “container layer”) on top of the underlying layers.
  • By “ephemeral,” we mean that the container can be stopped and destroyed, then rebuilt and replaced with an absolute minimum set up and configuration.
  • Inadvertently including files that are not necessary for building an image results in a larger build context and larger image size.
  • To exclude files not relevant to the build (without restructuring your source repository) use a .dockerignore file. This file supports exclusion patterns similar to .gitignore files.
  • minimize image layers by leveraging build cache.
  • if your build contains several layers, you can order them from the less frequently changed (to ensure the build cache is reusable) to the more frequently changed
  • avoid installing extra or unnecessary packages just because they might be “nice to have.”
  • Each container should have only one concern.
  • Decoupling applications into multiple containers makes it easier to scale horizontally and reuse containers
  • Limiting each container to one process is a good rule of thumb, but it is not a hard and fast rule.
  • Use your best judgment to keep containers as clean and modular as possible.
  • do multi-stage builds and only copy the artifacts you need into the final image. This allows you to include tools and debug information in your intermediate build stages without increasing the size of the final image.
  • avoid duplication of packages and make the list much easier to update.
  • When building an image, Docker steps through the instructions in your Dockerfile, executing each in the order specified.
  • the next instruction is compared against all child images derived from that base image to see if one of them was built using the exact same instruction. If not, the cache is invalidated.
  • simply comparing the instruction in the Dockerfile with one of the child images is sufficient.
  • For the ADD and COPY instructions, the contents of the file(s) in the image are examined and a checksum is calculated for each file.
  • If anything has changed in the file(s), such as the contents and metadata, then the cache is invalidated.
  • cache checking does not look at the files in the container to determine a cache match.
  • In that case just the command string itself is used to find a match.
    • 張 旭
      張 旭 on 28 Sep 18
       
      RUN apt-get 這樣的指令，直接比對指令內容的意思。
  • Whenever possible, use current official repositories as the basis for your images.
  • Using RUN apt-get update && apt-get install -y ensures your Dockerfile installs the latest package versions with no further coding or manual intervention.
  • cache busting
  • Docker executes these commands using the /bin/sh -c interpreter, which only evaluates the exit code of the last operation in the pipe to determine success.
  • set -o pipefail && to ensure that an unexpected error prevents the build from inadvertently succeeding.
  • The CMD instruction should be used to run the software contained by your image, along with any arguments.
  • CMD should almost always be used in the form of CMD [“executable”, “param1”, “param2”…]
  • CMD should rarely be used in the manner of CMD [“param”, “param”] in conjunction with ENTRYPOINT
  • The ENV instruction is also useful for providing required environment variables specific to services you wish to containerize,
  • Each ENV line creates a new intermediate layer, just like RUN commands
  • COPY is preferred
  • COPY only supports the basic copying of local files into the container
  • the best use for ADD is local tar file auto-extraction into the image, as in ADD rootfs.tar.xz /
  • If you have multiple Dockerfile steps that use different files from your context, COPY them individually, rather than all at once.
  • using ADD to fetch packages from remote URLs is strongly discouraged; you should use curl or wget instead
  • The best use for ENTRYPOINT is to set the image’s main command, allowing that image to be run as though it was that command (and then use CMD as the default flags).
  • the image name can double as a reference to the binary as shown in the command
  • The VOLUME instruction should be used to expose any database storage area, configuration storage, or files/folders created by your docker container.
  • use VOLUME for any mutable and/or user-serviceable parts of your image
  • If you absolutely need functionality similar to sudo, such as initializing the daemon as root but running it as non-root), consider using “gosu”.
  • always use absolute paths for your WORKDIR
  • An ONBUILD command executes after the current Dockerfile build completes.
  • Think of the ONBUILD command as an instruction the parent Dockerfile gives to the child Dockerfile
  • A Docker build executes ONBUILD commands before any command in a child Dockerfile.
  • Be careful when putting ADD or COPY in ONBUILD. The “onbuild” image fails catastrophically if the new build’s context is missing the resource being added.
張 旭

Baseimage-docker: A minimal Ubuntu base image modified for Docker-friendliness - 0 views

phusion.github.io/baseimage-docker

docker base system linux

shared by 張 旭 on 29 Oct 14 - No Cached
  • We encourage you to use multiple processes.
  • Baseimage-docker is a special Docker image that is configured for correct use within Docker containers.
  • When your Docker container starts, only the CMD command is run.
  • ...16 more annotations...
  • You're not running them, you're only running your app.
  • You have Ubuntu installed in Docker. The files are there. But that doesn't mean Ubuntu's running as it should.
  • The only processes that will be running inside the container is the CMD command, and all processes that it spawns.
  • A proper Unix system should run all kinds of important system services.
  • Ubuntu is not designed to be run inside Docker
  • When a system is started, the first process in the system is called the init process, with PID 1. The system halts when this processs halts.
  • Runit (written in C) is much lighter weight than supervisord (written in Python).
  • Docker runs fine with multiple processes in a container.
  • Baseimage-docker encourages you to run multiple processes through the use of runit.
  • If your init process is your app, then it'll probably only shut down itself, not all the other processes in the container.
  • a Docker container, which is a locked down environment with e.g. no direct access to many kernel resources.
  • Used for service supervision and management.
  • A custom tool for running a command as another user.
  • add additional daemons (e.g. your own app) to the image by creating runit entries.
  • write a small shell script which runs your daemon, and runit will keep it up and running for you, restarting it when it crashes, etc.
  • the shell script must run the daemon without letting it daemonize/fork it.
張 旭

Scalable architecture without magic (and how to build it if you're not Google) - DEV Co... - 0 views

dev.to/...ld-it-if-youre-not-google-336a

development architecture system google

shared by 張 旭 on 24 Feb 19 - No Cached
  • Don’t mess up write-first and read-first databases.
  • keep them stateless.
  • you should know how to make a scalable setup on bare metal.
  • ...29 more annotations...
  • Different programming languages are for different tasks.
  • Go or C which are compiled to run on bare metal.
  • To run NodeJS on multiple cores, you have to use something like PM2, but since this you have to keep your code stateless.
  • Python have very rich and sugary syntax that’s great for working with data while keeping your code small and expressive.
  • SQL is almost always slower than NoSQL
  • databases are often read-first or write-first
  • write-first, just like Cassandra.
  • store all of your data to your databases and leave nothing at backend
  • Functional code is stateless by default
  • It’s better to go for stateless right from the very beginning.
  • deliver exactly the same responses for same requests.
  • Sessions? Store them at Redis and allow all of your servers to access it.
  • Only the first user will trigger a data query, and all others will be receiving exactly the same data straight from the RAM
  • never, never cache user input
  • Only the server output should be cached
  • Varnish is a great cache option that works with HTTP responses, so it may work with any backend.
  • a rate limiter – if there’s not enough time have passed since last request, the ongoing request will be denied.
  • different requests blasting every 10ms can bring your server down
  • Just set up entry relations and allow your database to calculate external keys for you
  • the query planner will always be faster than your backend.
  • Backend should have different responsibilities: hashing, building web pages from data and templates, managing sessions and so on.
  • For anything related to data management or data models, move it to your database as procedures or queries.
  • a distributed database.
  • your code has to be stateless
  • Move anything related to the data to the database.
  • For load-balancing a database, go for cluster.
  • DB is balancing requests, as well as your backend.
  • Users from different continents are separated with DNS.
  • Keep is scalable, keep is stateless.
  • 張 旭 on 24 Feb 19
     
    "Don't mess up write-first and read-first databases."
張 旭

What's the difference between Prometheus and Zabbix? - Stack Overflow - 0 views

stackoverflow.com/...-between-prometheus-and-zabbix

system monitor php go

shared by 張 旭 on 23 Apr 18 - No Cached
  • Zabbix has core written in C and webUI based on PHP
  • Zabbix stores data in RDBMS (MySQL, PostgreSQL, Oracle, sqlite) of user's choice.
  • Prometheus uses its own database embedded into backend process
  • ...8 more annotations...
  • Zabbix by default uses "pull" model when a server connects to agents on each monitoring machine, agents periodically gather the info and send it to a server.
  • Prometheus prefers "pull" model when a server gather info from client machines.
  • Prometheus requires an application to be instrumented with Prometheus client library (available in different programming languages) for preparing metrics.
  • expose metrics for Prometheus (similar to "agents" for Zabbix)
  • Zabbix uses its own tcp-based communication protocol between agents and a server.
  • Prometheus uses HTTP with protocol buffers (+ text format for ease of use with curl).
  • Prometheus offers basic tool for exploring gathered data and visualizing it in simple graphs on its native server and also offers a minimal dashboard builder PromDash. But Prometheus is and is designed to be supported by modern visualizing tools like Grafana.
  • Prometheus offers solution for alerting that is separated from its core into Alertmanager application.
張 旭

How To Use Bash's Job Control to Manage Foreground and Background Processes | DigitalOcean - 0 views

www.digitalocean.com/...round-and-background-processes

linux system server command

shared by 張 旭 on 06 Feb 18 - No Cached
  • Most processes that you start on a Linux machine will run in the foreground. The command will begin execution, blocking use of the shell for the duration of the process.
  • By default, processes are started in the foreground. Until the program exits or changes state, you will not be able to interact with the shell.
  • stop the process by sending it a signal
  • ...17 more annotations...
  • Linux terminals are usually configured to send the "SIGINT" signal (typically signal number 2) to current foreground process when the CTRL-C key combination is pressed.
  • Another signal that we can send is the "SIGTSTP" signal (typically signal number 20).
  • A background process is associated with the specific terminal that started it, but does not block access to the shell
  • start a background process by appending an ampersand character ("&") to the end of your commands.
  • type commands at the same time.
  • The [1] represents the command's "job spec" or job number. We can reference this with other job and process control commands, like kill, fg, and bg by preceding the job number with a percentage sign. In this case, we'd reference this job as %1.
  • Once the process is stopped, we can use the bg command to start it again in the background
  • By default, the bg command operates on the most recently stopped process.
  • Whether a process is in the background or in the foreground, it is rather tightly tied with the terminal instance that started it
  • When a terminal closes, it typically sends a SIGHUP signal to all of the processes (foreground, background, or stopped) that are tied to the terminal.
  • a terminal multiplexer
  • start it using the nohup command
  • appending output to ‘nohup.out’
  • pgrep -a
  • The disown command, in its default configuration, removes a job from the jobs queue of a terminal.
  • You can pass the -h flag to the disown process instead in order to mark the process to ignore SIGHUP signals, but to otherwise continue on as a regular job
  • The huponexit shell option controls whether bash will send its child processes the SIGHUP signal when it exits.
張 旭

How to Benchmark Performance of MySQL & MariaDB Using SysBench | Severalnines - 1 views

severalnines.com/...e-mysql-mariadb-using-sysbench

database mysql performance

shared by 張 旭 on 22 Oct 20 - No Cached
  • SysBench is a C binary which uses LUA scripts to execute benchmarks
  • support for parallelization in the LUA scripts, multiple queries can be executed in parallel
  • by default, benchmarks which cover most of the cases - OLTP workloads, read-only or read-write, primary key lookups and primary key updates.
  • ...21 more annotations...
  • SysBench is not a tool which you can use to tune configurations of your MySQL servers (unless you prepared LUA scripts with custom workload or your workload happen to be very similar to the benchmark workloads that SysBench comes with)
  • it is great for is to compare performance of different hardware.
  • Every new server acquired should go through a warm-up period during which you will stress it to pinpoint potential hardware defects
  • by executing OLTP workload which overloads the server, or you can also use dedicated benchmarks for CPU, disk and memory.
  • bulk_insert.lua. This test can be used to benchmark the ability of MySQL to perform multi-row inserts.
  • All oltp_* scripts share a common table structure. First two of them (oltp_delete.lua and oltp_insert.lua) execute single DELETE and INSERT statements.
  • oltp_point_select, oltp_update_index and oltp_update_non_index. These will execute a subset of queries - primary key-based selects, index-based updates and non-index-based updates.
  • you can run different workload patterns using the same benchmark.
  • Warmup helps to identify “regular” throughput by executing benchmark for a predefined time, allowing to warm up the cache, buffer pools etc.
  • By default SysBench will attempt to execute queries as fast as possible. To simulate slower traffic this option may be used. You can define here how many transactions should be executed per second.
  • SysBench gives you ability to generate different types of data distribution.
  • decide if SysBench should use prepared statements (as long as they are available in the given datastore - for MySQL it means PS will be enabled by default) or not.
  • sysbench ./sysbench/src/lua/oltp_read_write.lua  help
  • By default, SysBench will attempt to execute queries in explicit transaction. This way the dataset will stay consistent and not affected: SysBench will, for example, execute INSERT and DELETE on the same row, making sure the data set will not grow (impacting your ability to reproduce results).
  • specify error codes from MySQL which SysBench should ignore (and not kill the connection).
  • the two most popular benchmarks - OLTP read only and OLTP read/write.
  • 1 million rows will result in ~240 MB of data. Ten tables, 1000 000 rows each equals to 2.4GB
  • by default, SysBench looks for ‘sbtest’ schema which has to exist before you prepare the data set. You may have to create it manually.
  • pass ‘--histogram’ argument to SysBench
  • ~48GB of data (20 tables, 10 000 000 rows each).
  • if you don’t understand why the performance was like it was, you may draw incorrect conclusions out of the benchmarks.
張 旭

Cluster Networking - Kubernetes - 0 views

kubernetes.io/...networking

kubernetes networking network system

shared by 張 旭 on 08 Jul 19 - No Cached
  • Networking is a central part of Kubernetes, but it can be challenging to understand exactly how it is expected to work
  • Highly-coupled container-to-container communications
  • Pod-to-Pod communications
  • ...57 more annotations...
  • this is the primary focus of this document
    • 張 旭
      張 旭 on 27 Aug 21
       
      Cluster Networking 所關注處理的是： Pod 到 Pod 之間的連線
  • Pod-to-Service communications
  • External-to-Service communications
  • Kubernetes is all about sharing machines between applications.
  • sharing machines requires ensuring that two applications do not try to use the same ports.
  • Dynamic port allocation brings a lot of complications to the system
  • Every Pod gets its own IP address
  • do not need to explicitly create links between Pods
  • almost never need to deal with mapping container ports to host ports.
  • Pods can be treated much like VMs or physical hosts from the perspectives of port allocation, naming, service discovery, load balancing, application configuration, and migration.
  • pods on a node can communicate with all pods on all nodes without NAT
  • agents on a node (e.g. system daemons, kubelet) can communicate with all pods on that node
  • pods in the host network of a node can communicate with all pods on all nodes without NAT
  • If your job previously ran in a VM, your VM had an IP and could talk to other VMs in your project. This is the same basic model.
  • containers within a Pod share their network namespaces - including their IP address
  • containers within a Pod can all reach each other’s ports on localhost
  • containers within a Pod must coordinate port usage
  • “IP-per-pod” model.
  • request ports on the Node itself which forward to your Pod (called host ports), but this is a very niche operation
  • The Pod itself is blind to the existence or non-existence of host ports.
  • AOS is an Intent-Based Networking system that creates and manages complex datacenter environments from a simple integrated platform.
  • Cisco Application Centric Infrastructure offers an integrated overlay and underlay SDN solution that supports containers, virtual machines, and bare metal servers.
  • AOS Reference Design currently supports Layer-3 connected hosts that eliminate legacy Layer-2 switching problems.
  • The AWS VPC CNI offers integrated AWS Virtual Private Cloud (VPC) networking for Kubernetes clusters.
  • users can apply existing AWS VPC networking and security best practices for building Kubernetes clusters.
  • Using this CNI plugin allows Kubernetes pods to have the same IP address inside the pod as they do on the VPC network.
  • The CNI allocates AWS Elastic Networking Interfaces (ENIs) to each Kubernetes node and using the secondary IP range from each ENI for pods on the node.
  • Big Cloud Fabric is a cloud native networking architecture, designed to run Kubernetes in private cloud/on-premises environments.
  • Cilium is L7/HTTP aware and can enforce network policies on L3-L7 using an identity based security model that is decoupled from network addressing.
  • CNI-Genie is a CNI plugin that enables Kubernetes to simultaneously have access to different implementations of the Kubernetes network model in runtime.
  • CNI-Genie also supports assigning multiple IP addresses to a pod, each from a different CNI plugin.
  • cni-ipvlan-vpc-k8s contains a set of CNI and IPAM plugins to provide a simple, host-local, low latency, high throughput, and compliant networking stack for Kubernetes within Amazon Virtual Private Cloud (VPC) environments by making use of Amazon Elastic Network Interfaces (ENI) and binding AWS-managed IPs into Pods using the Linux kernel’s IPvlan driver in L2 mode.
  • to be straightforward to configure and deploy within a VPC
  • Contiv provides configurable networking
  • Contrail, based on Tungsten Fabric, is a truly open, multi-cloud network virtualization and policy management platform.
  • DANM is a networking solution for telco workloads running in a Kubernetes cluster.
  • Flannel is a very simple overlay network that satisfies the Kubernetes requirements.
  • Any traffic bound for that subnet will be routed directly to the VM by the GCE network fabric.
  • sysctl net.ipv4.ip_forward=1
  • Jaguar provides overlay network using vxlan and Jaguar CNIPlugin provides one IP address per pod.
  • Knitter is a network solution which supports multiple networking in Kubernetes.
  • Kube-OVN is an OVN-based kubernetes network fabric for enterprises.
  • Kube-router provides a Linux LVS/IPVS-based service proxy, a Linux kernel forwarding-based pod-to-pod networking solution with no overlays, and iptables/ipset-based network policy enforcer.
  • If you have a “dumb” L2 network, such as a simple switch in a “bare-metal” environment, you should be able to do something similar to the above GCE setup.
  • Multus is a Multi CNI plugin to support the Multi Networking feature in Kubernetes using CRD based network objects in Kubernetes.
  • NSX-T can provide network virtualization for a multi-cloud and multi-hypervisor environment and is focused on emerging application frameworks and architectures that have heterogeneous endpoints and technology stacks.
  • NSX-T Container Plug-in (NCP) provides integration between NSX-T and container orchestrators such as Kubernetes
  • Nuage uses the open source Open vSwitch for the data plane along with a feature rich SDN Controller built on open standards.
  • OpenVSwitch is a somewhat more mature but also complicated way to build an overlay network
  • OVN is an opensource network virtualization solution developed by the Open vSwitch community.
  • Project Calico is an open source container networking provider and network policy engine.
  • Calico provides a highly scalable networking and network policy solution for connecting Kubernetes pods based on the same IP networking principles as the internet
  • Calico can be deployed without encapsulation or overlays to provide high-performance, high-scale data center networking.
  • Calico can also be run in policy enforcement mode in conjunction with other networking solutions such as Flannel, aka canal, or native GCE, AWS or Azure networking.
  • Romana is an open source network and security automation solution that lets you deploy Kubernetes without an overlay network
  • Weave Net runs as a CNI plug-in or stand-alone. In either version, it doesn’t require any configuration or extra code to run, and in both cases, the network provides one IP address per pod - as is standard for Kubernetes.
  • The network model is implemented by the container runtime on each node.
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