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張 旭

DNS Records: An Introduction - 0 views

www.linode.com/...dns-records-an-introduction

dns networking system

shared by 張 旭 on 28 Aug 19 - No Cached
  • Domain names are best understood by reading from right to left.
  • the top-level domain, or TLD
  • Every term to the left of the TLD is separated by a period and considered a more specific subdomain
  • ...40 more annotations...
  • Name servers host a domain’s DNS information in a text file called a zone file.
  • Start of Authority (SOA) records
  • specifying DNS records, which match domain names to IP addresses.
  • Every domain’s zone file contains the domain administrator’s email address, the name servers, and the DNS records.
  • Your ISP’s DNS resolver queries a root nameserver for the proper TLD nameserver. In other words, it asks the root nameserver, *Where can I find the nameserver for .com domains?*
  • In actuality, ISPs cache a lot of DNS information after they’ve looked it up the first time.
  • caching is a good thing, but it can be a problem if you’ve recently made a change to your DNS information
  • An A record points your domain or subdomain to your Linode’s IP address,
  • use an asterisk (*) as your subdomain
  • An AAAA record is just like an A record, but for IPv6 IP addresses.
  • An AXFR record is a type of DNS record used for DNS replication
  • DNS Certification Authority Authorization uses DNS to allow the holder of a domain to specify which certificate authorities are allowed to issue certificates for that domain.
  • A CNAME record or Canonical Name record matches a domain or subdomain to a different domain.
  • Some mail servers handle mail oddly for domains with CNAME records, so you should not use a CNAME record for a domain that gets email.
  • MX records cannot reference CNAME-defined hostnames.
  • Chaining or looping CNAME records is not recommended.
  • a CNAME record does not function the same way as a URL redirect.
  • A DKIM record or DomainKeys Identified Mail record displays the public key for authenticating messages that have been signed with the DKIM protocol
  • DKIM records are implemented as text records.
  • An MX record or mail exchanger record sets the mail delivery destination for a domain or subdomain.
  • An MX record should ideally point to a domain that is also the hostname for its server.
  • Priority allows you to designate a fallback server (or servers) for mail for a particular domain. Lower numbers have a higher priority.
  • NS records or name server records set the nameservers for a domain or subdomain.
  • You can also set up different nameservers for any of your subdomains
  • Primary nameservers get configured at your registrar and secondary subdomain nameservers get configured in the primary domain’s zone file.
  • The order of NS records does not matter. DNS requests are sent randomly to the different servers
  • A PTR record or pointer record matches up an IP address to a domain or subdomain, allowing reverse DNS queries to function.
  • opposite service an A record does
  • PTR records are usually set with your hosting provider. They are not part of your domain’s zone file.
  • An SOA record or Start of Authority record labels a zone file with the name of the host where it was originally created.
  • Minimum TTL: The minimum amount of time other servers should keep data cached from this zone file.
  • An SPF record or Sender Policy Framework record lists the designated mail servers for a domain or subdomain.
  • An SPF record for your domain tells other receiving mail servers which outgoing server(s) are valid sources of email so they can reject spoofed mail from your domain that has originated from unauthorized servers.
  • Make sure your SPF records are not too strict.
  • An SRV record or service record matches up a specific service that runs on your domain or subdomain to a target domain.
  • Service: The name of the service must be preceded by an underscore (_) and followed by a period (.)
  • Protocol: The name of the protocol must be proceeded by an underscore (_) and followed by a period (.)
  • Port: The TCP or UDP port on which the service runs.
  • Target: The target domain or subdomain. This domain must have an A or AAAA record that resolves to an IP address.
  • A TXT record or text record provides information about the domain in question to other resources on the internet.
  • 張 旭 on 28 Aug 19
     
    "Domain names are best understood by reading from right to left."
張 旭

vSphere Cloud Provider | vSphere Storage for Kubernetes - 0 views

vmware.github.io/...overview.html

docker container storage volume vmware

shared by 張 旭 on 30 Jul 19 - No Cached
  • Containers are stateless and ephemeral but applications are stateful and need persistent storage.
  • Cloud Provider
  • Kubernetes cloud providers are an interface to integrate various node (i.e. hosts), load balancers and networking routes
  • ...8 more annotations...
  • VMware offers a Cloud Provider known as the vSphere Cloud Provider (VCP) for Kubernetes which allows Pods to use enterprise grade persistent storage.
  • A vSphere datastore is an abstraction which hides storage details (such as LUNs) and provides a uniform interface for storing persistent data.
  • the datastores can be of the type vSAN, VMFS, NFS & VVol.
  • VMFS (Virtual Machine File System) is a cluster file system that allows virtualization to scale beyond a single node for multiple VMware ESX servers.
  • NFS (Network File System) is a distributed file protocol to access storage over network like local storage.
  • vSphere Cloud Provider supports every storage primitive exposed by Kubernetes
  • Kubernetes PVs are defined in Pod specifications.
  • PVCs when using Dynamic Provisioning (preferred).
張 旭

- 0 views

dev.to/...lized-useful-git-commands-37p1

git programming code

shared by 張 旭 on 07 May 20 - No Cached
  • A fast-forward merge can happen when the current branch has no extra commits compared to the branch we’re merging.
  • With a no-fast-forward merge, Git creates a new merging commit on the active branch.
  • We can manually remove the changes we don't want to keep, save the changes, add the changed file again, and commit the changes
  • ...14 more annotations...
  • A git rebase copies the commits from the current branch, and puts these copied commits on top of the specified branch.
  • The branch that we're rebasing always has the latest changes that we want to keep!
  • A git rebase changes the history of the project as new hashes are created for the copied commits!
  • Rebasing is great whenever you're working on a feature branch, and the master branch has been updated.
  • An interactive rebase can also be useful on the branch you're currently working on, and want to modify some commits.
  • A git reset gets rid of all the current staged files and gives us control over where HEAD should point to.
  • A soft reset moves HEAD to the specified commit (or the index of the commit compared to HEAD)
  • Git should simply reset its state back to where it was on the specified commit: this even includes the changes in your working directory and staged files!
  • By reverting a certain commit, we create a new commit that contains the reverted changes!
  • Performing a git revert is very useful in order to undo a certain commit, without modifying the history of the branch.
  • By cherry-picking a commit, we create a new commit on our active branch that contains the changes that were introduced by the cherry-picked commit.
  • a fetch simply downloads new data.
  • A git pull is actually two commands in one: a git fetch, and a git merge
  • git reflog is a very useful command in order to show a log of all the actions that have been taken
張 旭

MySQL :: MySQL 5.7 Reference Manual :: 20.2 Introducing InnoDB Cluster - 0 views

dev.mysql.com/...nodb-cluster-introduction.html

mysql cluster database HA

shared by 張 旭 on 19 Mar 17 - No Cached
  • A group of MySQL servers can be configured to create a cluster using MySQL Shell
  • The cluster of servers has a single master, called the primary, which acts as the read-write master.
  • Multiple secondary servers are replicas of the master
  • ...6 more annotations...
  • A client application is connected to the primary via MySQL Router
  • MySQL Shell also requires Python 2.7 and above to run cluster provisioning scripts
  • AdminAPI, which enables you to create and administer an InnoDB cluster, using either JavaScript or Python scripting
  • Caches the metadata of the InnoDB cluster and performs high availability routing to the MySQL Server instances which make up the cluster
  • Group Replication mechanism to allow data to be replicated from the primary to the secondaries in the cluster
  • AdminAPI is available as of MySQL Shell 1.0.8.
張 旭

MySQL :: MySQL 5.7 Reference Manual :: 20.4 Getting Started with InnoDB Cluster - 0 views

dev.mysql.com/...b-cluster-getting-started.html

mysql cluster HA router database

shared by 張 旭 on 19 Mar 17 - No Cached
  • InnoDB cluster instances are created and managed through the MySQL Shell.
  • To create a new InnoDB cluster, the MySQL Shell must be connected to the MySQL Server instance. By default, this MySQL Server instance is the seed instance of the new InnoDB cluster and hold the initial data set.
  • Sandbox instance are only suitable for deploying and running on your local machine.
  • ...3 more annotations...
  • A minimum of three instances are required to create an InnoDB cluster
  • reverts to read-only mode
  • MySQL Shell provides two scripting languages: JavaScript and Python.
張 旭

MySQL :: MySQL 5.7 Reference Manual :: 19.1 Group Replication Background - 0 views

dev.mysql.com/...up-replication-background.html

mysql cluster HA system database replication

shared by 張 旭 on 19 Mar 17 - No Cached
  • the component can be removed and the system should continue to operate as expected
  • network partitioning
  • split brain scenarios
  • ...8 more annotations...
  • the ultimate challenge is to fuse the logic of the database and data replication with the logic of having several servers coordinated in a consistent and simple way
  • MySQL Group Replication provides distributed state machine replication with strong coordination between servers.
  • Servers coordinate themselves automatically when they are part of the same group
  • The group can operate in a single-primary mode with automatic primary election, where only one server accepts updates at a time.
  • For a transaction to commit, the majority of the group have to agree on the order of a given transaction in the global sequence of transactions
  • Deciding to commit or abort a transaction is done by each server individually, but all servers make the same decision
  • group communication protocols
  • the Paxos algorithm. It acts as the group communication systems engine.
張 旭

MySQL :: MySQL 5.7 Reference Manual :: 19.1.1.2 Group Replication - 0 views

dev.mysql.com/...group-replication-summary.html

mysql HA system database replication

shared by 張 旭 on 19 Mar 17 - No Cached
  • The replication group is a set of servers that interact with each other through message passing.
  • The communication layer provides a set of guarantees such as atomic message and total order message delivery.
  • a multi-master update everywhere replication protocol
  • ...8 more annotations...
  • a replication group is formed by multiple servers and each server in the group may execute transactions independently
  • Read-only (RO) transactions need no coordination within the group and thus commit immediately
  • any RW transaction the group needs to decide whether it commits or not, thus the commit operation is not a unilateral decision from the originating server
  • when a transaction is ready to commit at the originating server, the server atomically broadcasts the write values (rows changed) and the correspondent write set (unique identifiers of the rows that were updated). Then a global total order is established for that transaction.
  • all servers receive the same set of transactions in the same order
  • The resolution procedure states that the transaction that was ordered first commits on all servers, whereas the transaction ordered second aborts, and thus is rolled back on the originating server and dropped by the other servers in the group. This is in fact a distributed first commit wins rule
  • Group Replication is a shared-nothing replication scheme where each server has its own entire copy of the data
  • MySQL Group Replication protocol
張 旭

Automated Nginx Reverse Proxy for Docker - 0 views

jasonwilder.com/...nginx-reverse-proxy-for-docker

docker nginx proxy haproxy system web server

shared by 張 旭 on 04 Dec 15 - No Cached
  • Docker containers are assigned random IPs and ports which makes addressing them much more complicated from a client perspsective
  • Binding the container to the hosts port can prevent multiple containers from running on the same host. For example, only one container can bind to port 80 at a time.
  • Docker provides a remote API to inspect containers and access their IP, Ports and other configuration meta-data.
  • ...1 more annotation...
  • nginx template can be used to generate a reverse proxy configuration for docker containers using virtual hosts for routing.
張 旭

Introducing Infrastructure as Code | Linode - 0 views

www.linode.com/...tion-to-infrastructure-as-code

devops server infrastructure

shared by 張 旭 on 14 Apr 21 - No Cached
  • Infrastructure as Code (IaC) is a technique for deploying and managing infrastructure using software, configuration files, and automated tools.
  • With the older methods, technicians must configure a device manually, perhaps with the aid of an interactive tool. Information is added to configuration files by hand or through the use of ad-hoc scripts. Configuration wizards and similar utilities are helpful, but they still require hands-on management. A small group of experts owns the expertise, the process is typically poorly defined, and errors are common.
  • The development of the continuous integration and continuous delivery (CI/CD) pipeline made the idea of treating infrastructure as software much more attractive.
  • ...20 more annotations...
  • Infrastructure as Code takes advantage of the software development process, making use of quality assurance and test automation techniques.
  • Consistency/Standardization
  • Each node in the network becomes what is known as a snowflake, with its own unique settings. This leads to a system state that cannot easily be reproduced and is difficult to debug.
  • With standard configuration files and software-based configuration, there is greater consistency between all equipment of the same type. A key IaC concept is idempotence.
  • Idempotence makes it easy to troubleshoot, test, stabilize, and upgrade all the equipment.
  • Infrastructure as Code is central to the culture of DevOps, which is a mix of development and operations
  • edits are always made to the source configuration files, never on the target.
  • A declarative approach describes the final state of a device, but does not mandate how it should get there. The specific IaC tool makes all the procedural decisions. The end state is typically defined through a configuration file, a JSON specification, or a similar encoding.
  • An imperative approach defines specific functions or procedures that must be used to configure the device. It focuses on what must happen, but does not necessarily describe the final state. Imperative techniques typically use scripts for the implementation.
  • With a push configuration, the central server pushes the configuration to the destination device.
  • If a device is mutable, its configuration can be changed while it is active
  • Immutable devices cannot be changed. They must be decommissioned or rebooted and then completely rebuilt.
  • an immutable approach ensures consistency and avoids drift. However, it usually takes more time to remove or rebuild a configuration than it does to change it.
  • System administrators should consider security issues as part of the development process.
  • Ansible is a very popular open source IaC application from Red Hat
  • Ansible is often used in conjunction with Kubernetes and Docker.
  • Linode offers a collection of several Ansible guides for a more comprehensive overview.
  • Pulumi permits the use of a variety of programming languages to deploy and manage infrastructure within a cloud environment.
  • Terraform allows users to provision data center infrastructure using either JSON or Terraform’s own declarative language.
  • Terraform manages resources through the use of providers, which are similar to APIs.
張 旭

Custom Resources | Kubernetes - 0 views

kubernetes.io/...custom-resources

kubernetes

shared by 張 旭 on 11 May 21 - No Cached
  • Custom resources are extensions of the Kubernetes API
  • A resource is an endpoint in the Kubernetes API that stores a collection of API objects of a certain kind
  • Custom resources can appear and disappear in a running cluster through dynamic registration
  • ...30 more annotations...
  • Once a custom resource is installed, users can create and access its objects using kubectl
  • When you combine a custom resource with a custom controller, custom resources provide a true declarative API.
  • A declarative API allows you to declare or specify the desired state of your resource and tries to keep the current state of Kubernetes objects in sync with the desired state.
  • Custom controllers can work with any kind of resource, but they are especially effective when combined with custom resources.
  • The Operator pattern combines custom resources and custom controllers.
  • the API represents a desired state, not an exact state.
  • define configuration of applications or infrastructure.
  • The main operations on the objects are CRUD-y (creating, reading, updating and deleting).
  • The client says "do this", and then gets an operation ID back, and has to check a separate Operation object to determine completion of the request.
  • The natural operations on the objects are not CRUD-y.
  • High bandwidth access (10s of requests per second sustained) needed.
  • Use a ConfigMap if any of the following apply
  • You want to put the entire config file into one key of a configMap.
  • You want to perform rolling updates via Deployment, etc., when the file is updated.
  • Use a secret for sensitive data, which is similar to a configMap but more secure.
  • You want to build new automation that watches for updates on the new object, and then CRUD other objects, or vice versa.
  • You want the object to be an abstraction over a collection of controlled resources, or a summarization of other resources.
  • CRDs are simple and can be created without any programming.
  • Aggregated APIs are subordinate API servers that sit behind the primary API server
  • CRDs allow users to create new types of resources without adding another API server
  • Defining a CRD object creates a new custom resource with a name and schema that you specify.
  • The name of a CRD object must be a valid DNS subdomain name
  • each resource in the Kubernetes API requires code that handles REST requests and manages persistent storage of objects.
  • The main API server delegates requests to you for the custom resources that you handle, making them available to all of its clients.
  • The new endpoints support CRUD basic operations via HTTP and kubectl
  • Custom resources consume storage space in the same way that ConfigMaps do.
  • Aggregated API servers may use the same storage as the main API server
  • CRDs always use the same authentication, authorization, and audit logging as the built-in resources of your API server.
  • most RBAC roles will not grant access to the new resources (except the cluster-admin role or any role created with wildcard rules).
  • CRDs and Aggregated APIs often come bundled with new role definitions for the types they add.
張 旭

Logging Architecture | Kubernetes - 0 views

kubernetes.io/...logging

kubernetes log

shared by 張 旭 on 27 May 21 - No Cached
  • Application logs can help you understand what is happening inside your application
  • container engines are designed to support logging.
  • The easiest and most adopted logging method for containerized applications is writing to standard output and standard error streams.
  • ...26 more annotations...
  • In a cluster, logs should have a separate storage and lifecycle independent of nodes, pods, or containers. This concept is called cluster-level logging.
  • Cluster-level logging architectures require a separate backend to store, analyze, and query logs
  • Kubernetes does not provide a native storage solution for log data.
  • use kubectl logs --previous to retrieve logs from a previous instantiation of a container.
  • A container engine handles and redirects any output generated to a containerized application's stdout and stderr streams
  • The Docker JSON logging driver treats each line as a separate message.
  • By default, if a container restarts, the kubelet keeps one terminated container with its logs.
  • An important consideration in node-level logging is implementing log rotation, so that logs don't consume all available storage on the node
  • You can also set up a container runtime to rotate an application's logs automatically.
  • The two kubelet flags container-log-max-size and container-log-max-files can be used to configure the maximum size for each log file and the maximum number of files allowed for each container respectively.
  • The kubelet and container runtime do not run in containers.
  • On machines with systemd, the kubelet and container runtime write to journald. If systemd is not present, the kubelet and container runtime write to .log files in the /var/log directory.
  • System components inside containers always write to the /var/log directory, bypassing the default logging mechanism.
  • Kubernetes does not provide a native solution for cluster-level logging
  • Use a node-level logging agent that runs on every node.
  • implement cluster-level logging by including a node-level logging agent on each node.
  • the logging agent is a container that has access to a directory with log files from all of the application containers on that node.
  • the logging agent must run on every node, it is recommended to run the agent as a DaemonSet
  • Node-level logging creates only one agent per node and doesn't require any changes to the applications running on the node.
  • Containers write stdout and stderr, but with no agreed format. A node-level agent collects these logs and forwards them for aggregation.
  • Each sidecar container prints a log to its own stdout or stderr stream.
  • It is not recommended to write log entries with different formats to the same log stream
  • writing logs to a file and then streaming them to stdout can double disk usage.
  • If you have an application that writes to a single file, it's recommended to set /dev/stdout as the destination
  • it's recommended to use stdout and stderr directly and leave rotation and retention policies to the kubelet.
  • Using a logging agent in a sidecar container can lead to significant resource consumption. Moreover, you won't be able to access those logs using kubectl logs because they are not controlled by the kubelet.
張 旭

Upgrading kubeadm clusters | Kubernetes - 0 views

kubernetes.io/...kubeadm-upgrade

kubernetes system

shared by 張 旭 on 02 Jun 21 - No Cached
  • Swap must be disabled.
  • read the release notes carefully.
  • back up any important components, such as app-level state stored in a database.
  • ...16 more annotations...
  • All containers are restarted after upgrade, because the container spec hash value is changed.
  • The upgrade procedure on control plane nodes should be executed one node at a time.
  • /etc/kubernetes/admin.conf
  • kubeadm upgrade also automatically renews the certificates that it manages on this node. To opt-out of certificate renewal the flag --certificate-renewal=false can be used.
  • Manually upgrade your CNI provider plugin.
  • sudo systemctl daemon-reload sudo systemctl restart kubelet
  • If kubeadm upgrade fails and does not roll back, for example because of an unexpected shutdown during execution, you can run kubeadm upgrade again.
  • To recover from a bad state, you can also run kubeadm upgrade apply --force without changing the version that your cluster is running.
  • kubeadm-backup-etcd contains a backup of the local etcd member data for this control plane Node.
  • the contents of this folder can be manually restored in /var/lib/etcd
  • kubeadm-backup-manifests contains a backup of the static Pod manifest files for this control plane Node.
  • the contents of this folder can be manually restored in /etc/kubernetes/manifests
  • Enforces the version skew policies.
  • Upgrades the control plane components or rollbacks if any of them fails to come up.
  • Creates new certificate and key files of the API server and backs up old files if they're about to expire in 180 days.
  • backup folders under /etc/kubernetes/tmp
張 旭

ALB vs ELB | Differences Between an ELB and an ALB on AWS | Sumo Logic - 0 views

www.sumologic.com/...aws-elb-alb

aws HA proxy

shared by 張 旭 on 06 Apr 21 - No Cached
  • If you use AWS, you have two load-balancing options: ELB and ALB.
  • An ELB is a software-based load balancer which can be set up and configured in front of a collection of AWS Elastic Compute (EC2) instances.
  • The load balancer serves as a single entry point for consumers of the EC2 instances and distributes incoming traffic across all machines available to receive requests.
  • ...14 more annotations...
  • the ELB also performs a vital role in improving the fault tolerance of the services which it fronts.
  • he Open Systems Interconnection Model, or OSI Model, is a conceptual model which is used to facilitate communications between different computing systems.
  • Layer 1 is the physical layer, and represents the physical medium across which the request is sent.
  • Layer 2 describes the data link layer
  • Layer 3 (the network layer)
  • Layer 7, which serves the application layer.
  • The Classic ELB operates at Layer 4. Layer 4 represents the transport layer, and is controlled by the protocol being used to transmit the request.
  • A network device, of which the Classic ELB is an example, reads the protocol and port of the incoming request, and then routes it to one or more backend servers.
  • the ALB operates at Layer 7. Layer 7 represents the application layer, and as such allows for the redirection of traffic based on the content of the request.
  • Whereas a request to a specific URL backed by a Classic ELB would only enable routing to a particular pool of homogeneous servers, the ALB can route based on the content of the URL, and direct to a specific subgroup of backing servers existing in a heterogeneous collection registered with the load balancer.
  • The Classic ELB is a simple load balancer, is easy to configure
  • As organizations move towards microservice architecture or adopt a container-based infrastructure, the ability to merely map a single address to a specific service becomes more complicated and harder to maintain.
  • the ALB manages routing based on user-defined rules.
  • oute traffic to different services based on either the host or the content of the path contained within that URL.
張 旭

Best practices for building Kubernetes Operators and stateful apps | Google Cloud Blog - 0 views

cloud.google.com/...es-operators-and-stateful-apps

kubernetes system operator

shared by 張 旭 on 17 May 21 - No Cached
  • use the StatefulSet workload controller to maintain identity for each of the pods, and to use Persistent Volumes to persist data so it can survive a service restart.
  • a way to extend Kubernetes functionality with application specific logic using custom resources and custom controllers.
  • An Operator can automate various features of an application, but it should be specific to a single application
  • ...12 more annotations...
  • Kubebuilder is a comprehensive development kit for building and publishing Kubernetes APIs and Controllers using CRDs
  • Design declarative APIs for operators, not imperative APIs. This aligns well with Kubernetes APIs that are declarative in nature.
  • With declarative APIs, users only need to express their desired cluster state, while letting the operator perform all necessary steps to achieve it.
  • scaling, backup, restore, and monitoring. An operator should be made up of multiple controllers that specifically handle each of the those features.
  • the operator can have a main controller to spawn and manage application instances, a backup controller to handle backup operations, and a restore controller to handle restore operations.
  • each controller should correspond to a specific CRD so that the domain of each controller's responsibility is clear.
  • If you keep a log for every container, you will likely end up with unmanageable amount of logs.
  • integrate application-specific details to the log messages such as adding a prefix for the application name.
  • you may have to use external logging tools such as Google Stackdriver, Elasticsearch, Fluentd, or Kibana to perform the aggregations.
  • adding labels to metrics to facilitate aggregation and analysis by monitoring systems.
  • a more viable option is for application pods to expose a metrics HTTP endpoint for monitoring tools to scrape.
  • A good way to achieve this is to use open-source application-specific exporters for exposing Prometheus-style metrics.
張 旭

第 05 章 - 計算機概論 - 主機系統與 I/O 界面 - 0 views

dic.vbird.tw/...2020unit05.php

shared by 張 旭 on 21 Jun 21 - No Cached
  • 接受使用者輸入指令與資料，經由中央處理器的數學與邏輯單元運算處理後，以產生或儲存成有用的資訊
  • CPU 為一個具有特定功能的晶片， 裡頭含有微指令集，如果你想要讓主機進行什麼特異的功能，就得要參考這顆 CPU 是否有相關內建的微指令集才可以。
  • CPU 讀取的資料都是從主記憶體來的！ 主記憶體內的資料則是從輸入單元所傳輸進來！而 CPU 處理完畢的資料也必須要先寫回主記憶體中，最後資料才從主記憶體傳輸到輸出單元。
  • ...49 more annotations...
  • 算數邏輯單元與控制單元。其中算數邏輯單元主要負責程式運算與邏輯判斷，控制單元則主要在協調各周邊元件與各單元間的工作。
  • 資料會先寫入到主記憶體，然後 CPU 才能開始應用
  • CPU 其實內部已經含有一些微指令，我們所使用的軟體都要經過 CPU 內部的微指令集來達成才行。
  • 世界上常見到的兩種主要 CPU 架構， 分別是：精簡指令集 (RISC) 與複雜指令集 (CISC) 系統。
  • 微指令集較為精簡，每個指令的執行時間都很短，完成的動作也很單純，指令的執行效能較佳； 但是若要做複雜的事情，就要由多個指令來完成。
  • CISC在微指令集的每個小指令可以執行一些較低階的硬體操作，指令數目多而且複雜， 每條指令的長度並不相同。因為指令執行較為複雜所以每條指令花費的時間較長， 但每條個別指令可以處理的工作較為豐富。
  • 最早的那顆Intel發展出來的CPU代號稱為8086
  • AMD依此架構修改新一代的CPU為64位元
  • CPU 位元指的是CPU一次資料讀取的最大量！64位元CPU代表CPU一次可以讀寫64bits這麼多的資料
  • 因為CPU讀取資料量有限制，因此能夠從記憶體中讀寫的資料也就有所限制
  • ：(1)北橋：負責連結速度較快的CPU、主記憶體與顯示卡界面等元件；
  • (2)南橋：負責連接速度較慢的裝置介面， 包括硬碟、USB、網路卡等等。不過由於北橋最重要的就是 CPU 與主記憶體之間的橋接，因此目前的主流架構中， 大多將北橋記憶體控制器整合到 CPU 封裝當中
  • CPU 與可接受的晶片組是有搭配性的，尤其目前每種 CPU 的腳位都不一樣
  • 時脈越高，代表單位時間內可進行的工作越多
  • 大概都只看總頻寬或基準時脈
  • CPU 時脈越高的情況下，會產生很多諸如散熱、設計及與週邊元件溝通的問題。
  • 其他的程序還在等待 CPU ，但是 CPU 又在等待 I/O
  • Intel 在同一個運算核心底下安裝兩個暫存器來模擬出另一個核心，實際上是兩個暫存器 (可以想成是程式的執行器) 共用一個實體核心。 這就是超執行緒的簡易認知
  • 時脈的意思是每秒鐘能夠進行的工作次數，而每次工作能夠讀進的資料量就是位元數
  • 每個用戶端大多是短時間的大運算，所以通常不會有一隻程序一直佔用著系統資源。
  • CPU 的所有資料都是從記憶體讀寫來的，所以記憶體的容量與頻寬就相當的重要了
  • DRAM 根據技術的更新又分好幾代，而使用上較廣泛的有所謂的 SDRAM 與 DDR SDRAM 兩種。 這兩種記憶體的差別除了在於腳位與工作電壓上的不同之外，DDR 是所謂的雙倍資料傳送速度 (Double Data Rate)
  • 晶片組廠商就將兩個主記憶體彙整在一起，如果一支記憶體可達 64 位元，兩支記憶體就可以達到 128 位元了，這就是雙通道的設計理念。 在某些比較多核心的伺服器主機上面，甚至還使用了 3 通道到 4 通道的設計
  • CPU 內部的暫存器與少量記憶體被稱為第一、第二層快取 (L1, L2 cache)，而放在核心間的快取記憶體就被稱為第三層快取記憶體 (L3 cache)
  • CPU 的暫存器是直接設計在 CPU 核心內部，可以用來幫助 CPU 的運算。
  • 在多核心 CPU 的核心之間，會有另一個共享的快取記憶體存在，讓所有的 CPU 核心可以共享某些資源。
  • 靜態隨機存取記憶體 (Static Random Access Memory, SRAM)
  • 各項參數， 是被記錄到主機板上頭的一個稱為 CMOS 的晶片上，這個晶片需要藉著額外的電源來發揮記錄功能， 這也是為什麼你的主機板上面會有一顆電池的緣故。
  • BIOS(Basic Input Output System)是一套程式，這套程式是寫死到主機板上面的一個記憶體晶片中， 這個記憶體晶片在沒有通電時也能夠將資料記錄下來，那就是唯讀記憶體(Read Only Memory, ROM)。
  • BIOS對於個人電腦來說是非常重要的， 因為他是系統在開機的時候首先會去讀取的一個小程式喔
  • 韌體(firmware)很多也是使用ROM來進行軟體的寫入的。 韌體像軟體一樣也是一個被電腦所執行的程式，然而他是對於硬體內部而言更加重要的部分。例如BIOS就是一個韌體， BIOS雖然對於我們日常操作電腦系統沒有什麼太大的關係，但是他卻控制著開機時各項硬體參數的取得！
  • 現在的 BIOS 通常是寫入類似快閃記憶體 (flash) 或 EEPROM
  • 顯示卡能夠傳輸的資料量當然也是越大越好！這時就得要考慮到傳輸的界面了！當前 (2018) 主流的傳輸界面為 PCI-E，這個 PCI-E 又有三種版本， version 1, 2, 3 ，這三個版本的速度並不相同
  • PCI-E (PCI-Express) 使用的是類似管線的概念來處理，在 PCI-E 第一版中，每條管線可以具有 250MBytes/s 的頻寬效能，管線越多(通常設計到 x16 管線)則總頻寬越高
  • 通常 CPU 製造商會根據 CPU 來設計搭配的南橋晶片，由於現在只有一個晶片 (北橋整合到 CPU 內了)，所以目前只有一顆主機板晶片組。
  • 插槽上面的資料要傳輸到 CPU 就得要經過晶片組，然後透過 DMI 通道傳上去！所以，在某些情況下，系統的效能會被卡住在這條通道上喔！
  • 晶片組接的設備相當多喔！有 PCI-E 插槽、USB設備、網路設備、音效設備、硬碟設備等，這全部的裝置共用那一條 DMI 喔！ 所以，整個系統效能的瓶頸通常不在 CPU 啦！通常就是在南橋接的設備上面！所以，當你有非常複雜的程式要運作的時候，讓這些程式越少通過南橋， 他的系統效能就會比較好一點
  • 物理組成
  • 讀寫主要是透過在機械手臂上的讀取頭(head)來達成
  • 由於磁碟盤是圓的，並且透過機器手臂去讀寫資料，磁碟盤要轉動才能夠讓機器手臂讀寫。
  • 磁碟的最小物理儲存單位，稱之為磁區 (sector)，那同一個同心圓的磁區組合成的圓就是所謂的磁軌(track)。 由於磁碟裡面可能會有多個磁碟盤，因此在所有磁碟盤上面的同一個磁軌可以組合成所謂的磁柱 (cylinder)。
  • 通常資料的讀寫會由外圈開始往內寫
  • 目前主流的硬碟連接界面就是 SATA
  • 雖然 SATA III 界面理論傳輸可到達 600Mbytes/s，不過傳統硬碟由於物理設計的限制因素，通常存取速度效能大多在 150~200Mbytes/s 之間
  • 串列式 SCSI (Serial Attached SCSI, SAS)
  • 傳統硬碟有個很致命的問題，就是需要驅動馬達去轉動磁碟盤～這會造成很嚴重的磁碟讀取延遲
  • 快閃記憶體去製作成高容量的設備
  • 沒有讀寫頭與磁碟盤啊！都是記憶體！
  • 各個繪圖卡的運算晶片 (GPU) 設計的理念不同，加上驅動程式與軟體搭配的問題，並不是一張高效能繪圖卡就可以完勝其他的繪圖卡， 還得要注意相關的軟體才行。
張 旭

LXC vs Docker: Why Docker is Better | UpGuard - 0 views

www.upguard.com/...docker-vs-lxc

docker container devops

shared by 張 旭 on 28 Jun 21 - No Cached
  • LXC (LinuX Containers) is a OS-level virtualization technology that allows creation and running of multiple isolated Linux virtual environments (VE) on a single control host.
  • Docker, previously called dotCloud, was started as a side project and only open-sourced in 2013. It is really an extension of LXC’s capabilities.
  • run processes in isolation.
  • ...35 more annotations...
  • Docker is developed in the Go language and utilizes LXC, cgroups, and the Linux kernel itself. Since it’s based on LXC, a Docker container does not include a separate operating system; instead it relies on the operating system’s own functionality as provided by the underlying infrastructure.
  • Docker acts as a portable container engine, packaging the application and all its dependencies in a virtual container that can run on any Linux server.
  • a VE there is no preloaded emulation manager software as in a VM.
  • In a VE, the application (or OS) is spawned in a container and runs with no added overhead, except for a usually minuscule VE initialization process.
  • LXC will boast bare metal performance characteristics because it only packages the needed applications.
  • the OS is also just another application that can be packaged too.
  • a VM, which packages the entire OS and machine setup, including hard drive, virtual processors and network interfaces. The resulting bloated mass usually takes a long time to boot and consumes a lot of CPU and RAM.
  • don’t offer some other neat features of VM’s such as IaaS setups and live migration.
  • LXC as supercharged chroot on Linux. It allows you to not only isolate applications, but even the entire OS.
  • Libvirt, which allows the use of containers through the LXC driver by connecting to 'lxc:///'.
  • 'LXC', is not compatible with libvirt, but is more flexible with more userspace tools.
  • Portable deployment across machines
  • Versioning: Docker includes git-like capabilities for tracking successive versions of a container
  • Component reuse: Docker allows building or stacking of already created packages.
  • Shared libraries: There is already a public registry (http://index.docker.io/ ) where thousands have already uploaded the useful containers they have created.
  • Docker taking the devops world by storm since its launch back in 2013.
  • LXC, while older, has not been as popular with developers as Docker has proven to be
  • LXC having a focus on sys admins that’s similar to what solutions like the Solaris operating system, with its Solaris Zones, Linux OpenVZ, and FreeBSD, with its BSD Jails virtualization system
  • it started out being built on top of LXC, Docker later moved beyond LXC containers to its own execution environment called libcontainer.
  • Unlike LXC, which launches an operating system init for each container, Docker provides one OS environment, supplied by the Docker Engine
  • LXC tooling sticks close to what system administrators running bare metal servers are used to
  • The LXC command line provides essential commands that cover routine management tasks, including the creation, launch, and deletion of LXC containers.
  • Docker containers aim to be even lighter weight in order to support the fast, highly scalable, deployment of applications with microservice architecture.
  • With backing from Canonical, LXC and LXD have an ecosystem tightly bound to the rest of the open source Linux community.
  • Docker Swarm
  • Docker Trusted Registry
  • Docker Compose
  • Docker Machine
  • Kubernetes facilitates the deployment of containers in your data center by representing a cluster of servers as a single system.
  • Swarm is Docker’s clustering, scheduling and orchestration tool for managing a cluster of Docker hosts. 
  • rkt is a security minded container engine that uses KVM for VM-based isolation and packs other enhanced security features. 
  • Apache Mesos can run different kinds of distributed jobs, including containers. 
  • Elastic Container Service is Amazon’s service for running and orchestrating containerized applications on AWS
  • LXC offers the advantages of a VE on Linux, mainly the ability to isolate your own private workloads from one another. It is a cheaper and faster solution to implement than a VM, but doing so requires a bit of extra learning and expertise.
  • Docker is a significant improvement of LXC’s capabilities.
張 旭

Use a fake DB adapter to avoid connection errors with rails assets precompile - 0 views

blog.zeit.io/th-rails-assets-precompilation

rails docker database

shared by 張 旭 on 18 Oct 19 - No Cached
  • # Dockerfile DB_ADAPTER=nulldb bundle exec rake assets:precompile
  • gem "activerecord-nulldb-adapter"
張 旭

Logstash Alternatives: Pros & Cons of 5 Log Shippers [2019] - Sematext - 0 views

sematext.com/...logstash-alternatives

log monitor system logstash fluentd

shared by 張 旭 on 05 Nov 19 - No Cached
  • In this case, Elasticsearch. And because Elasticsearch can be down or struggling, or the network can be down, the shipper would ideally be able to buffer and retry
  • Logstash is typically used for collecting, parsing, and storing logs for future use as part of log management.
  • Logstash’s biggest con or “Achille’s heel” has always been performance and resource consumption (the default heap size is 1GB).
  • ...37 more annotations...
  • This can be a problem for high traffic deployments, when Logstash servers would need to be comparable with the Elasticsearch ones.
  • Filebeat was made to be that lightweight log shipper that pushes to Logstash or Elasticsearch.
  • differences between Logstash and Filebeat are that Logstash has more functionality, while Filebeat takes less resources.
  • Filebeat is just a tiny binary with no dependencies.
  • For example, how aggressive it should be in searching for new files to tail and when to close file handles when a file didn’t get changes for a while.
  • For example, the apache module will point Filebeat to default access.log and error.log paths
  • Filebeat’s scope is very limited,
  • Initially it could only send logs to Logstash and Elasticsearch, but now it can send to Kafka and Redis, and in 5.x it also gains filtering capabilities.
  • Filebeat can parse JSON
  • you can push directly from Filebeat to Elasticsearch, and have Elasticsearch do both parsing and storing.
  • You shouldn’t need a buffer when tailing files because, just as Logstash, Filebeat remembers where it left off
  • For larger deployments, you’d typically use Kafka as a queue instead, because Filebeat can talk to Kafka as well
  • The default syslog daemon on most Linux distros, rsyslog can do so much more than just picking logs from the syslog socket and writing to /var/log/messages.
  • It can tail files, parse them, buffer (on disk and in memory) and ship to a number of destinations, including Elasticsearch.
  • rsyslog is the fastest shipper
  • Its grammar-based parsing module (mmnormalize) works at constant speed no matter the number of rules (we tested this claim).
  • use it as a simple router/shipper, any decent machine will be limited by network bandwidth
  • It’s also one of the lightest parsers you can find, depending on the configured memory buffers.
  • rsyslog requires more work to get the configuration right
  • the main difference between Logstash and rsyslog is that Logstash is easier to use while rsyslog lighter.
  • rsyslog fits well in scenarios where you either need something very light yet capable (an appliance, a small VM, collecting syslog from within a Docker container).
  • rsyslog also works well when you need that ultimate performance.
  • syslog-ng as an alternative to rsyslog (though historically it was actually the other way around).
  • a modular syslog daemon, that can do much more than just syslog
  • Unlike rsyslog, it features a clear, consistent configuration format and has nice documentation.
  • Similarly to rsyslog, you’d probably want to deploy syslog-ng on boxes where resources are tight, yet you do want to perform potentially complex processing.
  • syslog-ng has an easier, more polished feel than rsyslog, but likely not that ultimate performance
  • Fluentd was built on the idea of logging in JSON wherever possible (which is a practice we totally agree with) so that log shippers down the line don’t have to guess which substring is which field of which type.
  • Fluentd plugins are in Ruby and very easy to write.
  • structured data through Fluentd, it’s not made to have the flexibility of other shippers on this list (Filebeat excluded).
  • Fluent Bit, which is to Fluentd similar to how Filebeat is for Logstash.
  • Fluentd is a good fit when you have diverse or exotic sources and destinations for your logs, because of the number of plugins.
  • Splunk isn’t a log shipper, it’s a commercial logging solution
  • Graylog is another complete logging solution, an open-source alternative to Splunk.
  • everything goes through graylog-server, from authentication to queries.
  • Graylog is nice because you have a complete logging solution, but it’s going to be harder to customize than an ELK stack.
  • it depends
張 旭

HowTo/LDAP - FreeIPA - 0 views

www.freeipa.org/LDAP

ldap authorization authentication auth security

shared by 張 旭 on 03 Dec 19 - No Cached
  • The basedn in an IPA installation consists of a set of domain components (dc) for the initial domain that IPA was configured with.
  • You will only ever have one basedn, the one defined during installation.
  • find your basedn, and other interesting things, in /etc/ipa/default.conf
  • ...8 more annotations...
  • IPA uses a flat structure, storing like objects in what we call containers.
  • Users: cn=users,cn=accounts,$SUFFIX Groups: cn=groups,cn=accounts,$SUFFIX
  • Do not use the Directory Manager account to authenticate remote services to the IPA LDAP server. Use a system account
  • The reason to use an account like this rather than creating a normal user account in IPA and using that is that the system account exists only for binding to LDAP. It is not a real POSIX user, can't log into any systems and doesn't own any files.
  • This use also has no special rights and is unable to write any data in the IPA LDAP server, only read.
  • When possible, configure your LDAP client to communicate over SSL/TLS.
  • The IPA CA certificate can be found in /etc/ipa/ca.crt
  • /etc/openldap/ldap.conf
張 旭

Understanding GitHub Actions - GitHub Docs - 0 views

docs.github.com/...understanding-github-actions

github cicd devops

shared by 張 旭 on 11 Sep 21 - No Cached
  • A job is a set of steps that execute on the same runner. By default, a workflow with multiple jobs will run those jobs in parallel.
  • Workflows are made up of one or more jobs and can be scheduled or triggered by an event
  • An event is a specific activity that triggers a workflow.
  • ...8 more annotations...
  • configure a workflow to run jobs sequentially.
  • A step is an individual task that can run commands in a job. A step can be either an action or a shell command.
  • Each step in a job executes on the same runner, allowing the actions in that job to share data with each other.
  • Actions are standalone commands that are combined into steps to create a job.
  • Actions are the smallest portable building block of a workflow.
  • To use an action in a workflow, you must include it as a step.
  • You can use a runner hosted by GitHub, or you can host your own.
  • GitHub-hosted runners are based on Ubuntu Linux, Microsoft Windows, and macOS, and each job in a workflow runs in a fresh virtual environment.
  • 張 旭 on 11 Sep 21
     
    "A job is a set of steps that execute on the same runner. By default, a workflow with multiple jobs will run those jobs in parallel. "
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