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張 旭

Introduction to MongoDB - MongoDB Manual - 0 views

docs.mongodb.com/...introduction

database mongodb

shared by 張 旭 on 20 Apr 21 - No Cached
  • MongoDB is a document database designed for ease of development and scaling
  • MongoDB offers both a Community and an Enterprise version
  • A record in MongoDB is a document, which is a data structure composed of field and value pairs.
  • ...12 more annotations...
  • MongoDB documents are similar to JSON objects.
  • The values of fields may include other documents, arrays, and arrays of documents.
  • reduce need for expensive joins
  • MongoDB stores documents in collections.
  • Collections are analogous to tables in relational databases.
  • Read-only Views
  • Indexes support faster queries and can include keys from embedded documents and arrays.
  • MongoDB's replication facility, called replica set
  • A replica set is a group of MongoDB servers that maintain the same data set, providing redundancy and increasing data availability.
  • Sharding distributes data across a cluster of machines.
  • MongoDB supports creating zones of data based on the shard key.
  • MongoDB provides pluggable storage engine API
張 旭

Quick start - 0 views

terragrunt.gruntwork.io/...quick-start

devops terraform

shared by 張 旭 on 15 Jun 21 - No Cached
  • Terragrunt will forward almost all commands, arguments, and options directly to Terraform, but based on the settings in your terragrunt.hcl file
  • the backend configuration does not support variables or expressions of any sort
  • the path_relative_to_include() built-in function,
  • ...9 more annotations...
  • The generate attribute is used to inform Terragrunt to generate the Terraform code for configuring the backend.
  • The find_in_parent_folders() helper will automatically search up the directory tree to find the root terragrunt.hcl and inherit the remote_state configuration from it.
  • Unlike the backend configurations, provider configurations support variables,
  • if you needed to modify the configuration to expose another parameter (e.g session_name), you would have to then go through each of your modules to make this change.
  • instructs Terragrunt to create the file provider.tf in the working directory (where Terragrunt calls terraform) before it calls any of the Terraform commands
  • large modules should be considered harmful.
  • it is a Bad Idea to define all of your environments (dev, stage, prod, etc), or even a large amount of infrastructure (servers, databases, load balancers, DNS, etc), in a single Terraform module.
  • Large modules are slow, insecure, hard to update, hard to code review, hard to test, and brittle (i.e., you have all your eggs in one basket).
  • Terragrunt allows you to define your Terraform code once and to promote a versioned, immutable “artifact” of that exact same code from environment to environment.
張 旭

Think Before you NodePort in Kubernetes - Oteemo - 0 views

oteemo.com/think-nodeport-kubernetes

kubernetes networking

shared by 張 旭 on 23 Jun 21 - No Cached
  • Two options are provided for Services intended for external use: a NodePort, or a LoadBalancer
  • no built-in cloud load balancers for Kubernetes in bare-metal environments
  • NodePort may not be your best choice.
  • ...15 more annotations...
  • NodePort, by design, bypasses almost all network security in Kubernetes.
  • NetworkPolicy resources can currently only control NodePorts by allowing or disallowing all traffic on them.
  • put a network filter in front of all the nodes
  • if a Nodeport-ranged Service is advertised to the public, it may serve as an invitation to black-hats to scan and probe
  • When Kubernetes creates a NodePort service, it allocates a port from a range specified in the flags that define your Kubernetes cluster. (By default, these are ports ranging from 30000-32767.)
  • By design, Kubernetes NodePort cannot expose standard low-numbered ports like 80 and 443, or even 8080 and 8443.
  • A port in the NodePort range can be specified manually, but this would mean the creation of a list of non-standard ports, cross-referenced with the applications they map to
  • if you want the exposed application to be highly available, everything contacting the application has to know all of your node addresses, or at least more than one.
  • non-standard ports.
  • Ingress resources use an Ingress controller (the nginx one is common but not by any means the only choice) and an external load balancer or public IP to enable path-based routing of external requests to internal Services.
  • With a single point of entry to expose and secure
  • get simpler TLS management!
  • consider putting a real load balancer in front of your NodePort Services before opening them up to the world
  • Google very recently released an alpha-stage bare-metal load balancer that, once installed in your cluster, will load-balance using BGP
  • NodePort Services are easy to create but hard to secure, hard to manage, and not especially friendly to others
張 旭

The differences between Docker, containerd, CRI-O and runc - Tutorial Works - 0 views

www.tutorialworks.com/ocker-containerd-runc-crio-oci

docker container devops

shared by 張 旭 on 28 Jun 21 - No Cached
  • Docker isn’t the only container contender on the block.
  • Container Runtime Interface (CRI), which defines an API between Kubernetes and the container runtime
  • Open Container Initiative (OCI) which publishes specifications for images and containers.
  • ...20 more annotations...
  • for a lot of people, the name “Docker” itself is synonymous with the word “container”.
  • Docker created a very ergonomic (nice-to-use) tool for working with containers – also called docker.
  • docker is designed to be installed on a workstation or server and comes with a bunch of tools to make it easy to build and run containers as a developer, or DevOps person.
  • containerd: This is a daemon process that manages and runs containers.
  • runc: This is the low-level container runtime (the thing that actually creates and runs containers).
  • libcontainer, a native Go-based implementation for creating containers.
  • Kubernetes includes a component called dockershim, which allows it to support Docker.
  • Kubernetes prefers to run containers through any container runtime which supports its Container Runtime Interface (CRI).
  • Kubernetes will remove support for Docker directly, and prefer to use only container runtimes that implement its Container Runtime Interface.
  • Both containerd and CRI-O can run Docker-formatted (actually OCI-formatted) images, they just do it without having to use the docker command or the Docker daemon.
  • Docker images, are actually images packaged in the Open Container Initiative (OCI) format.
  • CRI is the API that Kubernetes uses to control the different runtimes that create and manage containers.
  • CRI makes it easier for Kubernetes to use different container runtimes
  • containerd is a high-level container runtime that came from Docker, and implements the CRI spec
  • containerd was separated out of the Docker project, to make Docker more modular.
  • CRI-O is another high-level container runtime which implements the Container Runtime Interface (CRI).
  • The idea behind the OCI is that you can choose between different runtimes which conform to the spec.
  • runc is an OCI-compatible container runtime.
  • A reference implementation is a piece of software that has implemented all the requirements of a specification or standard.
  • runc provides all of the low-level functionality for containers, interacting with existing low-level Linux features, like namespaces and control groups.
張 旭

Improving Kubernetes reliability: quicker detection of a Node down | Fatal failure - 0 views

fatalfailure.wordpress.com/...icker-detection-of-a-node-down

kubernetes HA

shared by 張 旭 on 21 Jul 21 - No Cached
  • when a Node gets down, the pods of the broken node are still running for some time and they still get requests, and those requests, will fail.
  • 1- The Kubelet posts its status to the masters using –node-status-update-frequency=10s 2- A node dies 3- The kube controller manager is the one monitoring the nodes, using –-node-monitor-period=5s it checks, in the masters, the node status reported by the Kubelet. 4- Kube controller manager will see the node is unresponsive, and has this grace period –node-monitor-grace-period=40s until it considers the node unhealthy.
  • node-status-update-frequency x (N-1) != node-monitor-grace-period
  • ...2 more annotations...
  • 5- Once the node is marked as unhealthy, the kube controller manager will remove its pods based on –pod-eviction-timeout=5m0s
  • 6- Kube proxy has a watcher over the API, so the very first moment the pods are evicted the proxy will notice and update the iptables of the node, removing the endpoints from the services so the failing pods won’t be accessible anymore.
張 旭

Monitor Node Health | Kubernetes - 0 views

kubernetes.io/...monitor-node-health

kubernetes monitor system

shared by 張 旭 on 21 Jul 21 - No Cached
  • Node Problem Detector is a daemon for monitoring and reporting about a node's health
  • Node Problem Detector collects information about node problems from various daemons and reports these conditions to the API server as NodeCondition and Event.
  • Node Problem Detector only supports file based kernel log. Log tools such as journald are not supported.
  • ...2 more annotations...
  • kubectl provides the most flexible management of Node Problem Detector.
  • run the Node Problem Detector in your cluster to monitor node health.
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

Running rootless Podman as a non-root user | Enable Sysadmin - 0 views

www.redhat.com/...rootless-podman-makes-sense

docker podman linux system

shared by 張 旭 on 04 Aug 20 - No Cached
  • By default, rootless Podman runs as root within the container.
  • the processes in the container have the default list of namespaced capabilities which allow the processes to act like root inside of the user namespace
  • the directory is owned by UID 26, but UID 26 is not mapped into the container and is not the same UID that Postgres runs with while in the container.
  • ...8 more annotations...
  • Podman launches a container inside of the user namespace, which is mapped with the range of UIDs defined for the user in /etc/subuid and /etc/subgid
  • The easy solution to this problem is to chown the html directory to match the UID that Postgresql runs with inside of the container.
  • use the podman unshare command, which drops you into the same user namespace that rootless Podman uses
  • This setup also means that the processes inside of the container are running as the user’s UID. If the container process escaped the container, the process would have full access to files in your home directory based on UID separation.
  • SELinux would still block the access, but I have heard that some people disable SELinux.
  • If you run the processes within the container as a different non-root UID, however, then those processes will run as that UID. If they escape the container, they would only have world access to content in your home directory.
  • run a podman unshare command, or set up the directories' group ownership as owned by your UID (root inside of the container).
  • running containers as non-root should always be your top priority for security reasons.
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. "
張 旭

Creating a cluster with kubeadm | Kubernetes - 0 views

kubernetes.io/...create-cluster-kubeadm

kubernetes networking

shared by 張 旭 on 25 Jan 23 - No Cached
  • (Recommended) If you have plans to upgrade this single control-plane kubeadm cluster to high availability you should specify the --control-plane-endpoint to set the shared endpoint for all control-plane nodes
  • set the --pod-network-cidr to a provider-specific value.
  • kubeadm tries to detect the container runtime by using a list of well known endpoints.
  • ...12 more annotations...
  • kubeadm uses the network interface associated with the default gateway to set the advertise address for this particular control-plane node's API server. To use a different network interface, specify the --apiserver-advertise-address=<ip-address> argument to kubeadm init
  • Do not share the admin.conf file with anyone and instead grant users custom permissions by generating them a kubeconfig file using the kubeadm kubeconfig user command.
  • The token is used for mutual authentication between the control-plane node and the joining nodes. The token included here is secret. Keep it safe, because anyone with this token can add authenticated nodes to your cluster.
  • You must deploy a Container Network Interface (CNI) based Pod network add-on so that your Pods can communicate with each other. Cluster DNS (CoreDNS) will not start up before a network is installed.
  • Take care that your Pod network must not overlap with any of the host networks
  • Make sure that your Pod network plugin supports RBAC, and so do any manifests that you use to deploy it.
  • You can install only one Pod network per cluster.
  • The cluster created here has a single control-plane node, with a single etcd database running on it.
  • The node-role.kubernetes.io/control-plane label is such a restricted label and kubeadm manually applies it using a privileged client after a node has been created.
  • By default, your cluster will not schedule Pods on the control plane nodes for security reasons.
  • kubectl taint nodes --all node-role.kubernetes.io/control-plane-
  • remove the node-role.kubernetes.io/control-plane:NoSchedule taint from any nodes that have it, including the control plane nodes, meaning that the scheduler will then be able to schedule Pods everywhere.
張 旭

Service | Kubernetes - 0 views

kubernetes.io/...service

kubernetes networking service ingress

shared by 張 旭 on 14 Apr 21 - No Cached
  • Each Pod gets its own IP address
  • Pods are nonpermanent resources.
  • Kubernetes Pods are created and destroyed to match the state of your cluster
  • ...23 more annotations...
  • In Kubernetes, a Service is an abstraction which defines a logical set of Pods and a policy by which to access them (sometimes this pattern is called a micro-service).
  • The set of Pods targeted by a Service is usually determined by a selector
  • If you're able to use Kubernetes APIs for service discovery in your application, you can query the API server for Endpoints, that get updated whenever the set of Pods in a Service changes.
  • A Service in Kubernetes is a REST object, similar to a Pod.
  • The name of a Service object must be a valid DNS label name
  • Kubernetes assigns this Service an IP address (sometimes called the "cluster IP"), which is used by the Service proxies
  • A Service can map any incoming port to a targetPort. By default and for convenience, the targetPort is set to the same value as the port field.
  • The default protocol for Services is TCP
  • As many Services need to expose more than one port, Kubernetes supports multiple port definitions on a Service object. Each port definition can have the same protocol, or a different one.
  • Because this Service has no selector, the corresponding Endpoints object is not created automatically. You can manually map the Service to the network address and port where it's running, by adding an Endpoints object manually
  • Endpoint IP addresses cannot be the cluster IPs of other Kubernetes Services
  • Kubernetes ServiceTypes allow you to specify what kind of Service you want. The default is ClusterIP
  • ClusterIP: Exposes the Service on a cluster-internal IP.
  • NodePort: Exposes the Service on each Node's IP at a static port (the NodePort). A ClusterIP Service, to which the NodePort Service routes, is automatically created. You'll be able to contact the NodePort Service, from outside the cluster, by requesting <NodeIP>:<NodePort>.
  • LoadBalancer: Exposes the Service externally using a cloud provider's load balancer
  • ExternalName: Maps the Service to the contents of the externalName field (e.g. foo.bar.example.com), by returning a CNAME record with its value. No proxying of any kind is set up.
  • You can also use Ingress to expose your Service. Ingress is not a Service type, but it acts as the entry point for your cluster.
  • If you set the type field to NodePort, the Kubernetes control plane allocates a port from a range specified by --service-node-port-range flag (default: 30000-32767).
  • The default for --nodeport-addresses is an empty list. This means that kube-proxy should consider all available network interfaces for NodePort.
  • you need to take care of possible port collisions yourself. You also have to use a valid port number, one that's inside the range configured for NodePort use.
  • Service is visible as <NodeIP>:spec.ports[*].nodePort and .spec.clusterIP:spec.ports[*].port
  • Choosing this value makes the Service only reachable from within the cluster.
  • NodePort: Exposes the Service on each Node's IP at a static port
張 旭

Syntax - Configuration Language | Terraform | HashiCorp Developer - 0 views

developer.hashicorp.com/...configuration

devops terraform

shared by 張 旭 on 22 Jan 23 - No Cached
  • the native syntax of the Terraform language, which is a rich language designed to be relatively easy for humans to read and write.
  • Terraform's configuration language is based on a more general language called HCL, and HCL's documentation usually uses the word "attribute" instead of "argument."
  • A particular block type may have any number of required labels, or it may require none
  • ...34 more annotations...
  • After the block type keyword and any labels, the block body is delimited by the { and } characters
  • Identifiers can contain letters, digits, underscores (_), and hyphens (-). The first character of an identifier must not be a digit, to avoid ambiguity with literal numbers.
  • The # single-line comment style is the default comment style and should be used in most cases.
  • he idiomatic style is to use the Unix convention
  • Indent two spaces for each nesting level.
  • align their equals signs
  • Use empty lines to separate logical groups of arguments within a block.
  • Use one blank line to separate the arguments from the blocks.
  • "meta-arguments" (as defined by the Terraform language semantics)
  • Avoid separating multiple blocks of the same type with other blocks of a different type, unless the block types are defined by semantics to form a family.
  • Resource names must start with a letter or underscore, and may contain only letters, digits, underscores, and dashes.
  • Each resource is associated with a single resource type, which determines the kind of infrastructure object it manages and what arguments and other attributes the resource supports.
  • Each resource type is implemented by a provider, which is a plugin for Terraform that offers a collection of resource types.
  • By convention, resource type names start with their provider's preferred local name.
  • Most publicly available providers are distributed on the Terraform Registry, which also hosts their documentation.
  • The Terraform language defines several meta-arguments, which can be used with any resource type to change the behavior of resources.
  • use precondition and postcondition blocks to specify assumptions and guarantees about how the resource operates.
  • Some resource types provide a special timeouts nested block argument that allows you to customize how long certain operations are allowed to take before being considered to have failed.
  • Timeouts are handled entirely by the resource type implementation in the provider
  • Most resource types do not support the timeouts block at all.
  • A resource block declares that you want a particular infrastructure object to exist with the given settings.
  • Destroy resources that exist in the state but no longer exist in the configuration.
  • Destroy and re-create resources whose arguments have changed but which cannot be updated in-place due to remote API limitations.
  • Expressions within a Terraform module can access information about resources in the same module, and you can use that information to help configure other resources. Use the <RESOURCE TYPE>.<NAME>.<ATTRIBUTE> syntax to reference a resource attribute in an expression.
  • resources often provide read-only attributes with information obtained from the remote API; this often includes things that can't be known until the resource is created, like the resource's unique random ID.
  • data sources, which are a special type of resource used only for looking up information.
  • some dependencies cannot be recognized implicitly in configuration.
  • local-only resource types exist for generating private keys, issuing self-signed TLS certificates, and even generating random ids.
  • The behavior of local-only resources is the same as all other resources, but their result data exists only within the Terraform state.
  • The count meta-argument accepts a whole number, and creates that many instances of the resource or module.
  • count.index — The distinct index number (starting with 0) corresponding to this instance.
  • the count value must be known before Terraform performs any remote resource actions. This means count can't refer to any resource attributes that aren't known until after a configuration is applied
  • Within nested provisioner or connection blocks, the special self object refers to the current resource instance, not the resource block as a whole.
  • This was fragile, because the resource instances were still identified by their index instead of the string values in the list.
  • 張 旭 on 22 Jan 23
     
    "the native syntax of the Terraform language, which is a rich language designed to be relatively easy for humans to read and write. "
張 旭

Configuring a cgroup driver | Kubernetes - 0 views

kubernetes.io/...configure-cgroup-driver

kubernetes docker devops

shared by 張 旭 on 25 Jan 23 - No Cached
  • the systemd driver is recommended for kubeadm based setups instead of the cgroupfs driver, because kubeadm manages the kubelet as a systemd service.
張 旭

Language Server Protocol - Wikipedia - 0 views

en.wikipedia.org/...Language_Server_Protocol

vim programming

shared by 張 旭 on 28 Jan 22 - No Cached
  • Modern IDEs provide developers with sophisticated features like code completion, refactoring, navigating to a symbol's definition, syntax highlighting, and error and warning markers.
  • an IDE needs a sophisticated understanding of the programming language that the program's source is written in.
  • Conventional compilers or interpreters for a specific programming language are typically unable to provide these language services, because they are written with the goal of either transforming the source code into object code or immediately executing the code.
  • ...5 more annotations...
  • Prior to the design and implementation of the Language Server Protocol for the development of Visual Studio Code, most language services were generally tied to a given IDE or other editor.
  • The Language Server Protocol allows for decoupling language services from the editor so that the services may be contained within a general purpose language server.
  • LSP is not restricted to programming languages. It can be used for any kind of text-based language, like specifications[7] or domain-specific languages (DSL).
  • When a user edits one or more source code files using a language server protocol-enabled tool, the tool acts as a client that consumes the language services provided by a language server.
  • The protocol does not make any provisions about how requests, responses and notifications are transferred between client and server.
張 旭

Optimizing Gitlab pipelines - Basics (1) | PrinsFrank.nl - 0 views

prinsfrank.nl/...g-gitlab-pipelines-pt-1-basics

devops gitlab cicd proxy performance

shared by 張 旭 on 23 Feb 22 - No Cached
  • When you use specific docker image, make sure you have the Dependency Proxy enabled so the image doesn’t have to be downloaded again for every job.
  • stages are used to group items that can run at the same time.
  • Instead of waiting for all jobs to finish, you can mark jobs as interruptible which signals a job to cancel when a new pipeline starts for the same branch
  • ...8 more annotations...
  • mark all jobs as interruptible as it doesn’t make sense to wait for builds and tests based on old information.
  • Deployment jobs are the main exception as they should probably finish.
  • only running it when specific files have changed
  • To prevent the ‘vendor’ and ‘node_modules’ folder from being regenerated in every job, we can configure a build job for composer and npm assets.
  • To share assets between multiple stages, Gitlab has caches and artifacts. For dependencies we should use caches.
  • The pull-push policy is the default, but specified here for clarity.
  • All consecutive runs for the build step with the same ‘composer.lock’ file don’t update the cache.
  • composer prevents this by caching packages in a global package cache,
張 旭

Considerations for large clusters | Kubernetes - 0 views

kubernetes.io/...cluster-large

kubernetes

shared by 張 旭 on 24 Mar 22 - No Cached
  • A cluster is a set of nodes (physical or virtual machines) running Kubernetes agents, managed by the control plane.
  • Kubernetes v1.23 supports clusters with up to 5000 nodes.
  • criteria: No more than 110 pods per node No more than 5000 nodes No more than 150000 total pods No more than 300000 total containers
  • ...14 more annotations...
  • In-use IP addresses
  • run one or two control plane instances per failure zone, scaling those instances vertically first and then scaling horizontally after reaching the point of falling returns to (vertical) scale.
  • Kubernetes nodes do not automatically steer traffic towards control-plane endpoints that are in the same failure zone
  • store Event objects in a separate dedicated etcd instance.
  • start and configure additional etcd instance
  • Kubernetes resource limits help to minimize the impact of memory leaks and other ways that pods and containers can impact on other components.
  • Addons' default limits are typically based on data collected from experience running each addon on small or medium Kubernetes clusters.
  • When running on large clusters, addons often consume more of some resources than their default limits.
  • Many addons scale horizontally - you add capacity by running more pods
  • The VerticalPodAutoscaler can run in recommender mode to provide suggested figures for requests and limits.
  • Some addons run as one copy per node, controlled by a DaemonSet: for example, a node-level log aggregator.
  • VerticalPodAutoscaler is a custom resource that you can deploy into your cluster to help you manage resource requests and limits for pods.
  • The cluster autoscaler integrates with a number of cloud providers to help you run the right number of nodes for the level of resource demand in your cluster.
  • The addon resizer helps you in resizing the addons automatically as your cluster's scale changes.
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