1597109100
In this video we are going to integrate Gatsby JS with Google Cloud Firestore Database and then query data using GraphQL.
Intro
Google Firebase Overview
Google Cloud Firestore Setup
Gatsby Project Setup
Gatsby Source Firestore Plugin Setup
Creating the GraphQL query to get the data
Creating a React Component using GraphQL
Testing the Gatsby application
Outro
#database
1594162500
A multi-cloud approach is nothing but leveraging two or more cloud platforms for meeting the various business requirements of an enterprise. The multi-cloud IT environment incorporates different clouds from multiple vendors and negates the dependence on a single public cloud service provider. Thus enterprises can choose specific services from multiple public clouds and reap the benefits of each.
Given its affordability and agility, most enterprises opt for a multi-cloud approach in cloud computing now. A 2018 survey on the public cloud services market points out that 81% of the respondents use services from two or more providers. Subsequently, the cloud computing services market has reported incredible growth in recent times. The worldwide public cloud services market is all set to reach $500 billion in the next four years, according to IDC.
By choosing multi-cloud solutions strategically, enterprises can optimize the benefits of cloud computing and aim for some key competitive advantages. They can avoid the lengthy and cumbersome processes involved in buying, installing and testing high-priced systems. The IaaS and PaaS solutions have become a windfall for the enterprise’s budget as it does not incur huge up-front capital expenditure.
However, cost optimization is still a challenge while facilitating a multi-cloud environment and a large number of enterprises end up overpaying with or without realizing it. The below-mentioned tips would help you ensure the money is spent wisely on cloud computing services.
Most organizations tend to get wrong with simple things which turn out to be the root cause for needless spending and resource wastage. The first step to cost optimization in your cloud strategy is to identify underutilized resources that you have been paying for.
Enterprises often continue to pay for resources that have been purchased earlier but are no longer useful. Identifying such unused and unattached resources and deactivating it on a regular basis brings you one step closer to cost optimization. If needed, you can deploy automated cloud management tools that are largely helpful in providing the analytics needed to optimize the cloud spending and cut costs on an ongoing basis.
Another key cost optimization strategy is to identify the idle computing instances and consolidate them into fewer instances. An idle computing instance may require a CPU utilization level of 1-5%, but you may be billed by the service provider for 100% for the same instance.
Every enterprise will have such non-production instances that constitute unnecessary storage space and lead to overpaying. Re-evaluating your resource allocations regularly and removing unnecessary storage may help you save money significantly. Resource allocation is not only a matter of CPU and memory but also it is linked to the storage, network, and various other factors.
The key to efficient cost reduction in cloud computing technology lies in proactive monitoring. A comprehensive view of the cloud usage helps enterprises to monitor and minimize unnecessary spending. You can make use of various mechanisms for monitoring computing demand.
For instance, you can use a heatmap to understand the highs and lows in computing visually. This heat map indicates the start and stop times which in turn lead to reduced costs. You can also deploy automated tools that help organizations to schedule instances to start and stop. By following a heatmap, you can understand whether it is safe to shut down servers on holidays or weekends.
#cloud computing services #all #hybrid cloud #cloud #multi-cloud strategy #cloud spend #multi-cloud spending #multi cloud adoption #why multi cloud #multi cloud trends #multi cloud companies #multi cloud research #multi cloud market
1632537859
Not babashka. Node.js babashka!?
Ad-hoc CLJS scripting on Node.js.
Experimental. Please report issues here.
Nbb's main goal is to make it easy to get started with ad hoc CLJS scripting on Node.js.
Additional goals and features are:
Nbb requires Node.js v12 or newer.
CLJS code is evaluated through SCI, the same interpreter that powers babashka. Because SCI works with advanced compilation, the bundle size, especially when combined with other dependencies, is smaller than what you get with self-hosted CLJS. That makes startup faster. The trade-off is that execution is less performant and that only a subset of CLJS is available (e.g. no deftype, yet).
Install nbb
from NPM:
$ npm install nbb -g
Omit -g
for a local install.
Try out an expression:
$ nbb -e '(+ 1 2 3)'
6
And then install some other NPM libraries to use in the script. E.g.:
$ npm install csv-parse shelljs zx
Create a script which uses the NPM libraries:
(ns script
(:require ["csv-parse/lib/sync$default" :as csv-parse]
["fs" :as fs]
["path" :as path]
["shelljs$default" :as sh]
["term-size$default" :as term-size]
["zx$default" :as zx]
["zx$fs" :as zxfs]
[nbb.core :refer [*file*]]))
(prn (path/resolve "."))
(prn (term-size))
(println (count (str (fs/readFileSync *file*))))
(prn (sh/ls "."))
(prn (csv-parse "foo,bar"))
(prn (zxfs/existsSync *file*))
(zx/$ #js ["ls"])
Call the script:
$ nbb script.cljs
"/private/tmp/test-script"
#js {:columns 216, :rows 47}
510
#js ["node_modules" "package-lock.json" "package.json" "script.cljs"]
#js [#js ["foo" "bar"]]
true
$ ls
node_modules
package-lock.json
package.json
script.cljs
Nbb has first class support for macros: you can define them right inside your .cljs
file, like you are used to from JVM Clojure. Consider the plet
macro to make working with promises more palatable:
(defmacro plet
[bindings & body]
(let [binding-pairs (reverse (partition 2 bindings))
body (cons 'do body)]
(reduce (fn [body [sym expr]]
(let [expr (list '.resolve 'js/Promise expr)]
(list '.then expr (list 'clojure.core/fn (vector sym)
body))))
body
binding-pairs)))
Using this macro we can look async code more like sync code. Consider this puppeteer example:
(-> (.launch puppeteer)
(.then (fn [browser]
(-> (.newPage browser)
(.then (fn [page]
(-> (.goto page "https://clojure.org")
(.then #(.screenshot page #js{:path "screenshot.png"}))
(.catch #(js/console.log %))
(.then #(.close browser)))))))))
Using plet
this becomes:
(plet [browser (.launch puppeteer)
page (.newPage browser)
_ (.goto page "https://clojure.org")
_ (-> (.screenshot page #js{:path "screenshot.png"})
(.catch #(js/console.log %)))]
(.close browser))
See the puppeteer example for the full code.
Since v0.0.36, nbb includes promesa which is a library to deal with promises. The above plet
macro is similar to promesa.core/let
.
$ time nbb -e '(+ 1 2 3)'
6
nbb -e '(+ 1 2 3)' 0.17s user 0.02s system 109% cpu 0.168 total
The baseline startup time for a script is about 170ms seconds on my laptop. When invoked via npx
this adds another 300ms or so, so for faster startup, either use a globally installed nbb
or use $(npm bin)/nbb script.cljs
to bypass npx
.
Nbb does not depend on any NPM dependencies. All NPM libraries loaded by a script are resolved relative to that script. When using the Reagent module, React is resolved in the same way as any other NPM library.
To load .cljs
files from local paths or dependencies, you can use the --classpath
argument. The current dir is added to the classpath automatically. So if there is a file foo/bar.cljs
relative to your current dir, then you can load it via (:require [foo.bar :as fb])
. Note that nbb
uses the same naming conventions for namespaces and directories as other Clojure tools: foo-bar
in the namespace name becomes foo_bar
in the directory name.
To load dependencies from the Clojure ecosystem, you can use the Clojure CLI or babashka to download them and produce a classpath:
$ classpath="$(clojure -A:nbb -Spath -Sdeps '{:aliases {:nbb {:replace-deps {com.github.seancorfield/honeysql {:git/tag "v2.0.0-rc5" :git/sha "01c3a55"}}}}}')"
and then feed it to the --classpath
argument:
$ nbb --classpath "$classpath" -e "(require '[honey.sql :as sql]) (sql/format {:select :foo :from :bar :where [:= :baz 2]})"
["SELECT foo FROM bar WHERE baz = ?" 2]
Currently nbb
only reads from directories, not jar files, so you are encouraged to use git libs. Support for .jar
files will be added later.
The name of the file that is currently being executed is available via nbb.core/*file*
or on the metadata of vars:
(ns foo
(:require [nbb.core :refer [*file*]]))
(prn *file*) ;; "/private/tmp/foo.cljs"
(defn f [])
(prn (:file (meta #'f))) ;; "/private/tmp/foo.cljs"
Nbb includes reagent.core
which will be lazily loaded when required. You can use this together with ink to create a TUI application:
$ npm install ink
ink-demo.cljs
:
(ns ink-demo
(:require ["ink" :refer [render Text]]
[reagent.core :as r]))
(defonce state (r/atom 0))
(doseq [n (range 1 11)]
(js/setTimeout #(swap! state inc) (* n 500)))
(defn hello []
[:> Text {:color "green"} "Hello, world! " @state])
(render (r/as-element [hello]))
Working with callbacks and promises can become tedious. Since nbb v0.0.36 the promesa.core
namespace is included with the let
and do!
macros. An example:
(ns prom
(:require [promesa.core :as p]))
(defn sleep [ms]
(js/Promise.
(fn [resolve _]
(js/setTimeout resolve ms))))
(defn do-stuff
[]
(p/do!
(println "Doing stuff which takes a while")
(sleep 1000)
1))
(p/let [a (do-stuff)
b (inc a)
c (do-stuff)
d (+ b c)]
(prn d))
$ nbb prom.cljs
Doing stuff which takes a while
Doing stuff which takes a while
3
Also see API docs.
Since nbb v0.0.75 applied-science/js-interop is available:
(ns example
(:require [applied-science.js-interop :as j]))
(def o (j/lit {:a 1 :b 2 :c {:d 1}}))
(prn (j/select-keys o [:a :b])) ;; #js {:a 1, :b 2}
(prn (j/get-in o [:c :d])) ;; 1
Most of this library is supported in nbb, except the following:
:syms
.-x
notation. In nbb, you must use keywords.See the example of what is currently supported.
See the examples directory for small examples.
Also check out these projects built with nbb:
See API documentation.
See this gist on how to convert an nbb script or project to shadow-cljs.
Prequisites:
To build:
bb release
Run bb tasks
for more project-related tasks.
Download Details:
Author: borkdude
Download Link: Download The Source Code
Official Website: https://github.com/borkdude/nbb
License: EPL-1.0
#node #javascript
1597833840
If you looking to learn about Google Cloud in depth or in general with or without any prior knowledge in cloud computing, then you should definitely check this quest out, Link.
Google Could Essentials is an introductory level Quest which is useful to learn about the basic fundamentals of Google Cloud. From writing Cloud Shell commands and deploying my first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.
Let’s see what was the Quest Outline:
A Tour of Qwiklabs and Google Cloud was the first hands-on lab which basically gives an overview about Google Cloud. There were few questions to answers that will check your understanding about the topic and the rest was about accessing Google cloud console, projects in cloud console, roles and permissions, Cloud Shell and so on.
**Creating a Virtual Machine **was the second lab to create virtual machine and also connect NGINX web server to it. Compute Engine lets one create virtual machine whose resources live in certain regions or zones. NGINX web server is used as load balancer. The job of a load balancer is to distribute workloads across multiple computing resources. Creating these two along with a question would mark the end of the second lab.
#google-cloud-essentials #google #google-cloud #google-cloud-platform #cloud-computing #cloud
1623224760
I have a few small websites hosted on the Digital Ocean server. Each of them has a MySQL database and I wanted to regularly set uploading full database export to some independent location outside of Digital Ocean to sleep more calmly. Since my life revolves around Google Cloud, my preference for storage was clear. The goal is to use crontab to periodically run a bash script to execute MySQL database export and gsutil command to copy a file to the Cloud Storage bucket. To configure the whole process there are several steps involved, which I will describe in this article. I interactions with the Google Cloud project, I am using web UI, although all steps could be done via the command-line interface.
…
#database #mysql #google-cloud-platform #google-cloud-storage #backup database to google cloud storage #backups
1620921300
In this Lab, we will configure Cloud Content Delivery Network (Cloud CDN) for a Cloud Storage bucket and verify caching of an image. Cloud CDN uses Google’s globally distributed edge points of presence to cache HTTP(S) load-balanced content close to our users. Caching content at the edges of Google’s network provides faster delivery of content to our users while reducing serving costs.
For an up-to-date list of Google’s Cloud CDN cache sites, see https://cloud.google.com/cdn/docs/locations.
Cloud CDN content can originate from different types of backends:
In this lab, we will configure a Cloud Storage bucket as the backend.
#google-cloud #google-cloud-platform #cloud #cloud storage #cloud cdn