#node js cron job

[codeonedigest]

Nodejs Cron Job Scheduler & Cron Expression Tutorial in JavaScript with Examples for Developers

Full Video Link https://youtu.be/yI_xAky_-3c Hello friends, new #video on #cronjob #jobscheduler #scheduler #cronexpression in #nodejs #javascript #projeect #application #tutorial #examples is published on #codeonedigest #youtube channel.

In this video, we will learn to create CRON JOB SCHEDULER in nodejs javascript. We will learn what “node-cron” module in nodejs javascript. How to use “node-cron” package to schedule jobs in nodejs javascript. * Important Nodejs Javascript Packages or Modules * node-cron – The node-cron module is tiny task scheduler in pure JavaScript for node.js based on GNU crontab. This module allows you to…

[opensourcefan]

How to Build a Cron Job with Node js ☞ http://bit.ly/2Lpraih #nodejs #javascript

[fullstackdevelop]

Node.js Cron Jobs By Examples ☞ https://morioh.com/p/2f06f4404ce5/node-js-cron-jobs-by-examples #nodejs #javascript

[nodejs-fan]

Node.js Cron Jobs By Examples ☞ https://morioh.com/p/2f06f4404ce5/node-js-cron-jobs-by-examples #nodejs #javascript

[blogging-from-itp]

Working with Pi - 2

Connecting to Firebase

This week I spent time figuring out how to capture images using the Pi cam and sending data to Firebase.

Pi cam

There are four parts to it. 

Capturing a picture: ✔️ This is the article where I started but it work, based on Alex’s suggestion. My issue was working with installing Imagemagick. May be it’s lack of experience, but based on Google search, I couldn’t find a simple workaround to use it. So I broke down the steps and started doing each step individually. Pi’s timelapse documentation came in handy.

Setting up a Cron job: ✔️ Tom Igoe’s page was super helpful.

Saving them in a folder: I think it’s about definig the path. But I couldn’t figure out a way to do the Cron job by storing the images in a folder. So my Home quickly got crowded with images. All of which I had to manually delete.

Sending it to Firebase: Read below.

Useful references:

This has good documentation on how to take photos: https://picamera.readthedocs.io/en/release-1.13/recipes1.html#capturing-to-a-network-stream

Sending data to Firebase

Before using Firebase, I was inclined to use MongoDB. Based on research, it turned out to be a slightly harder to send images. It’s easier to send text files. So I switched to Firebase.

One of the challenges working with Pi and hardware in general is that there are different ways to do the same thing. So a big chunk of my time was consumed in reading and looking for good documentation with clear explanation.

⇩ This one didn’t work:

Setting up Firebase: This was the easy part. I followed the steps from this article and created a project.

Since I didn’t know how to send images to Firebase, I tried to work with a sensor. I picked the DHT sensor. Little did I know how fragile and finicky it is.

I started with this documentation. As I went about debugging the Python script, I went into a rabbit hole. The problem: I used the Thorny Python IDE to run the script. It turns that the environment is in 2 but my script was in 3. 

Issues: I noticed that the console was throwing each line as an error. So I started debugging line by line. It started with missing libraries. A lot which I installed but the part that eventually made me start from scratch was the missing Adafruit DHT library. Akash (Software background) did a quick check and told me that it was deprecated. So I asked a classmate, Nick Boss, who knew CS to help me find a workaround. Initially we tried to rewrite the code but it was still throwing errors. It came down to GPIO pin library. I am still not sure what the exact problem was. Nick used iPython. I don’t think I understood it but after adding another GB of library and no clear solution, I realised that it’s best to pause.

⇩ This is in progress:

I found a much cleaner set of instructions in this Github repo.

So far, I finished all the steps and currently figuring out how to add the Pyrebase wrapper for Firebase.

⇩ This worked. Yay!

Eric offered to help me yesterday connecting Firebase with Node. I don’t know Js plus I haven’t much enough documentation with it so I let me give this a shot.

His first question was how are we connecting the DHT to the Pi. So we searched for node Serial port and found the Serial Port link.

Next, we had to find a way to read the GPIO pins. I couldn’t comprehend the need but nevertheless. We searched for “gpio reading node js” and then found the w3 school documentation on OnOff module for NPM. We used the blinking LED for code reference.

Following up, we searched for the OnOff NPM package.

Next, we had to figure out how to read OnOff dht value. The article here was useful. Alongside, we referred to Tom’s code on GPIO pins here.

The code finally worked and we started to get reading. Or so we thought. The reading was in binary. So we spent some more time to figure it out. We tried to refer to this article but it didn’t finally work. After a while we realized that the sensor isn’t working. Given that it has no role in my project, I instead thought of sending some random data or message to Firebase.

Two things were helpful. Setting the interval as described here and getting a timestamp in Js.

The image above is the screenshot of the same.

[phungthaihy]

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[javascriptnext]

How to Build a Cron Job with Node js ☞ http://bit.ly/2Lpraih #nodejs #javascript

[mediba-ce]

Datadog と Lighthouse を利用した WebPerf の継続的計測

こんにちは。ものづくり推進部、フロントエンドエンジニアの武田です。 今日は Datadog, Lighthouse を使ったクライアントパフォーマンス計測に取り組んでいる、というお話です。

mediba では webpagetest を使った定期実行と計測を以前から行っています。

DataStudioとGASでWebPagetestの計測結果をグラフ化する

uknmr/gas-webpagetest

紹介記事: gas-webpagetestでWebPagetestのパフォーマンス計測を自動化、可視化する

1 での取り組みをベースにし、clasp で GAS のソースコード管理・デプロイを実現するための仕組みや webpagetest Lighthouse test と連携したメトリクスの取得まで網羅したものが 2 になります。

今回は少し webpagetest とは趣向を変えて

Lighthouse による定期実行とパフォーマンス値取得

Datadog API を利用したカスタムメトリクスへの POST

Datadog による可視化

についてご紹介します。

実施に必要なもの

Datadog (Pro Plan or Enterprise Plan での契約)

Node.js v10.13 以上（現時点）、Chrome がインストールされている実行環境

Lighthouse

定期実行する仕組み

超簡単な説明ですが

Datadog とは? -> システム監視のための SaaS

Lighthouse とは? -> クライアントパフォーマンスのスコアリングツール

です。

Lighthouse による定期実行とパフォーマンス値取得

webpagetest ではなくなぜ Lighthouse ���のか

webpagetest を利用する場合、自前のプライベートインスタンスとして立てることも可能ですが、コストとの兼ね合いでパブリックインスタンスとして存在するリージョンを利用するというシーンがどうしてもあります。今回はプロダクション環境とパブリックに閲覧が不可能であるステージング環境の2環境を施策に合わせて比較をする必要があるため、どうしてもその制限をクリアできません。

ステージング環境を正常に閲覧できる（=リクエストを受け付けられる）

Lighthouse 実行のために必要な Node.js v10 以上が動作する

Lighthouse 実行のために Chrome が動作する

これらを定期的に実行する

以上を実現することが必要そうです。

どこで Lighthouse 定期的に動かすか

ランタイムを Node.js v10.x にした lambda もしくは CodeBuild でスクリプトを実行、定期スケジューリングを CloudWatch Events にするということも可能そうです。一度 CodeBuild 想定でコストを計算してみます。CodeBuild の OS image は Chrome も素で入っていますし、割となんでも入り感があります。

料金 - AWS CodeBuild | AWS

毎月かかりそうな試算の条件

デイリーで24回実行想定

ビルドにかかる時間 5 分

インスタンスタイプに一番高いクラス 1分単位で 0.02 USD

24回/day * 30day * 5 分 * 0.02 USD = 72 USD

現時点レートで 7,827 円、自分が毎月もらっているお小遣いから出せるかと言われると出せない金額なので今回は AWS 環境での実行を諦めます。

いろいろ考えた結果、ほぼゼロコストで仕上げるため選択したのは Travis CI でした。といっても弊社では Travis CI Enterprise を AWS 環境上で動作させており、そこで実行させる想定です（なので詳細を詰められるとゼロコストではないのですが）。

ただ残念ながら定期実行を叶える Travis Cron Jobs はリポジトリのブランチ毎にマニュアルで指定する必要があるのでそこは残念な感じになります、人間がポチポチ GUI から指定して定期実行を実現することにします。

Lighthouse スクリプト

フロントエンドエンジニアの方ですと Chrome Devtools -> audit や Lighthouse を CLI から利用することは一度はやってみたことがあると思うのですが、今回はよく見るスコアがほしいわけではなく特定のパフォーマンスメトリクスを取得したいという意図です。個人的にも絶対的なスコアリングが全てだと思っていません、計測し比較し向上しているかが一番重要であると思っています。

プログラマブルに Ligththouse を操作していきますが、実はほとんどドキュメントにあったりするので、参考に取得してパフォーマンス値をかき集めてみます。

const lighthouse = require('lighthouse'); const log = require('lighthouse-logger'); const chromeLauncher = require('chrome-launcher'); const opts = { chromeFlags: ["--headless", "--disable-gpu"], logLevel: "info" }; log.setLevel(opts.logLevel); launchChromeAndRunLighthouse("https://stg.example.com", opts).then(results => { // 一旦標準出力に表示 console.table(results); }); function launchChromeAndRunLighthouse(url, opts, config = null) { return chromeLauncher.launch({chromeFlags: opts.chromeFlags}).then(chrome => { opts.port = chrome.port; return lighthouse(url, opts, config).then(results => { // results.lhr はよく見るスコアリングの元データ // https://github.com/GoogleChrome/lighthouse/blob/master/types/lhr.d.ts const { "time-to-first-byte": ttfb, "first-contentful-paint": fcp, "first-meaningful-paint": fmp, "speed-index": speedindex, interactive, metrics, } = results.lhr.audits; return chrome.kill().then(() =>({ TTFB: Math.round(ttfb.numericValue), FIRST_PAINT: metrics.details.items[0].observedFirstPaint, FMP: Math.round(fmp.numericValue), FCP: Math.round(fcp.numericValue), SPEED_INDEX: Math.round(speedindex.numericValue), TTI: Math.round(interactive.numericValue), })); }); }); }

Lighthouse 実行時の Promise.resolve で返却される results は型定義もあり、昨今のエディタ補完の恩恵を受けると大変 DX が良いのですが、必要な数値は正直どこに格納されているか探すほかないので、CLI で一度 JSON ファイルを成果物として実行してから探すのが一番手っ取り早いです。切り取られたスクリーンショットの情報が Base64 でエンコードされ格納されているので違った工夫もできそうではあります。

ここまでで Lighthouse 側の準備は整ったので次に Datadog 側を準備します。

Datadog API を利用したカスタムメトリクスへの POST

そもそもなぜ Datadog を選ぶのか

担当するプロダクトのシステムモニタリングとして現在利用しており（他のプロジェクトでの利用実績もあります）、インテグレーションや API 連携について学びたいというのと、値のプロットと可視化を Datadog 一括にしちゃえば便利だし見るところ少なくていいんじゃね？ というのが大きなモチベーションです。

私が活動するメインフィールドはフロントエンドなのですが、チームでは属人化を避けるため監視やアラート対応・調査を含め、モブを通して暗黙知をなくそうという取り組みをしている点も Datadog を候補にした理由です。

Datadog API とカスタムメトリクスの利用

次はDatadog API を使ってカスタムメトリクスを作り POST しますが、まずは API key, APP key が必要になってきます。

ナビゲーションから Intergrations -> APIs

API key, APP key 取得

実際にリクエストを送る際は node-dogapi というのがあるのでこちらを利用してみます。

初期化

const datadog = require("dogapi"); // 環境変数に Datadog API key, Datadog App key がセットされている想定 datadog.initialize({ api_key: process.env.DATADOG_API_KEY, app_key: process.env.DATADOG_APP_KEY, });

カスタムメトリクスへの送信

任意の文字列をカスタムメトリクス名として、収集した値をプロットしていきます。なお以下のコードは先ほど出力に結果を表示したブロックで利用する想定です。タグ名に関しては特定の要素に紐づけ絞り込みを目的として利用を推奨しているようで、公式にもある通りプロダクション環境やステージング環境の種別としてタギングします。タグのルールとしては <KEY>:<VALUE> というルールになります。参照

const { TTFB, FIRST_PAINT, FMP, FCP, SPEED_INDEX, TTI, } = results; const tags = "env:staging"; datadog.metric.send_all([ { metric: "webperf.measure.ttfb", points: TTFB, tags, }, { metric: "webperf.measure.first_paint", points: FIRST_PAINT, tags, }, { metric: "webperf.measure.fmp", points: FMP, tags, }, { metric: "webperf.measure.fcp", points: FCP, tags, }, { metric: "webperf.measure.speed_index", points: SPEED_INDEX, tags, }, { metric: "webperf.measure.tti", points: TTI, tags, }, ], (err, results) => { if (err) { console.log(`Error: ${JSON.stringify()}`); process.exit(1); } console.log(`Results: ${JSON.stringify(results, null, 4)}`); });

ここまでのもの実行できれば Datadog のカスタムメトリクスに値がプロットされ可視化するデータは出来たことになります。

Datadog による可視化

ダッシュボードを作成

新しいダッシュボードを作成しグラフを作る準備をします。

Timeborad: 時系列にイベントグラフを閲覧しレイアウトが自動

Screenboard: ステータスやグラフなどデータとして混合されたもの向けでレイアウトがフレキシブル

2つから選べますがお好きな方を選んで調整��てください。

ダッシュボードにウィジェットを追加

グラフで可視化する場合は Timeseries というウィジェットを使用します。

ウィジェットでハマるとしたらタグでの絞り込みな気がします。もしタグがサジェストされないなどうまくいかないようでしたら </> アイコンを押下して raw text での変更に切り替えると avg:webperf.measure.ttfb{key:value} のような入力が可能になるので試してみると良いかもしれません。

最近よく聞くようなパフォーマンスバジェットを閾値として定めて、閾値よりオーバーしたら Warning 表示にする、なおかつ閾値を超えた際にモニタリングによって Slack に通知するといったことも可能です。

Google Developers Japan: パフォーマンスバジェットのご紹介 - ウェブパフォーマンスのための予算管理

ダッシュボードは今のところシンプルですがこんな感じになっています。

日々プロットしたグラフを可視化し追いかけたい数値と、重要視したい値・バジェットを定めてデカデカと表示する、見栄えはよくありませんが実務に事足りるものになっています。

まとめ

Lighthouse から特定の値を取得、Datadog API を使ったカスタムメトリクスへの POST、Datadog 内での可視化について書かせていただきました。

Datadog のカスタムメトリクス利用は Pro/Enterprise プランのみ

手早く低コストで定期実行したいなら CI のサービス利用を検討

Lighthouse の実行結果からはパフォーマンス値やその他（スクショなど）も取得できる

Datadog API の利用は簡単（各種言語のライブラリ等も揃っており充実）

ダッシュボードも気軽で簡単に可視化できる

今回は Datadog のプラン次第というところもありますが、まずは低コストでパフォーマンス定期計測やパフォーマンスバジェットの設定などに取り組んでみてはいかがでしょうか。

[unternehmensmeldungen-com]

Cron jobs in Node.js

New Post has been published on https://www.unternehmensmeldungen.com/cron-jobs-in-node-js/

Cron jobs in Node.js

medium.com - Every developer sooner or later faces a problem on how to deal with cron jobs. The list of cron jobs use-cases is enormous: cache invalidation, reports generation, refreshing data from external…Mehr zu Kubernetes Services, Kubernetes Training und Rancher dedicated as a Service lesen ...

Ganzen Artikel zu Cron jobs in Node.js lesen auf https://www.unternehmensmeldungen.com/cron-jobs-in-node-js/ Mehr Wirtschaftsnachrichten und Unternehmensmeldungen unter https://www.unternehmensmeldungen.com

[codeonedigest]

Nodejs Cron Job Scheduler & Cron Expression Tutorial in JavaScript with ... Full Video Link       https://youtu.be/yI_xAky_-3c         Hello friends, new #video on #cronjob #jobscheduler #scheduler #cronexpression in #nodejs #javascript #projeect #application #tutorial #examples is published on #codeonedigest #youtube channel.  @java #java #aws #awscloud @awscloud @AWSCloudIndia #salesforce #Cloud #CloudComputing @YouTube #youtube #azure #msazure  #codeonedigest @codeonedigest  #nodejs #cronjob #javascript #nodejstutorial #learnnodejs #node.js #nodejsandexpressjstutorial #cronjobexample #jobscheduling #jobscheduler #cronjobscheduler #javascriptcronjob #javascriptjobscheduler #javascripttutorialforbeginners #javascripttutorial #javascriptfullcourse #cronscheduler #cronjobschedulerexpression #cronexpression #cronexpressioninjavascript #nodejscronexpression #nodejsjobscheduler #nodejscronjob #nodejstutorial #job

[javascriptfan]

How to Build a Cron Job with Node js ☞ http://bit.ly/2Lpraih #nodejs #javascript

[the-openstack]

How to Build a Cron Job with Node js ☞ http://bit.ly/2Pjtslk #nodejs #javascript

[nodejs-fan]

How to Build a Cron Job with Node js ☞ http://bit.ly/2Pjtslk #nodejs #javascript

[robertbryantblog]

Install WordPress With Node Js

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Why Is Host Header Required

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Can Cron Job Is Running

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The post Install WordPress With Node Js appeared first on Quick Click Hosting.

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[quickclickhosting]

Install WordPress With Node Js

Who Web Hosting Vs Cloud Hosting

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Why Is Host Header Required

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Can Cron Job Is Running

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[nodejs-fan]

How to Build a Cron Job with Node js ☞ http://bit.ly/2Lpraih #nodejs #javascript