How to use @pulumi/cloud-aws - 10 common examples

const cloud = require("@pulumi/cloud-aws");

// Create a mapping from 'route' to a count
let counterTable = new cloud.Table("counterTable", "route");

// Create an API endpoint
let endpoint = new cloud.API("hello-world");

endpoint.get("/{route+}", (req, res) => {
    let route = req.params["route"];
    console.log(`Getting count for '${route}'`);

    // get previous value and increment
    // reference outer `counterTable` object
    counterTable.get({ route }).then(value => {
        let count = (value && value.count) || 0;
        counterTable.insert({ route, count: ++count }).then(() => {
            res.status(200).json({ route, count });
            console.log(`Got count ${count} for '${route}'`);
        });
    });
});

// Copyright 2016-2018, Pulumi Corporation.  All rights reserved.

// Note: @pulumi/cloud is a preview package demonstrating how to create cross-cloud Pulumi
// components. If you are targeting a specific cloud like AWS, Azure, or GCP, we recommend you use
// platform-specific packages like @pulumi/aws, @pulumi/azure or @pulumi/gcp. These packages give
// you full access to the breadth of the platform's capabilities and comes with many abstractions to
// make developing against that platform easier.

import * as cloud from "@pulumi/cloud-aws";

// Create a web server.
const endpoint = new cloud.API("urlshortener");

// Create a table `urls`, with `name` as primary key.
const urlTable = new cloud.Table("urls", "name");

// Serve all files in the www directory to the root.
endpoint.static("/", "www");

// GET /url lists all URLs currently registered.
endpoint.get("/url", async (req, res) => {
    try {
        const items = await urlTable.scan();
        res.status(200).json(items);
        console.log(`GET /url retrieved ${items.length} items`);
    } catch (err) {
        res.status(500).json(err.stack);
        console.log(`GET /url error: ${err.stack}`);

// Copyright 2016-2018, Pulumi Corporation.  All rights reserved.

"use strict";

const cloud = require("@pulumi/cloud-aws");
const video = require("./video-label-processor");

// A bucket to store videos and thumbnails.
const bucket = new cloud.Bucket("bucket");
const bucketName = bucket.bucket.id;

// A task which runs a containerized FFMPEG job to extract a thumbnail image.
const ffmpegThumbnailTask = new cloud.Task("ffmpegThumbTask", {
    build: "./docker-ffmpeg-thumb",
    memoryReservation: 512,
});

// Use module for processing video through Rekognition
const videoProcessor = new video.VideoLabelProcessor();

// When a new video is uploaded, start Rekognition label detection
bucket.onPut("onNewVideo", bucketArgs => {
    console.log(`*** New video: file ${bucketArgs.key} was uploaded at ${bucketArgs.eventTime}.`);
    videoProcessor.startRekognitionJob(bucketName.get(), bucketArgs.key);
    return Promise.resolve();

// Copyright 2016-2018, Pulumi Corporation.  All rights reserved.

const cloud = require("@pulumi/cloud-aws");

// A bucket to store videos and thumbnails.
const bucket = new cloud.Bucket("bucket");
const bucketName = bucket.bucket.id;

// A task which runs a containerized FFMPEG job to extract a thumbnail image.
const ffmpegThumbnailTask = new cloud.Task("ffmpegThumbTask", {
    build: "./docker-ffmpeg-thumb",
    memoryReservation: 512,
});

// When a new video is uploaded, run the FFMPEG task on the video file.
// Use the time index specified in the filename (e.g. cat_00-01.mp4 uses timestamp 00:01)
bucket.onPut("onNewVideo", bucketArgs => {
    console.log(`*** New video: file ${bucketArgs.key} was uploaded at ${bucketArgs.eventTime}.`);
    const file = bucketArgs.key;
    
    const thumbnailFile = file.substring(0, file.indexOf('_')) + '.jpg';
    const framePos = file.substring(file.indexOf('_')+1, file.indexOf('.')).replace('-',':');

console.log(now);
    res.status(200).end(now.toString());
});

endpoint.post("/echo", async (req, res) => {
    const data = parseUrlEncodedBody(req.body);

    const response: SlackSlashCommandResponse = {
        response_type: "in_channel",
        text: data.text,
    };

    res.status(200).json(response);
});

const quoteTable = new cloud.Table("quotes");

// quote-add [name] [value]
endpoint.post("/quote-add", async (req, res) => {
    const data = parseUrlEncodedBody(req.body);

    const kvp = getIdValue(data.text);
    if (!kvp) {
        res.status(400).end();
        return;
    }

    console.log(`Saving '${kvp.key}'='${kvp.value}'`);

    // Fetch the array.
    const value = await quoteTable.get({ id: kvp.key });
    const array: string[] = (value && value.array) || [];

const cloud = require("@pulumi/cloud-aws");

// Create a mapping from 'route' to a count
let counterTable = new cloud.Table("counterTable", "route");

// Create an API endpoint
let endpoint = new cloud.API("hello-world");

endpoint.get("/{route+}", (req, res) => {
    let route = req.params["route"];
    console.log(`Getting count for '${route}'`);

    // get previous value and increment
    // reference outer `counterTable` object
    counterTable.get({ route }).then(value => {
        let count = (value && value.count) || 0;
        counterTable.insert({ route, count: ++count }).then(() => {
            res.status(200).json({ route, count });
            console.log(`Got count ${count} for '${route}'`);
        });

// Copyright 2016-2018, Pulumi Corporation.  All rights reserved.

// Note: @pulumi/cloud is a preview package demonstrating how to create cross-cloud Pulumi
// components. If you are targeting a specific cloud like AWS, Azure, or GCP, we recommend you use
// platform-specific packages like @pulumi/aws, @pulumi/azure or @pulumi/gcp. These packages give
// you full access to the breadth of the platform's capabilities and comes with many abstractions to
// make developing against that platform easier.

import * as cloud from "@pulumi/cloud-aws";

// Create a web server.
const endpoint = new cloud.API("urlshortener");

// Create a table `urls`, with `name` as primary key.
const urlTable = new cloud.Table("urls", "name");

// Serve all files in the www directory to the root.
endpoint.static("/", "www");

// GET /url lists all URLs currently registered.
endpoint.get("/url", async (req, res) => {
    try {
        const items = await urlTable.scan();
        res.status(200).json(items);
        console.log(`GET /url retrieved ${items.length} items`);
    } catch (err) {
        res.status(500).json(err.stack);
        console.log(`GET /url error: ${err.stack}`);
    }
});

// Copyright 2016-2018, Pulumi Corporation.  All rights reserved.

"use strict";

const cloud = require("@pulumi/cloud-aws");
const video = require("./video-label-processor");

// A bucket to store videos and thumbnails.
const bucket = new cloud.Bucket("bucket");
const bucketName = bucket.bucket.id;

// A task which runs a containerized FFMPEG job to extract a thumbnail image.
const ffmpegThumbnailTask = new cloud.Task("ffmpegThumbTask", {
    build: "./docker-ffmpeg-thumb",
    memoryReservation: 512,
});

// Use module for processing video through Rekognition
const videoProcessor = new video.VideoLabelProcessor();

// When a new video is uploaded, start Rekognition label detection
bucket.onPut("onNewVideo", bucketArgs => {
    console.log(`*** New video: file ${bucketArgs.key} was uploaded at ${bucketArgs.eventTime}.`);
    videoProcessor.startRekognitionJob(bucketName.get(), bucketArgs.key);
    return Promise.resolve();
}, { keySuffix: ".mp4" });  // run this Lambda only on .mp4 files

// When Rekognition processing is complete, run the FFMPEG task on the video file
// Use the timestamp with the highest confidence for the label "cat"

// Copyright 2016-2018, Pulumi Corporation.  All rights reserved.

const cloud = require("@pulumi/cloud-aws");

// A bucket to store videos and thumbnails.
const bucket = new cloud.Bucket("bucket");
const bucketName = bucket.bucket.id;

// A task which runs a containerized FFMPEG job to extract a thumbnail image.
const ffmpegThumbnailTask = new cloud.Task("ffmpegThumbTask", {
    build: "./docker-ffmpeg-thumb",
    memoryReservation: 512,
});

// When a new video is uploaded, run the FFMPEG task on the video file.
// Use the time index specified in the filename (e.g. cat_00-01.mp4 uses timestamp 00:01)
bucket.onPut("onNewVideo", bucketArgs => {
    console.log(`*** New video: file ${bucketArgs.key} was uploaded at ${bucketArgs.eventTime}.`);
    const file = bucketArgs.key;
    
    const thumbnailFile = file.substring(0, file.indexOf('_')) + '.jpg';
    const framePos = file.substring(file.indexOf('_')+1, file.indexOf('.')).replace('-',':');

    ffmpegThumbnailTask.run({
        environment: {
            "S3_BUCKET":   bucketName.get(),

interface SlackSlashCommandResponse {
    response_type?: SlackSlashCommandResponseType;
    text: string;
    attachments?: SlackSlashCommandResponseAttachment[];
}

interface SlackSlashCommandResponseAttachment {
    text: string;
}




// Create an API endpoint
let endpoint = new cloud.HttpEndpoint("echo");

endpoint.get("/test", async (req, res) => {
    const now = Date.now();
    console.log(now);
    res.status(200).end(now.toString());
});

endpoint.post("/echo", async (req, res) => {
    const data = parseUrlEncodedBody(req.body);

    const response: SlackSlashCommandResponse = {
        response_type: "in_channel",
        text: data.text,
    };

    res.status(200).json(response);