Automated Daily Backups

October 09, 2020 | Glynn Bird | Backup Serverless

Cloudant is already reslient in that it stores data in triplicate across a region’s three availability zones but that’s not the same thing as having a backup:


Photo by Ashim D’Silva on Unsplash

In this article we’ll create a serverless backup utility which can be triggered to run periodically to backup a Cloudant database to IBM Cloud Object Storage:


To follow this tutorial you’ll need:

Couchbackup 🔗

The couchbackup utility is a command-line tool that allows a Cloudant database to be turned a text file.

# turn our "animals" database into a text file
couchbackup --db animals > animals.txt

It comes with a matching utility which does the reverse: restores a text file back to a Cloudant database.

# restore our animals backup to a new database
cat animals.txt | couchrestore --db animals2

All we need to do is trigger couchbackup periodically to perform a backup. To do this we’ll use IBM Cloud Functions, which allows code to run serverlessly, meaning you pay only for the execution time and nothing while your application stands idle.

Creating a suitable Docker image 🔗

To create a Docker image suitable for running inside the IBM Cloud Functions platform we need a file called Dockerfile containing the definition of our image:

# based on the IBM Cloud Functions Node.js runtime
FROM ibmfunctions/action-nodejs-v10

# with additional npm modules for Cloudant & COS
RUN npm install ibm-cos-sdk@1.6.1
RUN npm install @cloudant/couchbackup

The image is based on the existing IBM Cloud Functions Node.js runtime but adds two additional Node.js modules:

Assuming you have a DockerHub account (let’s assume a username of x), you can build the image with the following terminal commands:

docker build -t x/cloudant_backup .
docker push x/cloudant_backup:latest

If you don’t want to build the Docker image yourself, there is one already built using this definition at which we’ll use in the rest of the tutorial.

Making a backup script 🔗

The Docker image provides the operating system, the IBM Cloud Functions scaffolding and the libraries we need - all that is required is to add our own custom code to allow us to backup a Cloudant database to Object Storage programmatically. Here’s an example:

const couchbackup = require('@cloudant/couchbackup')
const AWS = require('ibm-cos-sdk')
const stream = require('stream')

const main = async function (args) {
  // combine bare URL with source database
  if (!args.CLOUDANT_URL || !args.CLOUDANT_DB) {
    return Promise.reject(new Error('missing Cloudant config'))
  const fullURL = args.CLOUDANT_URL + '/' + args.CLOUDANT_DB

  // COS config
  if (!args.COS_ENDPOINT || !args.COS_API_KEY || !args.COS_SERVICE_INSTANCE_ID || !args.COS_BUCKET) {
    return Promise.reject(new Error('missing COS config'))
  const COSConfig = {
    endpoint: args.COS_ENDPOINT,
    apiKeyId: args.COS_API_KEY,
    ibmAuthEndpoint: '',
    serviceInstanceId: args.COS_SERVICE_INSTANCE_ID
  const cos = new AWS.S3(COSConfig)
  const streamToUpload = new stream.PassThrough({ highWaterMark: 67108864 })
  const key = `${args.CLOUDANT_DB}_${new Date().toISOString()}_backup.txt`
  const bucket = args.COS_BUCKET
  const uploadParams = {
    Bucket: args.COS_BUCKET,
    Key: key,
    Body: streamToUpload
  console.log(`Backing up DB ${fullURL} to ${bucket}/${key}`)

  // return a Promise as this may take some time
  return new Promise((resolve, reject) => {
    // create a COS upload operation hanging on a stream of data
    cos.upload(uploadParams, function (err, data) {
      if (err) {
        return reject(new Error('could not write to COS'))
      console.log('COS upload done')

    // then kick off a backup writing to that stream
    couchbackup.backup(fullURL, streamToUpload, { iamApiKey: args.CLOUDANT_IAM_KEY },
      function (err, data) {
        if (err) {
          return reject(err)
        console.log('couchbackup done')

module.exports = {

Most of the above code involves the the handling of the incoming parameters which are listed here:

The values you’ll need can be found in your Cloudant and Cloud Object Storage service credentials, apart from COS_ENDPOINT which can be found here. Note that if the IBM Cloud Functions region and IBM Cloud Object Storage region are the same, then a “private” endpoint can be chosen to keep the traffic within the data centre.

If our code is written to an index.js file, we can deploy to IBM Cloud Functions with:

# create a new Cloud Functions package
ibmcloud fn package create cron
# create a function in the cron package based on the Docker image
ibmcloud fn action update cron/backup --docker choirless/backup:latest index.js

We now have an IBM Cloud Function called cron/backup which is based on our Docker image and adds our index.js script.

Executing a backup 🔗

To avoid having to pass all of the configuration options in with each execution, we’re going to bind most of the configuration (all items except the database name) to the function. Create a JSON file opts.json containing your configuration:


Then bind this configuration to your action:

ibmcloud fn action update cron/backup --param-file opts.json

This means that when we execute the action we only need provide the one missing parameter: the name of the database to backup:

ibmcloud fn action invoke cron/backup --result --param CLOUDANT_DB mydb

Scheduling a backup to run periodically 🔗

We can tell IBM Cloud Functions to run our action once every 24 hours for each database we need to backup:

# backup each database after midnight

# mydb1 database
ibmcloud fn trigger create mydb1BackupTrigger --feed /whisk.system/alarms/alarm --param cron "5 0 * * *" --param trigger_payload "{\"CLOUDANT_DB\":\"mydb1\"}" 
ibmcloud fn rule create mydb1BackupRule mydb1BackupTrigger cron/backup

# mydb2 database
ibmcloud fn trigger create mydb2BackupTrigger --feed /whisk.system/alarms/alarm --param cron "10 0 * * *" --param trigger_payload "{\"CLOUDANT_DB\":\"mydb2\"}" 
ibmcloud fn rule create mydb2BackupRule mydb2BackupTrigger cron/backup

Scheduling an invocation of an IBM Cloud Function is a two-part process:

In the above example mydb1 is backed up at five past midnight every day and mydb2 five minutes later.

Limitations 🔗

This approach is reasonable for small Cloudant databases but IBM Cloud Functions has a ten minute execution limit so very large databases would not complete in time.

For very large databases, consider consuming a database’s changes feed, passing in a last known since value to get incremental changes.