Salesforce Capabilities With Heroku Knowledge for Redis

This text is an element two of a three-part collection on utilizing Heroku Managed Data merchandise from inside a Salesforce Function. Partially one, we targeted on Salesforce Capabilities with Heroku Postgres. Partially two, we’ll discover Salesforce Capabilities with Heroku Data for Redis. Lastly, partly three, we’ll cowl Salesforce Capabilities and Apache Kafka on Heroku.

Introduction to Core Concepts

What Is a Salesforce Function?

For example, you could leverage a JavaScript library to calculate and cache a value based on a triggered process within Salesforce. If you are new to Functions in general, check out “Get to Know Salesforce Functions” to study what they’re and the way they work.

What Is Heroku Data for Redis?

Heroku Data for Redis is a Redis key-value datastore that’s absolutely managed for you by Heroku. That implies that Heroku takes care of issues like safety, backups, and upkeep. All you must do is use it. As a result of Heroku is a part of Salesforce, this makes entry and safety a lot simpler. The Heroku Dev Center documentation is a superb place to search out extra particulars on Heroku Knowledge for Redis.

Use Case #1: Store State Between Function Runs

This use case is concerned with flexibility around background jobs. Because applications built on Salesforce run on a multitenant architecture, Salesforce locations restrictions on CPU and reminiscence utilization for purposes. Lengthy-running applications are sometimes out of bounds and restricted.

Then how may you run a protracted or heavy job in your Salesforce Org? The reply is Salesforce Capabilities. You may wire up your perform to assemble the data wanted and insert it into Redis. Then, your Heroku worker processes can retrieve the data and carry out the duties.

Use Case #3: Cache the Outcomes of Costly Operations

On this final use case, let’s assume that you’ve an costly question or calculation. The consequence doesn’t change typically, however the report that wants the consequence runs continuously. For instance, maybe we wish to match some standards throughout numerous information that seldom change. We are able to use a Salesforce Perform to do the work and Redis to retailer the consequence. Subsequent executions of the perform can merely seize the cached consequence.

How Do I Get Began?

To get began, you’ll must have a couple of items in place—each on the Salesforce Capabilities facet and the Heroku facet.

• Stipulations
• Getting began with Salesforce Capabilities

$ sf generate function -n yourfunction -l javascript

Connecting to Your Redis Instance

Your function code can use the dotenv bundle for specifying the Redis URL as an setting variable and the node-redis bundle as a Redis consumer. Connecting to Redis may look one thing like this:

import "dotenv/config";
import  createClient  from 'redis';

async perform redisConnect() 
  const redis = createClient(
    url: course of.env.REDIS_URL,
    socket: 
      tls: true,
      rejectUnauthorized: false
    
  );
  await redis.join();
  return redis;

For native execution, utilizing course of.env and dotenv assumes that you’ve a .env file that specifies your REDIS_URL.

Store Data in Redis

export default async function (event, context) 
  const redis = await redisConnect();
  const CACHE_KEY = `my_cache_key`;
  const CACHE_TTL_SECONDS = 86400;

  // Check Redis for cached value
  let cached_value = await redis.get(CACHE_KEY);

  if (cached_value) 
    return  result: cached_value 
   else 
    // Perform some calculation
    const calculated_value = await perform_long_running_computation();

    // Store in Redis
    redis.set(CACHE_KEY, calculated_value, 
      EX: CACHE_TTL_SECONDS,
      NX: true
    );
    // Return result
    return  result: calculated_value 
  

Test Your Salesforce Function Locally

$ sf run function -l http://localhost:8080 -p '"payloadID": "info"'

For more information on running Functions locally, see this guide.

Associate Your Salesforce Function and Your Heroku Environment

After verifying locally that our Function runs as expected, we can associate our Salesforce Function with a computing environment. (See this documentation for extra details about making a compute setting and deploying a perform.)

Now, affiliate your capabilities and Heroku environments by including your Heroku consumer as a collaborator to your perform’s compute setting:

$ sf env compute collaborator add --heroku-user [email protected]

The environments can now share Heroku information. Subsequent, you will want the identify of the computing setting as a way to connect the information retailer to it.

Lastly, connect the information retailer.

$ heroku addons:connect <your-heroku-redis> --app <your-compute-environment-name>

Listed here are some further sources which may be useful for you as you start implementing your Salesforce Perform and accessing Heroku Knowledge for Redis:

Conclusion