A Temporal Workflow Execution has no time limit. You can write a Workflow that runs forever, storing some state and responding to Signals and Queries, as long as you remember to use Continue-As-New. One neat use case for long-lived Workflows is caching API requests.

For example, suppose you want to display prices in various currencies based on cached exchange rates. Exchange rate APIs are often expensive for high volumes of requests, so caching can be worthwhile as long as stale data isn't a problem for your use case. You can create a single Temporal Workflow that makes one API request per day to get the latest exchange rates for a set of currencies and stores the most recent result, with no explicit database calls or cron jobs. In this blog post, I'll describe how you can write an API caching Workflow for the moneyconvert.net API with the Temporal TypeScript SDK. You can find the full source code for this example in vkarpov/temporal-api-caching-example on GitHub.

Getting Started

When you make an HTTP GET request to https://cdn.moneyconvert.net/api/latest.json, the API returns JSON that looks like the following:

{
  "table": "latest",
  "rates": {
    "AED": 3.6731,
    "AFN": 87.249991,
    "ALL": 114.227196,
    "AMD": 473.915796,
    ...
  },
  "lastupdate": "2022-05-11T00:46:04.483000+00:00"
}

Because Temporal Workflows must be deterministic, you can't make an API request directly from a Workflow. You need to create an Activity that makes an API request, and call that Activity from your Workflow. Following is an activities.ts file that makes an HTTP request to the preceding API endpoint and returns the exchange rates.

import axios from 'axios';

export async function getExchangeRates(): Promise<any> {
  const res = await axios.get('https://cdn.moneyconvert.net/api/latest.json');
  return res.data.rates;
};

Next, let's write a Workflow that calls this Activity once per day. With Temporal Workflows, you can simply write a while (true) {} loop with a JavaScript sleep that pauses the Workflow until the next time you need to refresh exchange rates. Writing the Workflow this way might seem counterintuitive, because we've all had to learn over the course of our careers that writing applications isn't this easy. But, with Temporal, it actually is this easy!

import {
  defineQuery,
  proxyActivities,
  setHandler,
  sleep
} from '@temporalio/workflow';
import type * as activities from './activities';

const { getExchangeRates } = proxyActivities<typeof activities>({
  startToCloseTimeout: '1 minute',
});

type ExchangeRatesType = { [key: string]: number };

export const getExchangeRatesQuery = defineQuery<ExchangeRatesType | undefined, [string]>('getExchangeRates');

export async function exchangeRatesWorkflow(): Promise<void> {
  let rates: ExchangeRatesType | undefined = undefined;

  // Register a query handler that allows querying for the current rates
  setHandler(getExchangeRatesQuery, () => rates);

  while (true) {
    // Get the latest rates
    rates = await getExchangeRates();

    // Sleep until tomorrow at 12pm server time, and then get the rates again
    const today = new Date();
    const tomorrow = new Date(today);
    tomorrow.setHours(12, 0, 0, 0);
    tomorrow.setDate(tomorrow.getDate() + 1);
    await sleep(tomorrow.valueOf() - today.valueOf());
  }
}

That's the entire Workflow for caching exchange rates. The full source code is available in this GitHub repo. Notice that the code has no explicit references to a database or job queue. This Workflow is almost pure business logic, with a minimum of references to frameworks or services.

Workflow Queries

To run this Workflow, you can run a start-workflow.ts script as shown below. This script starts a Workflow and exits, leaving the Workflow running on the Worker. Note that only one Workflow with a given workflowId can run at any given time, so the following code also ensures that only one copy of this Workflow is running at any particular time.

import { WorkflowClient } from '@temporalio/client';
import { exchangeRatesWorkflow } from '../workflows';

run().catch((err) => {
  console.error(err);
  process.exit(1);
});

async function run() {
  const client = new WorkflowClient();

  const handle = await client.start(exchangeRatesWorkflow, {
    taskQueue: 'exchange-rates',
    workflowId: 'exchange-rates-workflow',
  });
  console.log(`Started workflow ${handle.workflowId}`);
}

Following is the output of start-workflow.ts.

Started workflow exchange-rates-workflow

After you start the Workflow, you can execute a Query to get the latest exchange rates using the following query-workflow.ts script.

import { WorkflowClient } from '@temporalio/client';
import { getExchangeRatesQuery } from '../workflows';
import { toYYYYMMDD } from '../shared';

const date: string = process.argv[2] || toYYYYMMDD(new Date()); 

run().catch((err) => {
  console.error(err);
  process.exit(1);
});

async function run() {
  const client = new WorkflowClient();

  const handle = client.getHandle('exchange-rates-workflow');
  console.log('Query exchange rates for', date);
  console.log(await handle.query(getExchangeRatesQuery, date));
}

Following is an example of the output from running query-workflow.ts.

Query exchange rates for 20220527
{
 AED: 3.6731,
 AFN: 88.999995,
 ALL: 112.95,
 AMD: 455.70744,
 ...
}

This Workflow is missing one key detail: a Continue-As-New. There's more about that later in this blog post.

Storing Historical Data

You can do more than just store the latest exchange rates. You can also store previous exchange rates. For example, suppose you want to store up to 30 days worth of historical exchange rates. You can store the rates in an in-memory JavaScript map in your Workflow, as shown in the following code.

const maxNumRates = 30;

export async function exchangeRatesWorkflow(): Promise<void> {
  const ratesByDay = new Map<string, ExchangeRatesType>();

  // Allow querying exchange rates by day
  setHandler(getExchangeRatesQuery, (date: string) => {
    return ratesByDay.get(date);
  });

  while (true) {
    const exchangeRates = await getExchangeRates();
    const today = new Date();
    // Store today's exchange rates
    ratesByDay.set(toYYYYMMDD(today), exchangeRates);
    console.log(toYYYYMMDD(today), exchangeRates);

    // Delete the oldest key if we have more than 30 entries
    const keys = Array.from(ratesByDay.keys());
    if (keys.length > maxNumRates) {
      ratesByDay.delete(keys[0]);
    }

    // Wait until tomorrow at 12pm to refresh the exchange rates
    const tomorrow = new Date(today);
    tomorrow.setHours(12, 0, 0, 0);
    tomorrow.setDate(tomorrow.getDate() + 1);
    await sleep(tomorrow.valueOf() - today.valueOf());
  }
}

Temporal makes ratesByDay durable, even though ratesByDay is just a normal JavaScript variable. That's because Temporal stores the entire history of events for this Workflow. If the machine running exchangeRatesWorkflow() crashes, Temporal can resume the Workflow on another machine by replaying the entire event history.

Continue-As-New

The exchangeRatesWorkflow can run for an unlimited period of time: days, months, even years. However, Temporal caps a Workflow at 50,000 events. (See the Time constraints section in Temporal Workflows.) In the exchangeRatesWorkflow, eight events are fired during each iteration of the while loop, assuming no API errors.

  1. EVENT_TYPE_TIMER_FIRED: the setTimeout() resolved and it's time to refresh the exchange rates
  2. EVENT_TYPE_ACTIVITY_TASK_SCHEDULED: the Temporal server scheduled the getExchangeRates() activity
  3. EVENT_TYPE_ACTIVITY_TASK_STARTED: the getExchangeRates() activity started executing
  4. EVENT_TYPE_ACTIVITY_TASK_COMPLETED: the getExchangeRates() activity completed successfully
  5. EVENT_TYPE_WORKFLOW_TASK_SCHEDULED: the Temporal server scheduled the Workflow logic that handles getExchangeRates()
  6. EVENT_TYPE_WORKFLOW_TASK_STARTED: the Workflow resumed
  7. EVENT_TYPE_WORKFLOW_TASK_COMPLETED: the Workflow paused
  8. EVENT_TYPE_TIMER_STARTED: the Workflow used setTimeout() to pause until tomorrow

With one API request per day, exchangeRatesWorkflow() can run for almost 6,250 days (approximately 17 years) before running into the 50,000 event limit. However, you should still avoid running into this limit. And that's what Continue-As-New is for.

You can think of Continue-As-New as restarting your Workflow from an initial state. The only data that exchangeRatesWorkflow() needs to respond to queries is the ratesByDay map, so exchangeRatesWorkflow() needs to Continue-As-New with a serialized version of the ratesByDay map. The exchangeRatesWorkflow() also needs to be able to resume from a previous state. Continue-As-New just calls exchangeRatesWorkflow() with an initial state. Following is the exchangeRatesWorkflow() workflow with an extra storedRatesByDay parameter that will contain the serialized Workflow state after a Continue-As-New.

const maxNumRates = 30;
const maxIterations = 1000;

// `storedRatesByDay` contains the serialized data from Continue-As-New, if available. Otherwise, just an
// empty array.
export async function exchangeRatesWorkflow(storedRatesByDay: Array<[string, any]> = []): Promise<any> {
  const ratesByDay = new Map<string, any>(storedRatesByDay);
  setHandler(getExchangeRatesQuery, (date: string) => {
    return ratesByDay.get(date)
  });

  // Max out at 1k iterations (~8k events) so we don't get too close to the 50k event limit
  for (let i = 0; i < maxIterations; ++i) {
    const exchangeRates = await getExchangeRates();
    const today = new Date();
    ratesByDay.set(toYYYYMMDD(today), exchangeRates);

    tomorrow.setHours(12, 0, 0, 0);
    tomorrow.setDate(tomorrow.getDate() + 1);
    await sleep(tomorrow.valueOf() - today.valueOf());
  }

  // After 1k iterations, trigger a Continue-As-New and finish the Workflow
  const state = Array.from(ratesByDay.entries());
  await continueAsNew<typeof exchangeRatesWorkflow>(state);
}

Moving On

Temporal Workflows make it easy to build stateful caching layers for APIs. With Temporal, you just write the business logic. Temporal handles persisting the data, ensuring only one copy of the Workflow is running, and allowing clients to query the cached API data. Next time you need to build a tool that pings an API on a regular schedule, try building it with Temporal.