It's official, **Node.js v14** is live and it's packed with new awesome features. The highlights in this release include an upgrade of V8 and many other improvements. Let's see what has changed and what's new

## What's new in Node.js v 14

Node.js is a JavaScript runtime using an event-driven I/O model which makes it extremely efficient when it comes to making scalable network applications.
Node.js offers a lot for developers and the latest version adds even more!

### 1. V8 engine upgraded to version 8.1

The new version of JavaScript engine bringing performance improvements as well as some new features like:

* **Optional Chaining** - which allows accessing the value of a property located deep within a chain of connected objects without the need to expressly validate that each reference in the chain,
* **Nullish Coalescing** - a logical operator returning its right-hand side operand when its left-hand side operand is null/undefined (and otherwise returning its left-hand side operand),
* **`Intl.DisplayNames`** - providing the consistency of language, region, and script display names translations,
* **`Intl.DateTimeFormat`** - `calendar` and `numberingSystem` options enabled.

### 2. Experimental Web Assembly System Interface

The 14.x release includes an experimental implementation of the Web Assembly System Interface (WASI) in order to provide better performance, cross-platform support, and could drastically simplify usage of native modules.

![Node.js v14 was released](https://graphqleditorcms.fra1.cdn.digitaloceanspaces.com/graphqleditorcms/blogpost/node-js-1730848098650.webp)

##### Credits: [undraw.co](https://undraw.co/)

### 3. Experimental Async Local Storage API

The numerous attempts to manage context across Async Calls resulted in experimental Async Hooks API being introduced in earlier versions of Node.js. As Async Local Storage was a key use case of Async Hooks API, the 14.x release brings an [experimental Async Local storage API](https://nodejs.org/api/async_hooks.html).

### 4. Diagnostic Report goes Stable

The diagnostic report was originally released in v12 as an experimental feature. in v14 it's been promoted to a stable feature. It provides triggered/on-demand reports containing useful insights about issues occurring on production including but not limited to unexpected errors, crashes, memory leaks, extensive CPU usage etc.

### 5. Hardening of the streams APIs

Latest release contains numerous changes to Streams implementation aiming to improve consistency across the Streams APIs i.e.:

* `http.OutgoingMessage` is similar to `stream.Writable`
* `net.Socket` behaves exactly like `stream.Duplex`.
* `autoDestroy` option is set 'true' by default and makes stream always call `_destroy` after ending

### 6. Removal of Experimental Modules Warning

Despite the need to include the `experimental-modules` flag was removed in v13 running EcmaScript Modules in Node.js would still result in a warning `ExperimentalWarning: The ESM module loader is experimental`. This warning was removed in v14 but the ESM implementation still remains experimental so be cautious when using ESM in production environments.

Quite a lot right? Node.js 14 will be the `Current` release for the next 6 months and then promoted to Long-term Support (LTS) in October 2020. This update looks really awesome and if you can't wait to get your hand on it [download Node.js version 14](https://nodejs.org/en/download/current).

What's new in Node.js v14

Ready for take-off?

For GraphQL cache can significantly improve performance and reduce redundancy, particularly when the same data is queried multiple times within a short timeframe. In this post, I'll go over implementing caching using [GraphQL Zeus](/docs/zeus) to fetch data from our custom CMS. No worries this can also be applied just as effectively to other GraphQL APIs, such as Hygraph or Hasura. Whether you’re working with a headless CMS, an e-commerce backend, or any other GraphQL-powered service, caching is just as important in every scenario and the implementation should look very similar.

## Why Add Caching?

Caching provides a number of advantages like:
 -  Reduced Server Load: By serving repeated requests from the cache, you avoid making unnecessary calls to the GraphQL server, which can be essential for scaling applications with high traffic.
 - Improved Performance: frequently requested data can be served directly from memory, reducing query response time significantly
 - Cost Efficiency: if your GraphQL API usage is metered (e.g., cloud-based APIs), caching significantly reduces the number of queries made, saving on usage costs

## [GraphQL Zeus](/docs/zeus) query example

Let’s start with a simple query I made using [GraphQL Zeus](/docs/zeus), which fetches homepage data from our CMS:

```ts
export const getHomepageData = async () => {
  try {
    const result = await chain('query')({
      onehomepageBySlug: [{ slug: 'home' }, HomepageDataSelector],
    });
    return result;
  } catch (error) {
    console.error('failed to fetch home data', error);
  }
};
```

This query retrieves all the homepage data at once and passes it to the relevant components. This allows users to update the homepage content directly through the CMS without needing to modify any code. Currently, this function is called in server-side props, meaning it triggers an API call every time the page is refreshed or visited.

To optimize this and reduce redundant API calls, we’ll implement caching by using the [node-lru-cache](https://github.com/isaacs/node-lru-cache) library.

## LRU cache

LRU stands for "Least Recently Used," a caching strategy that automatically removes the least recently accessed items when the cache reaches its limit. The node-lru-cache library offers several configuration options, but in our case to set up a basic GraphQL cache, we only need two key settings:

 - `ttl` (Time to Live): This setting defines how long an item stays in the cache before it’s considered expired, specified in milliseconds.
 - `ttlAutopurge`: When enabled, this option automatically deletes expired items from the cache. Without it, expired items are only purged when the cache is next accessed which can potentially lead it to grow unbounded.
 
```ts
import { LRUCache } from 'lru-cache';

const cache = new LRUCache({
  ttl: 1000 * 60 * 5, // Set time to live to 5 minutes
  ttlAutopurge: true,  // Automatically clean up expired entries
});
```

## Caching the query

To cache the query I mentioned earlier, we need to do three simple things:
1. Set up a cache key: This helps the cache know which entry to return when the same data is requested. You can name the key however you like, but it has to be unique to avoid conflicts.
2. Check if the cache contains the result: If the cache has the entry for that key, return the cached result.
3. Store the query result in the cache: After fetching the data, save the result in the cache for future use.

```ts
export const getHomepageData = async () => {
  const cacheKey = 'homepageData'; // Cache key for this entry
  if (cache.has(cacheKey)) { // Check if the cache contains this key
    return cache.get(cacheKey) as { onehomepageBySlug: HomepageDataType }; // Return cached result
  } 
  try {
    const result = await chain('query')({
      onehomepageBySlug: [{ slug: 'home' }, HomepageDataSelector],
    });
    cache.set(cacheKey, result); // Store query result in the cache
    return result;
  } catch (error) {
    console.error('failed to fetch home data', error);
  }
};
```

This approach results in two scenarios:

 - First visit: The query runs, fetches the data, and caches it for future use.
 - Subsequent visits (within the TTL): The cached result is returned, avoiding the need to make a new API request.

## Query with params (slug, locale)

As mentioned earlier, the cache key must be unique to avoid conflicts. This is especially important for queries that include parameters, such as `locale` (for localization) or `slug` (for specific blog pages). Without unique cache keys, you may end up with the same content being served for different locales or blog pages. To avoid this, it's best to use a dynamic cache key based on the query parameters.

```ts
export const getBlogpostBySlug = async ({ slug }: { slug: string }) => {
  const cacheKey = `Blogpost:${slug}`; // Unique cache key based on the slug
```

By using this dynamic approach, we ensure that the correct data is returned for the given slug. If you were to use a static cache key like 'blogpost', you'd always get the first cached blog post, regardless of which slug is provided. The same issue would arise with localization: without unique keys, you'd end up serving the wrong content for different locales.

## Its all about performance

GraphQL is all about efficiency — retrieving only the data you need (unlike REST). It makes sense to take that a step further to further enhance performance. With a GraphQL cache setup like this we can reduce redundant API calls and significantly speed up queries, especially for frequently accessed data like homepage content or blog posts. Dynamic cache keys based on query parameters ensure that the data is correctly localized or filtered according to specific slugs and [GraphQL Zeus](/docs/zeus) and selectors keep everything type-safe. Together this solution can greatly improve your app's speed and scalability. As mentioned, even if you're not using [GraphQL Zeus](/docs/zeus), the implementation should still be very similar to the above, so give it a try!
  

GraphQL cache: using LRU cache with GraphQL Zeus

Unlocking the Power of React 19

Welcome to a short post about a recent quality of life update to [GraphQL Zeus](/docs/zeus). If you're not familiar with [GraphQL Zeus](/docs/zeus) go ahead and read my [earlier post which breaks down its basics](/what-is-graphql-zeus). If you are lets go ahead and talk about the update!

### Graphql Fragments

GraphQL has long supported reusable fields natively with the use of fragments. If you're not familiar with them basically if you had the same fields in multiple queries you could define a fragment - a set of fields, and then reuse it instead of repeating all the fields every time. Lets say you had a user with some fields like name, email, address. Then you could use a fragment like this:

```ts
query getUser {
  user(id: 4) {
    ...userFields
  }
}

fragment userFields on User {
  name,
  email,
  address,
  avatar
}
```

For reusability you could put all your fragments in a fragments.js file and then use them across a project. Zeus already had a solution like Selectors (which work a bit similarly to that) but with the latest update it can now go a step further! :)

### Zeus fields - GraphQL spread operator

For our example lets say we need to get the posts data for our blog page where we display them in a grid, usually the query that would look something like this:

```ts
const posts = await Chain('http://example.com/api/graphql')('query')({
  posts: [
    {
      title: true,
      coverImage: true,
      publishedAt: true,
      slug: true,
      content: { markdown: true },
    },
  ],
});
```

With Zeus 6.0.0 you can simply use a spread operator `...fields` with the TypeScript type from the schema (eg. `Post`) to simply get all the fields available for that type:

```ts
const posts = await Chain('http://example.com/api/graphql')('query')({
  posts: [
    {
      ...fields('Post'),
    },
  ],
});
```

### Never go full REST

With this, we now have a convenient quality-of-life improvement for cases where you just want to quickly retrieve all the fields for a type. That said it's important to remember what GraphQL is all about - getting exactly what you requested without overfetching. So don't just use `...fields` everywhere or you'll defeat the entire purpose of using GraphQL in the first place and turn it into REST, always pulling way more data than necessary.


What's new in Node.js v14

What's new in Node.js v 14

1. V8 engine upgraded to version 8.1

2. Experimental Web Assembly System Interface

Credits: undraw.co

3. Experimental Async Local Storage API

4. Diagnostic Report goes Stable

5. Hardening of the streams APIs

6. Removal of Experimental Modules Warning

Check out our other blogposts

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