Header image

TypeScript – How To Avoid “Any”?

26/09/2022

1.55k

  • The harmful effects of any
  • Avoiding any
TypeScript - How To Avoid "Any"?

How to avoid any?

In the previous blog – Typescript and “any” type, I introduced TypeScript and what exactly is any type.

In this blog, I’d like to show more about the harmful effects when using any and introduce some built-in types, features and customs types that you can use to avoid any.

The harmful effects of any

While TypeScript is a type checker, any type tells TypeScript to skip/disable type-checking. On the other hand, due to the nature of JavaScript, in some cases providing accurate types isn’t a simple task. In such situations, programmers are tempted to use any.

In most situations using or implicit any – a type that allows to store anything and skip type checkers, programmers can’t guarantee what type the value is stored and how it will be used. Furthermore, when the code is executed at runtime, errors may occur even though they were not warned before. For example:

let result; // Variable 'result' implicitly has an 'any' type.
result = 10.123; // Number is stored at 'result'

console.log(result.toFixed()); // `toFixed()` is a method of `number`

result.willExist(); // `willExist()` isn't a method of `number`, but no errors appear.

Because of that, the use of any is something that should be minimized as much as possible, to ensure the source code does not encounter any errors.

Avoiding any

Based on the basics of TypeScript and Everyday Types, in this blog, I’ll be sharing what I learned and used to write code without any.

Type aliases & Interfaces

A type alias is exactly a name for any type, you can actually use a type alias to give a name to any type at all, not just an object type. For example:

// Type alias
type Point = {
  x: number,
  y: number
};

type ID = number | string;

An interface declaration is another way to name an object type:

// Interface
interface IPoint {
  x: number,
  y: number
};

Differences between Type Aliases and Interfaces:

// Override
type Point = { // TypeError: Duplicate identifier 'Point'.
  a: string
};
interface IPoint {
  a: string
};

Union & Literal types

A union type is a type formed from two or more other types, representing values that may be any one of those types.

// Union types
let anyNumber: string | number;

// Usage
anyNumber = '123';
anyNumber = 123;
anyNumber = true; // TypeError: Type 'boolean' is not assignable to type 'string | number'.

In addition to the general types of string and number, you can refer to specific value of strings and numbers.
By combining literals into unions, you can express a much more useful concept. For example:

// Literal types
let direction: 'top' | 'left' | 'right' | 'bottom';

direction = 'top';
direction = 'top-right'; // TypeError: Type '"top-right"' is not assignable to type '"top" | "left" | "right" | "bottom"'

Type assertions

Sometimes you will have information about the type of a value that TypeScript can’t know about.

For example, if you’re using document.getElementById, TypeScript only knows that this will return some kind of HTMLElement, but you might know that your page will always have an HTMLCanvasElement with a given ID.

In this situation, you can use a type assertion to specify a more specific type:

// Type assertions
const myCanvas = document.getElementById('main-canvas') as HTMLCanvasElement;

Generics

// Example
const getRandomNumber = (items: number[]): number => {
  let randomIndex = Math.floor(Math.random() * items.length);
  return items[randomIndex];
};
const getRandomString = (items: string[]): string => {
  let randomIndex = Math.floor(Math.random() * items.length);
  return items[randomIndex];
};

// Generics function
const getRandomGeneric = <T>(items: T[]): T => {
  let randomIndex = Math.floor(Math.random() * items.length);
  return items[randomIndex];
};

// Usage
const teams: string[] = ['frontend', 'ios', 'android'];
const numbers: number[] = [1, 2, 3, 4, 5, 6, 7, 9, 10];

const randomResult1 = getRandomGeneric<string>(teams);
const randomResult2 = getRandomGeneric<number>(numbers);

In the example above, the getRandomGeneric is the generic identity function that worked over a range of types.

The type of generic functions is just like those of non-generic functions, with the type parameters listed first, similarly to function declarations:

const identity = <Type>(param: Type): Type => {
  return param;
};

When calling identity a function, you now will also need to specify the type of param that the function will use.

The detail above just Generic identity functions, you can read more generics Generic link

Unknown

unknown is what should be used when you don’t know a proper type of object. Unlike any, it doesn’t let you do any operations on a value until you know its type (skip/disable type-checker).

When you unknow something, you need to check before executing. For example:

const invokeAnything = (callback: unknown): void => {
  if (typeof callback === 'function') {
    callback();
  }
  if (typeof callback === 'number') {
    console.log(callback);
  }
  if (typeof callback === 'string') {
    console.log(callback.toUpperCase());
  }
};

// Usage
invokeAnything('typescript'); // Result: TYPESCRIPT

Record for basic object

Probably, nearly every JavaScript developer at some time has used an object as a map-like collection. However, with strict types, it may not be that obvious how to type this. So, you may use interface, but this way you can’t add anything to the object. Then, you need to think about using Record.

The definition:

type Record<K extends keyof any, T> = {
  [P in K]: T;
};

And the usage:

// Usage
const dict: Record<string, number> = {};
dict.a = 1;
dict.b = 'a'; // TypeError: "a" is not assignable to type number

let obj: Record<string, number>;
obj = {
  a: 1,
  b: 2
};

As you can see, it means that the developer can enter any key, but the value has to be of a specific type.

Conclusion

The TypeScript compiler is so powerful. There are so many things we can do with it.

any type can be avoided with more advanced technics such as interface, type intersection, and the use of generics, etc.

Hope you like it! Enjoy TypeScript and make the code without any!

Author: Anh Nguyen

Related Blog

prd-thumb-draft-product

Software Development

+0

    TypeScript And “Any” Type

    TypeScript is a strongly typed programming language that builds on JavaScript, giving you a better ability to detect errors and describe your code. But sometimes you don't know the exact type of value that you're using because it comes from user input or a third-party API. In this case, you want to skip the type checking and allow the value to pass through the compile check. The TypeScript any type is the perfect solution for you because if you use it, the TypeScript compiler will not complain about the type issue. This blog will help you understand the any type in TypeScript, but before doing that, let's begin with some basic concepts! What is TypeScript? TypeScript checks a program for errors before execution and does so based on the kinds of values; it’s a static type checker. Superset of JavaScript TypeScript is a language that is a superset of JavaScript: JS syntax is, therefore, legal TS. However, TypeScript is a typed superset that adds rules about how different kinds of values can be used. Runtime Behavior TypeScript is also a programming language that preserves JavaScript's runtime behavior. This means that if you move code from JavaScript to TypeScript, it is guaranteed to run the same way, even if TypeScript thinks the code has type errors. Erased Types Roughly speaking, once TypeScript’s compiler is done with checking your code, it erases the types to produce the resulting compiled code. This means that once your code is compiled, the resulting plain JS code has no type information. An easy way of understanding TypeScript A languageA superset of JavaScriptPreserver the runtime behavior of JavaScriptType checker layer JavaScript + Types = TypeScript Basic typing Type annotations TypeScript uses type annotations to explicitly specify types for identifiers such as variables, functions, objects, etc. // Syntax : type Once an identifier is annotated with a type, it can be used as that type only. If the identifier is used as a different type, the TypeScript compiler will issue an error. let counter: number; counter = 1; counter = 'Hello'; // Error: Type '"Hello"' is not assignable to type 'number'. The following shows other examples of type annotations: let name: string = 'John'; let age: number = 25; let active: boolean = true; // Array let names: string[] = ['John', 'Jane', 'Peter', 'David', 'Mary']; // Object let person: { name: string; age: number }; person = { name: 'John', age: 25 }; // Valid // Function let sayHello : (name: string) => string; sayHello = (name: string) => { return `Hello ${name}`; }; Type inference Type inference describes where and how TypeScript infers types when you don’t explicitly annotate them. For example: // Annotations let counter: number; // Inference: TypeScript will infer the type the `counter` to be `number` let counter = 1; Likewise, when you assign a function parameter a value, TypeScript infers the type of the parameter to the type of the default value. For example: // TypeScript infers type of the `max` parameter to be `number` const setCounter = (max = 100) => { // ... } Similarly, TypeScript infers the return type to the type of the return value: const increment = (counter: number) => { return counter++; } // It is the same as: const increment = (counter: number) : number => { return counter++; } The following shows other examples of type inference: const items = [0, 1, null, 'Hi']; // (number | string)[] const mixArr = [new Date(), new RegExp('\d+')]; // (RegExp | Date)[] const increase = (counter: number, max = 100) => { return counter++; }; // (counter: number, max?: number) => number Contextual typing TypeScript uses the locations of variables to infer their types. This mechanism is known as contextual typing. For example: document.addEventListener('click', (event) => { console.log(event.button); // Valid }); In this example, TypeScript knows that the event the parameter is an instance of MouseEvent because of the click event. However, when you change the click event to the scroll the event, TypeScript will issue an error: document.addEventListener('scroll', (event) => { console.log(event.button); // Compile error }); // Property 'button' does not exist on type 'Event'. TypeScript knows that the event in this case, is an instance of UIEvent, not a MouseEvent. And UIEvent does not have the button property, therefore, TypeScript throws an error. Other examples of contextual typing // Array members const names = ['John', 'Jane', 'Peter', 'David', 'Mary']; // string[] names.map(name => name.toUpperCase()); // (name: string) => string // Type assertions const myCanvas = document.getElementById('main-canvas') as HTMLCanvasElement; Type inference vs Type annotations Type inferenceType annotationsTypeScript guesses the typeYou explicitly tell TypeScript the type What exactly is TypeScript any? When you don’t explicitly annotate and TypeScript can't infer exactly the type, that means you declare a variable without specifying a type, TypeScript assumes that you use the any type. This practice is called implicit typing. For example: let result; // Variable 'result' implicitly has an 'any' type. So, what exactly is any? TypeScript any is a particular type that you can use whenever you don't want a particular value to cause type-checking errors. That means the TypeScript compiler doesn't complain or issue any errors. When a value is of type any, you can access any properties of it, call it like a function, assign it to (or from) a value of any type, or pretty much anything else that’s syntactically legal: let obj: any = { x: 0 }; // None of the following lines of code will throw compiler errors. // Using `any` disables all further type checking, and it is assumed // you know the environment better than TypeScript. obj.foo(); obj(); obj.bar = 100; obj = 'hello'; const n: number = obj; Looking back at an easier-to-understand any: A special type.Skip/Disable type-checking.TypeScript doesn't complain or issue any errors.Default implicit typing is any. Note that to disable implicit typing to the any type, you change the noImplicitAny option in the tsconfig.json file to true. Why does TypeScript provide any type? As described above, while TypeScript is a type checker, any type tells TypeScript to skip/disable type-checking. Whether TypeScript has made a mistake here and why it provides any type? In fact, sometimes the developer can't determine the type of value or can't determine the return value from the 3rd party. In most cases they use any type or implicit typing as any. So they seem to think that TypeScript provides any to do those things. So, is that the root reason that TypeScript provides any? Actually, I think there is a more compelling reason for TypeScript providing any that the any type provides you with a way to work with the existing JavaScript codebase. It allows you to gradually opt-in and opt out of type checking during compilation. Therefore, you can use the any type for migrating a JavaScript project over to TypeScript. Conclusion TypeScript is a Type checker layer. The TypeScript any type allows you to store a value of any type. It instructs the compiler to skip type-checking. Use the any type to store a value when you migrate a JavaScript project over to a TypeScript project. In the next blog, I will show you more about the harmful effects of any and how to avoid them. Hope you like it! See you in the next blog! Reference TypeScript handbookTypeScript tutorial Author: Anh Nguyen

    07/09/2022

    1.07k

    Software Development

    +0

      TypeScript And “Any” Type

      07/09/2022

      1.07k

      Our success stories

      +0

        SupremeTech Partners with AWS and MegazoneCloud to Drive AI-Powered Business Growth

        SupremeTech is pleased to announce our collaboration with AWS and MegazoneCloud for an upcoming event, Harnessing AI on AWS: Transforming Software Builders for the Future, scheduled for March 20, 2025, in Da Nang. This event is about giving software companies the tools, strategies, and real-world solutions they need to spark innovation, boost performance, and even take their businesses global with AI. The software world is changing fast, and Artificial Intelligence is leading the charge. Companies that tap into AI on AWS are finding new ways to grow, streamline their workflows, and stay ahead of the game. This event offers software firms in Da Nang and beyond the chance to see how AI can level up your business and prepare them for the future. SupremeTech’s Contribution to the Event In partnership with AWS and MegazoneCloud, SupremeTech will share valuable insights from our experience mastering complex technical challenges, such as Aurora MySQL upgrades. We will break it down into practical tips and solutions that software companies can use to fine-tune their infrastructure and grow smarter. The SupremeTech partners with AWS and MegazoneCloud event is structured into two key sessions: Morning Session: Accelerating Technical Performance Enhancing Product Value with AI/ML Services: Attendees will learn how AWS’s advanced tools, including Amazon SageMaker and Bedrock, can optimize infrastructure, improve performance, and reduce time to market.Real-World Solutions: Megazone will present hands-on demonstrations of AI services on AWS, offering insights into seamless integration and proven strategies derived from their own expertise. Afternoon Session: Strategic Growth Expansion Scaling with AWS Programs: Discover how AWS initiatives such as the ISV Accelerate and Workload Migration Program (WMP) can accelerate market expansion and support rapid business growth.Global Opportunities with MegazoneCloud: Explore how MegazoneCloud’s extensive partner network and the AWS ecosystem can help software companies bring their products to international markets. This event is more than a technical gathering; it represents a strategic opportunity for software businesses to advance their capabilities and adopt AI effectively on AWS. Why You Should Attend Actionable Strategies: Gain practical knowledge to integrate AI into your business operations.Expert Insights: Benefit from the expertise of SupremeTech, AWS, and MegazoneCloud leaders with proven success in the AI landscape.Networking: Connect with industry peers and potential partners within Da Nang’s growing tech community.Global Expansion: Access tools and programs to scale your business internationally. Event Details Date: March 20, 2025Location: Voco Ma Belle Danang - 168 Vo Nguyen Giap Street, Son Tra Da Nang, Vietnam Register Today to Stay Ahead in the AI Era Do not miss this opportunity to leverage AI on AWS and position your software business for success. Join the event that SupremeTech partners with AWS and MegazoneCloud on March 20, 2025, to grab the insights and tools you need to lead the charge in innovation and growth. Click Here to Register Now and take the first step toward a future of innovation and growth. Related articles about AWS: Mastering AWS Lambda: An Introduction to Serverless ComputingCreate Your First AWS Lambda Function (Node.js, Python, and Go)Triggers and Events: How AWS Lambda Connects with the WorldBest Practices for Building Reliable AWS Lambda Functions

        11/03/2025

        22

        Ngan Phan

        Our success stories

        +0

          SupremeTech Partners with AWS and MegazoneCloud to Drive AI-Powered Business Growth

          11/03/2025

          22

          Ngan Phan

          E-commerce (Shopify)

          +0

            How to Build a High-Performing E-commerce Store

            E-commerce is growing every year and is set to make heavy profits, with more and more people opting for it. However, with ever-growing competition in this domain, you need to stand out to stay afloat. You have to compete with giants like Amazon, eBay, and Alibaba, which can give you a tough time. In this blog, we will discuss building a high-performing e-commerce store in detail. So, let’s get started. See more: Exploring 7 Top Online Food Ordering Systems for Small BusinessesSmooth Sailing: How to Migrate Website to Shopify? Step-by-Step Procedure for Building an E-commerce Store E-commerce stores are becoming increasingly popular due to their range of products on a single platform, short delivery time, and easy payment options. Let’s go through a step-by-step procedure for building an attractive and high-performing e-commerce store. Step 1: Choose Your Platform Each e-commerce store is unique and has its own goals and target audience. Hence, you need to choose an ideal e-commerce platform for your needs. There are a number of options available including Shopify, WooCommerce, Squarespace, WordPress and more.  These eCommerce platforms have their own features, so you should discuss each one with your development team and pick the most suitable one for your needs. Step 2: Create an Account on the Chosen Platform Once you have chosen your eCommerce store platform, you need to purchase the subscription, in case it is not open source. These platforms offer a variety of plans, uptime guarantees, and security features.  If you have chosen an all-in-one e-commerce platform, all you need to do is go to the provider’s website and create an account. Then, you select a plan and pay for it if it is not free. Step 3: Choose a Template After you have decided on your eCommerce platform, you will have a variety of options regarding templates. Each has its own colors, fonts, and layouts, which gives an e-commerce store a consistent look and feel. Templates can be free or premium ones, for which you need to pay. Generally speaking, paid ones offer more features and designs. This saves time which will be spent on coming up with designs from scratch. Step 4: Build Your Webpages & Product Pages You must not use the template as it is; you should customize it according to your requirements. Some common customizations include adding your logo and contact details.  Other changes could be adding product images, configuring your site navigation, and building check-out and returns pages. Step 5: Write Product Descriptions As it is not a brick-and-mortar store where customers can view the products or feel them, you need to work on your product descriptions along with images. They need to be very accurate, easy to understand, and detailed. It should include basic details, along with information about who the product is meant for and where it can be used.  Product images should be high-definition and of the same size, and should show the product from all possible angles.  Step 6: Set Up Payment Gateway As most of your customers will opt for online payments and not Cash on Delivery, you need to have a secure payment gateway. So, integrate secure payment options on your e-Commerce store, which are hassle-free, fast and secure at the same time.  If you redirect your customers to other platforms like PayPal, ensure that data is fully encrypted.  If your payment options are not convenient, no matter how good your product catalog is, customers will not come back. Step 7: Integrate Shipping  The platform you have chosen for your e-Commerce store may allow integrated shipping along with selling. This creates a seamless customer experience and lets you focus on selling products.  You also need to decide on your shipping policy, such as free shipping, flat rates, variable fees, etc. Along with this, you need to decide on your returns and refund policy to make the situation clear for your customers. Step 8: Test & Launch Your e-Commerce Store After all the hard work, it is time to test your e-commerce store before launching it. You should do rigorous testing to ensure there are no bottlenecks and pain points. You can do the testing in-house or outsource the task.  Check all links, buttons, and navigation options and ensure they work. Payment processing should also be thoroughly checked. Your e-commerce store should be compatible with desktop, mobile devices, and all browsers. Once everything has been checked, you are ready for launch. Popular eCommerce Platforms To Consider Several options are available for e-commerce platforms. Let’s discuss some popular ones to help you choose. Shopify Shopify is an eCommerce platform suitable for Web, iOS, and Android. It is easy to set up and has all the necessary tools. The support and resources provided are best in class, which makes it popular and effective.  The only constraint of Shopify is that it can be expensive if you add many extra apps. Many eCommerce stores currently run on Shopify, which has been around for 18 years and is ideal for small businesses that want to go online. BigCommerce BigCommerce is an e-commerce platform suitable for Web, iOS, and Android devices. It is the SMB version of a very popular enterprise eCommerce platform. It has integrated features like shipping and taxes to encourage established businesses online. However, it is not recommended for small retailers setting up their businesses.   It also enables listing your products on e-commerce giants like eBay, Walmart, and Amazon.  As a result, customers do not necessarily have to buy from your store.   BigCommerce has 12 free themes, all of which have a great look. They also have a drag-and-drop site builder that can be used to customize the look.  WooCommerce   WooCommerce is an e-commerce platform for the Web, iOS, and Android. It provides all the flexibility of WordPress, is widely supported, and has many apps and integrations. Installing WooCommerce on your website is very easy, similar to installing any  other plugin on WordPress. If you use WordPress for your eCommerce store, you should ideally go for WooCommerce. Wrapping Up E-commerce is still nascent and will continue to grow over the decade. It provides a range of products and the convenience of buying them from your home from across the world. So, whether you are starting or have an established business, you should consider going online, as it will increase your reach. After considering everything, you should choose your e-commerce store platform. This will ensure that you have a high-performing e-commerce store. For building your e-Commerce store, get in touch with SupremeTech. 

            10/03/2025

            25

            E-commerce (Shopify)

            +0

              How to Build a High-Performing E-commerce Store

              10/03/2025

              25

              Knowledge

              +0

                Best Practices for Building Reliable AWS Lambda Functions

                Welcome back to the "Mastering AWS Lambda with Bao" series! The previous episode explored how AWS Lambda connects to the world through AWS Lambda triggers and events. Using S3 and DynamoDB Streams triggers, we demonstrated how Lambda automates workflows by processing events from multiple sources. This example provided a foundation for understanding Lambda’s event-driven architecture. However, building reliable Lambda functions requires more than understanding how triggers work. To create AWS lambda functions that can handle real-world production workloads, you need to focus on optimizing performance, implementing robust error handling, and enforcing strong security practices. These steps optimize your Lambda functions to be scalable, efficient, and secure. In this episode, SupremeTech will explore the best practices for building reliable AWS Lambda functions, covering two essential areas: Optimizing Performance: Reducing latency, managing resources, and improving runtime efficiency.Error Handling and Logging: Capturing meaningful errors, logging effectively with CloudWatch, and setting up retries. Adopting these best practices, you’ll be well-equipped to optimize Lambda functions that thrive in production environments. Let’s dive in! Optimizing Performance Optimize the Lambda function's performance to run efficiently with minimal latency and cost. Let's focus first on Cold Starts, a critical area of concern for most developers. Understanding Cold Starts What Are Cold Starts? A Cold Start occurs when AWS Lambda initializes a new execution environment to handle an incoming request. This happens under the following circumstances: When the Lambda function is invoked for the first time.After a period of inactivity (execution environments are garbage collected after a few minutes of no activity – meaning it will be shut down automatically).When scaling up to handle additional concurrent requests. Cold starts introduce latency because AWS needs to set up a new execution environment from scratch. Steps Involved in a Cold Start: Resource Allocation:AWS provisions a secure and isolated container for the Lambda function.Resources like memory and CPU are allocated based on the function's configuration.Execution Environment Initialization:AWS sets up the sandbox environment, including:The /tmp directory is for temporary storage.Networking configurations, such as Elastic Network Interfaces (ENI), for VPC-based Lambdas.Runtime Initialization:The specified runtime (e.g., Node.js, Python, Java) is initialized.For Node.js, this involves loading the JavaScript engine (V8) and runtime APIs.Dependency Initialization:AWS loads the deployment package (your Lambda code and dependencies).Any initialization code in your function (e.g., database connections, library imports) is executed.Handler Invocation:Once the environment is fully set up, AWS invokes your Lambda function's handler with the input event. Cold Start Latency Cold start latency varies depending on the runtime, deployment package size, and whether the function runs inside a VPC: Node.js and Python: ~200ms–500ms for non-VPC functions.Java or .NET: ~500ms–2s due to heavier runtime initialization.VPC-Based Functions: Add ~500ms–1s due to ENI initialization. Warm Starts In contrast to cold starts, Warm Starts reuse an already-initialized execution environment. AWS keeps environments "warm" for a short time after a function is invoked, allowing subsequent requests to bypass initialization steps. Key Differences: Cold Start: New container setup → High latency.Warm Start: Reused container → Minimal latency (~<100ms). Reducing Cold Starts Cold starts can significantly impact the performance of latency-sensitive applications. Below are some actionable strategies to reduce cold starts, each with good and bad practice examples for clarity. 1. Use Smaller Deployment Packages to optimize lambda function Good Practice: Minimize the size of your deployment package by including only the required dependencies and removing unnecessary files.Use bundlers like Webpack, ESBuild, or Parcel to optimize your package size.Example: const DynamoDB = require('aws-sdk/clients/dynamodb'); // Only loads DynamoDB, not the entire SDK Bad Practice: Bundling the entire AWS SDK or other large libraries without considering modular imports.Example: const AWS = require('aws-sdk'); // Loads the entire SDK, increasing package size Why It Matters: Smaller deployment packages load faster during the initialization phase, reducing cold start latency. 2. Move Heavy Initialization Outside the Handler Good Practice: Place resource-heavy operations, such as database or SDK client initialization, outside the handler function so they are executed only once per container lifecycle – a cold start.Example: const DynamoDB = new AWS.DynamoDB.DocumentClient(); exports.handler = async (event) => {     const data = await DynamoDB.get({ Key: { id: '123' } }).promise();     return data; }; Bad Practice: Reinitializing resources inside the handler for every invocation.Example: exports.handler = async (event) => {     const DynamoDB = new AWS.DynamoDB.DocumentClient(); // Initialized on every call     const data = await DynamoDB.get({ Key: { id: '123' } }).promise();     return data; }; Why It Matters: Reinitializing resources for every invocation increases latency and consumes unnecessary computing power. 3. Enable Provisioned Concurrency1 Good Practice: Use Provisioned Concurrency to pre-initialize a set number of environments, ensuring they are always ready to handle requests.Example:AWS CLI: aws lambda put-provisioned-concurrency-config \ --function-name myFunction \ --provisioned-concurrent-executions 5 AWS Management Console: Why It Matters: Provisioned concurrency ensures a constant pool of pre-initialized environments, eliminating cold starts entirely for latency-sensitive applications. 4. Reduce Dependencies to optimize the lambda function Good Practice: Evaluate your libraries and replace heavy frameworks with lightweight alternatives or native APIs.Example: console.log(new Date().toISOString()); // Native JavaScript API Bad Practice: Using heavy libraries for simple tasks without considering alternatives.Example: const moment = require('moment'); console.log(moment().format()); Why It Matters: Large dependencies increase the deployment package size, leading to slower initialization during cold starts. 5. Avoid Unnecessary VPC Configurations Good Practice: Place Lambda functions outside a VPC unless necessary. If a VPC is required (e.g., to access private resources like RDS), optimize networking using VPC endpoints.Example:Use DynamoDB and S3 directly without placing the Lambda inside a VPC. Bad Practice: Deploying Lambda functions inside a VPC unnecessarily, such as accessing services like DynamoDB or S3, which do not require VPC access.Why It’s Bad: Placing Lambda in a VPC introduces additional latency due to ENI setup during cold starts. Why It Matters: Functions outside a VPC initialize faster because they skip ENI setup. 6. Choose Lightweight Runtimes to optimize lambda function Good Practice: Use lightweight runtimes like Node.js or Python for faster initialization than heavier runtimes like Java or .NET.Why It’s Good: Lightweight runtimes require fewer initialization resources, leading to lower cold start latency. Why It Matters: Heavier runtimes have higher cold start latency due to the complexity of their initialization process. Summary of Best Practices for Cold Starts AspectGood PracticeBad PracticeDeployment PackageUse small packages with only the required dependencies.Bundle unused libraries, increasing the package size.InitializationPerform heavy initialization (e.g., database connections) outside the handler.Initialize resources inside the handler for every request.Provisioned ConcurrencyEnable provisioned concurrency for latency-sensitive applications.Ignore provisioned concurrency for high-traffic functions.DependenciesUse lightweight libraries or native APIs for simple tasks.Use heavy libraries like moment.js without evaluating lightweight alternatives.VPC ConfigurationAvoid unnecessary VPC configurations; use VPC endpoints when required.Place all Lambda functions inside a VPC, even when accessing public AWS services.Runtime SelectionChoose lightweight runtimes like Node.js or Python for faster initialization.Use heavy runtimes like Java or .NET for simple, lightweight workloads. Error Handling and Logging Error handling and logging are critical for optimizing your Lambda functions are reliable and easy to debug. Effective error handling prevents cascading failures in your architecture, while good logging practices help you monitor and troubleshoot issues efficiently. Structured Error Responses Errors in Lambda functions can occur due to various reasons: invalid input, AWS service failures, or unhandled exceptions in the code. Properly structured error handling ensures that these issues are captured, logged, and surfaced effectively to users or downstream services. 1. Define Consistent Error Structures Good Practice: Use a standard error format so all errors are predictable and machine-readable.Example: {   "errorType": "ValidationError",   "message": "Invalid input: 'email' is missing",   "requestId": "12345-abcd" } Bad Practice: Avoid returning vague or unstructured errors that make debugging difficult. { "message": "Something went wrong", "error": true } Why It Matters: Structured errors make debugging easier by providing consistent, machine-readable information. They also improve communication with clients or downstream systems by conveying what went wrong and how it should be handled. 2. Use Custom Error Classes Good Practice: In Node.js, define custom error classes for clarity: class ValidationError extends Error {   constructor(message) {     super(message);     this.name = "ValidationError";     this.statusCode = 400; // Custom property   } } // Throwing a custom error if (!event.body.email) {   throw new ValidationError("Invalid input: 'email' is missing"); } Bad Practice: Use generic errors for everything, making identifying or categorizing issues hard.Example: throw new Error("Error occurred"); Why It Matters: Custom error classes make error handling more precise and help segregate application errors (e.g., validation issues) from system errors (e.g., database failures). 3. Include Contextual Information in Logs Good Practice: Add relevant information like requestId, timestamp, and input data (excluding sensitive information) when logging errors.Example: console.error({     errorType: "ValidationError",     message: "The 'email' field is missing.",     requestId: context.awsRequestId,     input: event.body,     timestamp: new Date().toISOString(), }); Bad Practice: Log errors without any context, making debugging difficult.Example: console.error("Error occurred"); Why It Matters: Contextual information in logs makes it easier to identify what triggered the error and where it happened, improving the debugging experience. Retry Logic Across AWS SDK and Other Services Retrying failed operations is critical when interacting with external services, as temporary failures (e.g., throttling, timeouts, or transient network issues) can disrupt workflows. Whether you’re using AWS SDK, third-party APIs, or internal services, applying retry logic effectively can ensure system reliability while avoiding unnecessary overhead. 1. Use Exponential Backoff and Jitter Good Practice: Apply exponential backoff with jitter to stagger retry attempts. This avoids overwhelming the target service, especially under high load or rate-limiting scenarios.Example (General Implementation): async function retryWithBackoff(fn, retries = 3, delay = 100) {     for (let attempt = 1; attempt <= retries; attempt++) {         try {             return await fn();         } catch (error) {             if (attempt === retries) throw error; // Rethrow after final attempt             const backoff = delay * 2 ** (attempt - 1) + Math.random() * delay; // Add jitter             console.log(`Retrying in ${backoff.toFixed()}ms...`);             await new Promise((res) => setTimeout(res, backoff));         }     } } // Usage Example const result = await retryWithBackoff(() => callThirdPartyAPI()); Bad Practice: Retrying without delays or jitter can lead to cascading failures and amplify the problem. for (let i = 0; i < retries; i++) {     try {         return await callThirdPartyAPI();     } catch (error) {         console.log("Retrying immediately...");     } } Why It Matters: Exponential backoff reduces pressure on the failing service, while jitter randomizes retry times, preventing synchronized retry storms from multiple clients. 2. Leverage Built-In Retry Mechanisms Good Practice: Use the built-in retry logic of libraries, SDKs, or APIs whenever available. These are typically optimized for the specific service.Example (AWS SDK): const DynamoDB = new AWS.DynamoDB.DocumentClient({     maxRetries: 3, // Number of retries     retryDelayOptions: { base: 200 }, // Base delay in ms }); Example (Axios for Third-Party APIs):Use libraries like axios-retry to integrate retry logic for HTTP requests. const axios = require('axios'); const axiosRetry = require('axios-retry'); axiosRetry(axios, {     retries: 3, // Retry 3 times     retryDelay: (retryCount) => retryCount * 200, // Exponential backoff     retryCondition: (error) => error.response.status >= 500, // Retry only for server errors }); const response = await axios.get("https://example.com/api"); Bad Practice: Writing your own retry logic unnecessarily when built-in mechanisms exist, risking suboptimal implementation. Why It Matters: Built-in retry mechanisms are often optimized for the specific service or library, reducing the likelihood of bugs and configuration errors. 3. Configure Service-Specific Retry Limits Good Practice: Set retry limits based on the service's characteristics and criticality.Example (AWS S3 Upload): const s3 = new AWS.S3({ maxRetries: 5, // Allow more retries for critical operations retryDelayOptions: { base: 300 }, // Slightly longer base delay }); Example (Database Queries): async function queryDatabaseWithRetry(queryFn) {     await retryWithBackoff(queryFn, 5, 100); // Retry with custom backoff logic } Bad Practice: Allowing unlimited retries can cause resource exhaustion and increase costs. while (true) {     try {         return await callService();     } catch (error) {         console.log("Retrying...");     } } Why It Matters: Excessive retries can lead to runaway costs or cascading failures across the system. Always define a sensible retry limit. 4. Handle Transient vs. Persistent Failures Good Practice: Retry only transient failures (e.g., timeouts, throttling, 5xx errors) and handle persistent failures (e.g., invalid input, 4xx errors) immediately.Example: const isTransientError = (error) =>     error.code === "ThrottlingException" || error.code === "TimeoutError"; async function callServiceWithRetry() {     await retryWithBackoff(() => {         if (!isTransientError(error)) throw error; // Do not retry persistent errors         return callService();     }); } Bad Practice: Retrying all errors indiscriminately, including persistent failures like ValidationException or 404 Not Found. Why It Matters: Persistent failures are unlikely to succeed with retries and can waste resources unnecessarily. 5. Log Retry Attempts Good Practice: Log each retry attempt with relevant context, such as the retry count and delay. async function retryWithBackoff(fn, retries = 3, delay = 100) {     for (let attempt = 1; attempt <= retries; attempt++) {         try {             return await fn();         } catch (error) {             if (attempt === retries) throw error;             console.log(`Attempt ${attempt} failed. Retrying in ${delay}ms...`);             await new Promise((res) => setTimeout(res, delay));         }     } } Bad Practice: Failing to log retries makes debugging or understanding the retry behavior difficult. Why It Matters: Logs provide valuable insights into system behavior and help diagnose retry-related issues. Summary of Best Practices for Retry logic AspectGood PracticeBad PracticeRetry LogicUse exponential backoff with jitter to stagger retries.Retry immediately without delays, causing retry storms.Built-In MechanismsLeverage AWS SDK retry options or third-party libraries like axios-retry.Write custom retry logic unnecessarily when optimized built-in solutions are available.Retry LimitsDefine a sensible retry limit (e.g., 3–5 retries).Allow unlimited retries, risking resource exhaustion or runaway costs.Transient vs PersistentRetry only transient errors (e.g., timeouts, throttling) and fail fast for persistent errors.Retry all errors indiscriminately, including persistent failures like validation or 404 errors.LoggingLog retry attempts with context (e.g., attempt number, delay,  error) to aid debugging.Fail to log retries, making it hard to trace retry behavior or diagnose problems. Logging Best Practices Logs are essential for debugging and monitoring Lambda functions. However, unstructured or excessive logging can make it harder to find helpful information. 1. Mask or Exclude Sensitive Data Good Practice: Avoid logging sensitive information like:User credentialsAPI keys, tokens, or secretsPersonally Identifiable Information (PII)Use tools like AWS Secrets Manager for sensitive data management.Example: Mask sensitive fields before logging: const sanitizedInput = {     ...event,     password: "***", }; console.log(JSON.stringify({     level: "info",     message: "User login attempt logged.",     input: sanitizedInput, })); Bad Practice: Logging sensitive data directly can cause security breaches or compliance violations (e.g., GDPR, HIPAA).Example: console.log(`User logged in with password: ${event.password}`); Why It Matters: Logging sensitive data can expose systems to attackers, breach compliance rules, and compromise user trust. 2.  Set Log Retention Policies Good Practice: Set a retention policy for CloudWatch log groups to prevent excessive log storage costs.AWS allows you to configure retention settings (e.g., 7, 14, or 30 days). Bad Practice: Using the default “Never Expire” retention policy unnecessarily stores logs indefinitely. Why It Matters: Unmanaged logs increase costs and make it harder to find relevant data. Retaining logs only as long as needed reduces costs and keeps logs manageable. 3. Avoid Excessive Logging Good Practice: Log only what is necessary to monitor, troubleshoot, and analyze system behavior.Use info, debug, and error levels to prioritize logs appropriately. console.info("Function started processing..."); console.error("Failed to fetch data from DynamoDB: ", error.message); Bad Practice: Logging every detail (e.g., input payloads, execution steps) unnecessarily increases log volume.Example: console.log(`Received event: ${JSON.stringify(event)}`); // Avoid logging full payloads unnecessarily Why It Matters: Excessive logging clutters log storage, increases costs, and makes it harder to isolate relevant logs. 4. Use Log Levels (Info, Debug, Error) Good Practice: Use different log levels to differentiate between critical and non-critical information.info: For general execution logs (e.g., function start, successful completion).debug: For detailed logs during development or troubleshooting.error: For failure scenarios requiring immediate attention. Bad Practice: Using a single log level (e.g., console.log() everywhere) without prioritization. Why It Matters: Log levels make it easier to filter logs based on severity and focus on critical issues in production. Conclusion In this episode of "Mastering AWS Lambda with Bao", we explored critical best practices for building reliable AWS Lambda functions, focusing on optimizing performance, error handling, and logging. Optimizing Performance: By reducing cold starts, using smaller deployment packages, lightweight runtimes, and optimizing VPC configurations, you can significantly lower latency and optimize Lambda functions. Strategies like moving initialization outside the handler and leveraging Provisioned Concurrency ensure smoother execution for latency-sensitive applications.Error Handling: Implementing structured error responses and custom error classes makes troubleshooting easier and helps differentiate between transient and persistent issues. Handling errors consistently improves system resilience.Retry Logic: Applying exponential backoff with jitter, using built-in retry mechanisms, and setting sensible retry limits optimizes that Lambda functions gracefully handle failures without overwhelming dependent services.Logging: Effective logging with structured formats, contextual information, log levels, and appropriate retention policies enables better visibility, debugging, and cost control. Avoiding sensitive data in logs ensures security and compliance. Following these best practices, you can optimize lambda function performance, reduce operational costs, and build scalable, reliable, and secure serverless applications with AWS Lambda. In the next episode, we’ll dive deeper into "Handling Failures with Dead Letter Queues (DLQs)", exploring how DLQs act as a safety net for capturing failed events and ensuring no data loss occurs in your workflows. Stay tuned! Note: 1. Provisioned Concurrency is not a universal solution. While it eliminates cold starts, it also incurs additional costs since pre-initialized environments are billed regardless of usage. When to Use:Latency-sensitive workloads like APIs or real-time applications where even a slight delay is unacceptable.When Not to Use:Functions with unpredictable or low invocation rates (e.g., batch jobs, infrequent triggers). For such scenarios, on-demand concurrency may be more cost-effective.

                13/01/2025

                237

                Bao Dang D. Q.

                Knowledge

                +0

                  Best Practices for Building Reliable AWS Lambda Functions

                  13/01/2025

                  237

                  Bao Dang D. Q.

                  Customize software background

                  Want to customize a software for your business?

                  Meet with us! Schedule a meeting with us!