General

Introducing the express-typeorm-postgres Starter Kit

Published Jan 13, 2023

Updated Feb 13, 2023

5 min read

This article was written over 18 months ago and may contain information that is out of date. Some content may be relevant but please refer to the relevant official documentation or available resources for the latest information.

Here at This Dot, we've been working with ExpressJS APIs for a while, and we've created a starter.dev kit for ExpressJS that you can use to scaffold your next backend project. The starter kit uses many well-known npm packages, such as TypeORM or BullMQ and integrates with databases such as PostgreSQL and Redis.

Kit contents

The express-typeorm-postgres starter kit provides you with infrastructure for development, and integrations with these infrastructures. It comes with a working Redis instance for caching and a second Redis instance for queues. It also starts up a Postgres instance for you, which you can seed with TypeORM. The infrastructure runs on docker using docker-compose.

The generated project comes with prettier and eslint set-up, so you only need to spend time on configuration if you want to tweak or change the existing rules.

Unit testing is set up using Jest, and there are some example tests provided with the example controllers.

How to initialise

API development usually requires more infrastructure than front-end development. Before you start, please make sure you have docker and docker-compose installed on your machine.

To initialize a project with the express-typeorm-postgres kit, run the following:

Run npx @this-dot/create-starter to run the scaffolding tool
Select the Express.js, TypeORM, and PostgreSQL kit from the CLI library options
Name your project
cd into your project directory, and install dependencies using the tool of your choice (npm, yarn or pnpm)
copy the contents of the .env.example file into a .env file

With this setup, you have a working starter kit that you can modify to your needs.

TypeORM and Database

When we started developing the kit, we decided to use PostgreSQL as the database, because it is a powerful, open-source object-relational database system that is widely used for storing and manipulating data. It has a strong reputation for reliability, performance, and feature richness, making it a great choice for a wide range of applications. It can also handle high levels of concurrency and large amounts of data, and supports complex queries and data types. Postgres is also highly extensible because it allows developers to add custom functions and data types to the database. It has a large and active community of developers and users who contribute to its ongoing development and support.

The kit uses TypeORM to connect to the database instance. We chose TypeORM because it makes it easy to manage database connections and perform common database operations, such as querying, inserting, updating and deleting data. It supports TypeScript and a wide range of databases, such as PostgreSQL, MySQL, SQLite and MongoDB, therefore if you want to be able to switch between databases, it makes it easier.

TypeORM also includes features such as database migrations, which help manage changes to database schema over time, and an entity model that allows you to define your database schema using classes and decorators. Overall, TypeORM is a useful tool for improving the efficiency and reliability of database-related code, and it can be a valuable addition to any TypeScript or JavaScript project that needs to interact with a database.

To seed an initial set of data into your database, run the following commands:

npm run infrastructure:start - this starts up the database instance
npm run db:seed - this leverages TypeORM to seed the database.

The seed command runs the src/db/run-seeders.ts file, where you can introduce your seeders for your own needs. The kit uses TypeORM-extension for seeding. Please refer to the src/db/seeding/technology-seeder.ts file for an example.

Caching

Storing response data in caches allows subsequent requests for the same data to be served more quickly. This can improve the performance and user experience of an API by reducing the amount of time it takes to retrieve data from the server. It can reduce the load on the database or mitigate rate limiting on third-party APIs called from your back-end. It also improves the reliability of an application by providing a fallback mechanism in case the database or the server is unavailable or slow to respond.

There is a Redis instance set up in the kit to be used for caching data. Under the hood, we use the cachified library to store cached data in Redis. The kit has a useCache method exported from src/cache/cache.ts, which requires a key and a callback function to be called to fetch the data.

const technologyId: number = parseInt(req.params.technologyId);
const technologyResult = await useCache<TechnologyResult>(req.originalUrl, () =>
  findTechnology(technologyId)
);

When you need to invalidate cache entries, you can use the clearCacheEntry method by supplying a key string to it. It will remove the cached data from Redis, and the next request that fetches from the database will cache the new values.

const technologyId: number = parseInt(req.params.technologyId);
const updateResult = await updateTechnologyEntry(technologyId, {
  displayName: req.body.name,
  description: req.body.description,
});

// ...

clearCacheEntry(req.baseUrl);
clearCacheEntry(req.originalUrl);

Under the src/modules/technology folder, you can see a complete example of a basic CRUD REST endpoint with caching enabled. Feel free to use those handlers as examples for your development needs.

Queue

A message queue allows different parts of an application, or different applications, to communicate with each other asynchronously by sending and receiving messages. This can be useful in a variety of situations, such as when one part of the application needs to perform a task that could take a long time, or when different parts of the application need to be decoupled from each other for flexibility and scalability.

We chose BullMQ because it is a fast, reliable, and feature-rich message queue system. It is built on top of the popular Redis in-memory data store, which makes it very performant and scalable. It has support for parallel processing, rate limiting, retries, and a variety of other features that make it well-suited for a wide range of use cases. BullMQ has a straightforward API and good documentation.

The kit has a second Redis instance set up to be used with BullMQ, and there is a queue set up out of the box, so resource-intensive tasks can be offloaded to a background process. The src/queue/ folder contains all the configuration and setup steps for the queue.

Both the queue and its worker is set up in the queue.ts file. The job-processor.ts file contains the function that will process the data. To run int in a separate thread, we must pass the path to this file into the worker:

const processorPath = path.join(__dirname, 'job-processor.js');
export const defaultWorker = new Worker(queueName, processorPath, {
	connection: {
		host: REDIS_QUEUE_HOST,
		port: REDIS_QUEUE_PORT,
	},
	autorun: true,
});

When to use this kit

This kit is most optimal when you:

want to build back-end services that can be consumed by other applications and services using ExpressJS
need a flexible and scalable way to build server-side applications
need to deal with CPU-intense operations on the server and you need a messaging queue
need to build an API with relational data
would like to just jump right into API development with ExpressJS using TypeORM and Postgres

Conclusion

The express-typeorm-postgres starter kit can help you kickstart your development by providing you with a working preset. It has testing configured, and it comes with a complete infrastructure orchestrated by docker-compose.

This Dot is a consultancy dedicated to guiding companies through their modernization and digital transformation journeys. Specializing in replatforming, modernizing, and launching new initiatives, we stand out by taking true ownership of your engineering projects.

We love helping teams with projects that have missed their deadlines or helping keep your strategic digital initiatives on course. Check out our case studies and our clients that trust us with their engineering.

About the author(s)

Balázs Tápai
He is a Software Engineer with a passion for automated testing. He loves Angular on the Front-End and NestJS on the Back-End. He also uses Cypress to reduce developer anxiety before demo meetings.
@TapaiBalazs @TapaiBalazs

End-to-end type-safety with JSON Schema

End-to-end type-safety with JSON Schema I recently wrote an introduction to JSON Schema post. If you’re unfamiliar with it, check out the post, but TLDR: It’s a schema specification that can be used to define the input and output data for your JSON API. In my post, I highlight many fantastic benefits you can reap from defining schemas for your JSON API. One of the more interesting things you can achieve with your schemas is end-to-end type safety from your backend API to your client application(s). In this post, we will explore how this can be accomplished slightly deeper. Overview The basic idea of what we want to achieve is: * a JSON API server that validates input and output data using JSON Schema * The JSON Schema definitions that our API uses transformed into TypeScript types With those pieces in place, we can achieve type safety on our API server and the consuming client application. The server side is pretty straightforward if you’re using a server like Fastify with already enabled JSON Schema support. This post will focus on the concepts more than the actual implementation details though. Here’s a simple diagram illustrating the high-level concept: We can share the schema and type declaration between the client and server. In that case, we can make a request to an endpoint where we know its type and schema, and assuming the server validates the data against the schema before sending it back to the client, our client can be confident about the type of the response data. Marrying JSON Schema and TypeScript There are a couple of different ways to accomplish this: * Generating types from schema definitions using code generation tools * Creating TypeBox definitions that can infer TypeScript types and be compiled to JSON Schema I recommend considering both and figuring out which would better fit your application and workflows. Like anything else, each has its own set of trade-offs. In my experience, I’ve found TypeBox to be the most compelling if you want to go deep with this pattern. Code generation A couple of different packages are available for generating TS types from JSON Schema definitions. * https://github.com/bcherny/json-schema-to-typescript * https://github.com/vega/ts-json-schema-generator They are CLI tools that you can provide a glob path to where your schema files are located and will generate TS declaration files to a specified output path. You can set up an npm hook or a similar type of script that will generate types for your development environment. TypeBox TypeBox is a JSON Schema type builder. With this approach, instead of json files, we define schemas in code using the TypeBox API. The TypeBox definitions infer to TypeScript types directly, which eliminates the code generation step described above. Here’s a simple example from the documentation of a JSON Schema definition declared with TypeBox: ` This can then be inferred as a TypeScript type: ` Aside from schemas and types, TypeBox can do a lot more to help us on our type-safety journey. We will explore it a bit more in upcoming sections. Sharing schemas between client and server applications Sharing our JSON Schema between our server and client app is the main requirement for end-to-end type-safety. There are a couple of different ways to accomplish this, but the simplest would be to set up our codebase as a monorepo that contains both the server and client app. Some popular options for TypeScript monorepos are: PNPM, Turborepo, and NX. If a monorepo is not an option, you can publish your schema and types as a package that can be installed in both projects. However, this setup would require a lot more maintenance work. Ultimately, as long as you can import your schemas and types from the client and server app, you are in good shape. Server-to-client validation and type-safety For the sake of simplicity, let's focus on data flowing from the server to the client for now. Generally speaking, the concepts also apply in reverse, as long as your JSON API server validates your inputs and outputs. We’ll look at the most basic version of having strongly typed data on the client from a request to our server. Type-safe client requests In our server application, if we validate the /users endpoint with a shared schema - on the client side, when we make the request to the endpoint, we know that the response data is validated using the user schema. As long as we are confident of this fact, we can use the generated type from that schema as the return type on our client fetch call. Here’s some pseudocode: ` Our server endpoint would look something like this: ` You could get creative and build out a map that defines all of your endpoints, their metadata, and schemas, and use the map to define your server endpoints and create an API client. Transforming data over the wire Everything looks stellar, but we can still take our efforts a bit further. To this point, we are still limited to serialized JSON data. If we have a created_at field (number or ISO string) tied to our user, and we want it to be a Date object when we get a hold of it on the client side - additional work and consideration are required. There are some different strategies out there for deserializing JSON data. The great thing about having shared schemas between our client and server is that we can encode our type information in the schema without sending additional metadata from our server to the client. Using format to declare type data In my initial JSON Schema blog post, I touched on the format field of the specification. In our schema, if the actual type of our date is a string in ISO8601 format, we can declare our format to be "date-time". We can use this information on the client to transform the field into a proper Date object. ` Transforming serialized JSON Data This can be a little bit tricky; again, there are many ways to accomplish it. To demonstrate the concept, we’ll use TypeBox to define our schemas as discussed above. TypeBox provides a Transform type that you can use to declare, encode, and decode methods for your schema definition. ` It even provides helpers to statically generate the decoded and encoded types for your schema ` If you declare your decode and encode functions for your schemas, you can then use the TypeBox API to handle decoding the serialized values returned from your JSON API. Here’s what the concept looks like in practice fetching a user from our API: ` Nice. You could use a validation library like Zod to achieve a similar result but here we aren’t actually doing any validation on our client side. That happened on the server. We just know the types based on the schema since both ends share them. On the client, we are just transforming our serialized JSON into what we want it to be in our client application. Summary There are a lot of pieces in play to accomplish end-to-end type safety. With the help of JSON Schema and TypeBox though, it feels like light work for a semi-roll-your-own type of solution. Another great thing about it is that it’s flexible and based on pretty core concepts like a JSON API paired with a TypeScript-based client application. The number of benefits that you can reap from defining JSON Schemas for your APIs is really great. If you’re like me and wanna keep it simple by avoiding GraphQL or other similar tools, this is a great approach....

Apr 17, 2024

6 mins

JSONTypeScript

TypeScript Integration with .env Variables

Introduction In TypeScript projects, effectively managing environment variables can significantly enhance the development experience. However, a common hurdle is that TypeScript, by default, doesn't recognize variables defined in .env files. This oversight can lead to type safety issues and, potentially, hard-to-trace bugs. In this blog post, we'll walk you through the process of setting up an environment.d.ts file. This simple yet powerful addition enables TypeScript to seamlessly integrate with and accurately interpret your environment variables. Let's dive into the details! Creating and Configuring environment.d.ts Install @types/node Before creating your environment.d.ts file, make sure you have the @types/node package installed as it provides TypeScript definitions for Node.js, including the process.env object. Install it as a development dependency: ` Setting Up environment.d.ts To ensure TypeScript correctly recognizes and types your .env variables, start by setting up an environment.d.ts file in your project. This TypeScript declaration file will explicitly define the types of your environment variables. 1. Create the File: In the root of your TypeScript project, create a file named environment.d.ts 2. Declare Environment Variables: In environment.d.ts, declare your environment variables as part of the NodeJS.ProcessEnv interface. For example, for API_KEY and DATABASE_URL, the file would look like this: ` 3. Typescript config: In you tsconfig.json file, ensure that Typescript will recognize our the new file: ` 4. Usage in Your Project: With these declarations, TypeScript will provide type-checking and intellisense for process.env.API_KEY and process.env.DATABASE_URL, enhancing the development experience and code safety. Checking on Your IDE By following the steps above, you can now verify on your IDE how your environment variables recognizes and auto completes the variables added: Conclusion Integrating .env environment variables into TypeScript projects enhances not only the security and flexibility of your application but also the overall developer experience. By setting up an environment.d.ts file and ensuring the presence of @types/node, you bridge the gap between TypeScript’s static type system and the dynamic nature of environment variables. This approach leads to clearer, more maintainable code, where the risks of runtime errors are significantly reduced. It's a testament to TypeScript's versatility and its capability to adapt to various development needs. As you continue to build and scale your TypeScript applications, remember that small enhancements like these can have a profound impact on your project's robustness and the efficiency of your development processes. Embrace these nuanced techniques, and watch as they bring a new level of precision and reliability to your TypeScript projects....

Mar 13, 2024

2 mins

TypeScript

How to host a full-stack app with AWS CloudFront and Elastic Beanstalk

How to host a full-stack JavaScript app with AWS CloudFront and Elastic Beanstalk Let's imagine that you have finished building your app. You have a Single Page Application (SPA) with a NestJS back-end. You are ready to launch, but what if your app is a hit, and you need to be prepared to serve thousands of users? You might need to scale your API horizontally, which means that to serve traffic, you need to have more instances running behind a load balancer. Serving your front-end using a CDN will also be helpful. In this article, I am going to give you steps on how to set up a scalable distribution in AWS, using S3, CloudFront and Elastic Beanstalk. The NestJS API and the simple front-end are both inside an NX monorepo The sample application For the sake of this tutorial, we have put together a very simple HTML page that tries to reach an API endpoint and a very basic API written in NestJS. The UI The UI code is very simple. There is a "HELLO" button on the UI which when clicked, tries to reach out to the /api/hello endpoint. If there is a response with status code 2xx, it puts an h1 tag with the response contents into the div with the id result. If it errors out, it puts an error message into the same div. ` The API We bootstrap the NestJS app to have the api prefix before every endpoint call. ` We bootstrap it with the AppModule which only has the AppController in it. ` And the AppController sets up two very basic endpoints. We set up a health check on the /api route and our hello endpoint on the /api/hello route. ` Hosting the front-end with S3 and CloudFront To serve the front-end through a CMS, we should first create an S3 bucket. Go to S3 in your AWS account and create a new bucket. Name your new bucket to something meaningful. For example, if this is going to be your production deployment I recommend having -prod in the name so you will be able to see at a glance, that this bucket contains your production front-end and nothing should get deleted accidentally. We go with the defaults for this bucket setting it to the us-east-1 region. Let's set up the bucket to block all public access, because we are going to allow get requests through CloudFront to these files. We don't need bucket versioning enabled, because these files will be deleted every time a new front-end version will be uploaded to this bucket. If we were to enable bucket versioning, old front-end files would be marked as deleted and kept, increasing the storage costs in the long run. Let's use server-side encryption with Amazon S3-managed keys and create the bucket. When the bucket is created, upload the front-end files to the bucket and let's go to the CloudFront service and create a distribution. As the origin domain, choose your S3 bucket. Feel free to change the name for the origin. For Origin access, choose the Origin access control settings (recommended). Create a new Control setting with the defaults. I recommend adding a description to describe this control setting. At the Web Application Firewall (WAF) settings we would recommend enabling security protections, although it has cost implications. For this tutorial, we chose not to enable WAF for this CloudFront distribution. In the Settings section, please choose the Price class that best fits you. If you have a domain and an SSL certificate you can set those up for this distribution, but you can do that later as well. As the Default root object, please provide index.html and create the distribution. When you have created the distribution, you should see a warning at the top of the page. Copy the policy and go to your S3 bucket's Permissions tab. Edit the Bucket policy and paste the policy you just copied, then save it. If you have set up a domain with your CloudFront distribution, you can open that domain and you should be able to see our front-end deployed. If you didn't set up a domain the Details section of your CloudFront distribution contains your distribution domain name. If you click on the "Hello" button on your deployed front-end, it should not be able to reach the /api/hello endpoint and should display an error message on the page. Hosting the API in Elastic Beanstalk Elastic beanstalk prerequisites For our NestJS API to run in Elastic Beanstalk, we need some additional setup. Inside the apps/api/src folder, let's create a Procfile with the contents: web: node main.js. Then open the apps/api/project.json and under the build configuration, extend the production build setup with the following (I only ) ` The above settings will make sure that when we build the API with a production configuration, it will generate a package.json and a package-lock.json near the output file main.js. To have a production-ready API, we set up a script in the package.json file of the repository. Running this will create a dist/apps/api and a dist/apps/frontend folder with the necessary files. ` After running the script, zip the production-ready api folder so we can upload it to Elastic Beanstalk later. ` Creating the Elastic Beanstalk Environment Let's open the Elastic Beanstalk service in the AWS console. And create an application. An application is a logical grouping of several environments. We usually put our development, staging and production environments under the same application name. The first time you are going to create an application you will need to create an environment as well. We are creating a Web server environment. Provide your application's name in the Application information section. You could also provide some unique tags for your convenience. In the Environment information section please provide information on your environment. Leave the Domain field blank for an autogenerated value. When setting up the platform, we are going to use the Managed Node.js platform with version 18 and with the latest platform version. Let's upload our application code, and name the version to indicate that it was built locally. This version label will be displayed on the running environment and when we set up automatic deployments we can validate if the build was successful. As a Preset, let's choose Single instance (free tier eligible) On the next screen configure your service access. For this tutorial, we only create a new service-role. You must select the aws-elasticbeanstalk-ec2-role for the EC2 instance profile. If can't select this role, you should create it in AWS IAM with the AWSElasticBeanstalkWebTier, AWSElasticBeanstalkMulticontainerDocker and the AWSElasticBeanstalkRoleWorkerTier managed permissions. The next step is to set up the VPC. For this tutorial, I chose the default VPC that is already present with my AWS account, but you can create your own VPC and customise it. In the Instance settings section, we want our API to have a public IP address, so it can be reached from the internet, and we can route to it from CloudFront. Select all the instance subnets and availability zones you want to have for your APIs. For now, we are not going to set up a database. We can set it up later in AWS RDS but in this tutorial, we would like to focus on setting up the distribution. Let's move forward Let's configure the instance traffic and scaling. This is where we are going to set up the load balancer. In this tutorial, we are keeping to the defaults, therefore, we add the EC2 instances to the default security group. In the Capacity section we set the Environment type to Load balanced. This will bring up a load balancer for this environment. Let's set it up so that if the traffic is large, AWS can spin up two other instances for us. Please select your preferred tier in the instance types section, We only set this to t3.micro For this tutorial, but you might need to use larger tiers. Configure the Scaling triggers to your needs, we are going to leave them as defaults. Set the load balancer's visibility to the public and use the same subnets that you have used before. At the Load Balancer Type section, choose Application load balancer and select Dedicated for exactly this environment. Let's set up the listeners, to support HTTPS. Add a new listener for the 443 port and connect your SSL certificate that you have set up in CloudFront as well. For the SSL policy choose something that is over TLS 1.2 and connect this port to the default process. Now let's update the default process and set up the health check endpoint. We set up our API to have the health check endpoint at the /api route. Let's modify the default process accordingly and set its port to 8080. For this tutorial, we decided not to enable log file access, but if you need it, please set it up with a separate S3 bucket. At the last step of configuring your Elastic Beanstalk environment, please set up Monitoring, CloudWatch logs and Managed platform updates to your needs. For the sake of this tutorial, we have turned most of these options off. Set up e-mail notifications to your dedicated alert e-mail and select how you would like to do your application deployments. At the end, let's configure the Environment properties. We have set the default process to occupy port 8080, therefore, we need to set up the PORT environment variable to 8080. Review your configuration and then create your environment. It might take a few minutes to set everything up. After the environment's health transitions to OK you can go to AWS EC2 / Load balancers in your web console. If you select the freshly created load balancer, you can copy the DNS name and test if it works by appending /api/hello at the end of it. Connect CloudFront to the API endpoint Let's go back to our CloudFront distribution and select the Origins tab, then create a new origin. Copy your load balancer's URL into the Origin domain field and select HTTPS only protocol if you have set up your SSL certificate previously. If you don't have an SSL certificate set up, you might use HTTP only, but please know that it is not secure and it is especially not recommended in production. We also renamed this origin to API. Leave everything else as default and create a new origin. Under the Behaviors tab, create a new behavior. Set up the path pattern as /api/* and select your newly created API origin. At the Viewer protocol policy select Redirect HTTP to HTTPS and allow all HTTP methods (GET, HEAD, OPTIONS, PUT, POST, PATCH, DELETE). For this tutorial, we have left everything else as default, but please select the Cache Policy and Origin request policy that suits you the best. Now if you visit your deployment, when you click on the HELLO button, it should no longer attach an error message to the DOM. --- Now we have a distribution that serves the front-end static files through CloudFront, leveraging caching and CDN, and we have our API behind a load balancer that can scale. But how do we deploy our front-end and back-end automatically when a release is merged to our main branch? For that we are going to leverage AWS CodeBuild and CodePipeline, but in the next blog post. Stay tuned....

Sep 11, 2023

12 mins

NestJSAWSTypeScriptNodeJS

Docusign Momentum 2025 From A Developer’s Perspective

*What if your contract details stuck in PDFs could ultimately become the secret sauce of your business automation workflows?* In a world drowning in PDFs and paperwork, I never thought I’d get goosebumps about agreements – until I attended Docusign Momentum 2025. I went in expecting talks about e-signatures; I left realizing the big push and emphasis with many enterprise-level organizations will be around Intelligent Agreement Management (IAM). It is positioned to transform how we build business software, so let’s talk about it. As Director of Technology at This Dot Labs, I had a front-row seat to all the exciting announcements at Docusign Momentum. Our team also had a booth there showing off the 6 Docusign extension apps This Dot Labs has released this year. We met 1-on-1 with a lot of companies and leaders to discuss the exciting promise of IAM. What can your company accomplish with IAM? Is it really worth it for you to start adopting IAM?? Let’s dive in and find out. After his keynote, I met up with Robert Chatwani, President of Docusign and he said this > “At Docusign, we truly believe that the power of a great platform is that you won’t be able to exactly predict what can be built on top of it,and builders and developers are at the heart of driving this type of innovation. Now with AI, we have entered what I believe is a renaissance era for new ideas and business models, all powered by developers.” Docusign’s annual conference in NYC was an eye-opener: agreements are no longer just documents to sign and shelve, but dynamic data hubs driving key processes. Here’s my take on what I learned, why it matters, and why developers should pay attention. From E-Signatures to Intelligent Agreements – A New Era Walking into Momentum 2025, you could feel the excitement. Docusign’s CEO and product team set the tone in the keynote: “Agreements make the world go round, but for too long they’ve been stuck in inboxes and PDFs, creating drag on your business.” Their message was clear – Docusign is moving from a product to a platform. In other words, the company that pioneered e-signatures now aims to turn static contracts into live, integrated assets that propel your business forward. I saw this vision click when I chatted with an attendee from a major financial services firm. His team manages millions of forms a year – loan applications, account forms, you name it. He admitted they were still “just scanning and storing PDFs” and struggled to imagine how IAM could help. We discussed how much value was trapped in those documents (what Docusign calls the “Agreement Trap” of disconnected processes). By the end of our coffee, the lightbulb was on: with the right platform, those forms could be automatically routed, data-extracted, and trigger workflows in other systems – no more black hole of PDFs. His problem wasn’t unique; many organizations have critical data buried in agreements, and they’re waking up to the idea that it doesn’t have to be this way. What Exactly is Intelligent Agreement Management (IAM)? So what is Docusign’s Intelligent Agreement Management? In essence, IAM is an AI-powered platform that connects every part of the agreement lifecycle. It’s not a single product, but a collection of services and tools working in concert. Docusign IAM helps transform agreement data into insights and actions, accelerate contract cycles, and boost productivity across departments. The goal is to address the inefficiencies in how agreements are created, signed, and managed – those inefficiencies that cost businesses time and money. At Momentum, Docusign showcased the core components of IAM: - Docusign Navigator link: A smart repository to centrally store, search, and analyze agreements. It uses AI to convert your signed documents (which are basically large chunks of text) into structured, queryable data. Instead of manually digging through contracts for a specific clause, you can search across all agreements in seconds. Navigator gives you a clear picture of your organization’s contractual relationships and obligations (think of it as Google for your contracts). Bonus: it comes with out-of-the-box dashboards for things like renewal dates, so you can spot risks and opportunities at a glance. - Docusign Maestro link: A no-code workflow engine to automate agreement workflows from start to finish. Maestro lets you design customizable workflows that orchestrate Docusign tasks and integrate with third-party apps – all without writing code. For example, you could have a workflow for new vendor onboarding: once a vendor contract is signed, Maestro could automatically notify your procurement team, create a task in your project tracker, and update a record in your ERP system. At the conference, they demoed how Maestro can streamline processes like employee onboarding and compliance checks through simple drag-and-drop steps or archiving PDFs of signed agreements into Google Drive or Dropbox. - Docusign Iris (AI Engine) link: The brains of the operation. Iris is the new AI engine powering all of IAM’s “smarts” – from reading documents to extracting data and making recommendations. It’s behind features like automatic field extraction, AI-assisted contract review, intelligent search, and even document summarization. In the keynote, we saw examples of Iris in action: identify key terms (e.g. payment terms or renewal clauses) across a stack of contracts, or instantly generate a summary of a lengthy agreement. These capabilities aren’t just gimmicks; as one Docusign executive put it, they’re “signals of a new way of working with agreements”. Iris essentially gives your agreement workflow a brain – it can understand the content of agreements and help you act on it. - Docusign App Center link: A hub to connect the tools of your trade into Docusign. App Center is like an app store for integrations – it lets you plug in other software (project management, CRM, HR systems, etc.) directly into your Maestro workflows. This is huge for developers (and frankly, anyone tired of building one-off integrations). Instead of treating Docusign as an isolated e-signature tool, App Center makes it a platform you can extend. I’ll dive more into this in the next section, since it’s close to my heart – my team helped build some of these integrations! In short, IAM ties together the stages of an agreement (create → sign → store → manage) and supercharges each with automation and AI. It’s modular, too – you can adopt the pieces you need. Docusign essentially unbundled the agreement process into building blocks that developers and admins can mix-and-match. The future of agreements, as Docusign envisions it, is a world where organizations *“seamlessly add, subtract, and rearrange modular solutions to meet ever-changing needs”* on a single trusted platform. The App Center and Real-World Integrations (Yes, We Built Those!) One of the most exciting parts of Momentum 2025 for me was seeing the Docusign App Center come alive. As someone who works on integrations, I was practically grinning during the App Center demos. Docusign highlighted several partner-built apps that snap into IAM, and I’m proud to say This Dot Labs built six of them – including integrations for Monday.com, Slack, Jira, Asana, Airtable, and Mailchimp. Why are these integrations a big deal? Because developers often spend countless hours wiring up systems that need to talk to each other. With App Center, a lot of that heavy lifting is already done. You can install an app with a few clicks and configure data flows in minutes instead of coding for months. In fact, a study found it takes the average org 12 months to develop a custom workflow via APIs, whereas with Docusign’s platform you can do it via configuration almost immediately. That’s a game-changer for time-to-value. At our This Dot Labs booth, I spoke with many developers who were intrigued by these possibilities. For example, we showed how our Docusign Slack Extension lets teams send Slack messages and notifications when agreements are sent and signed.. If a sales contract gets signed, the Slack app can automatically post a notification in your channel and even attach the signed PDF – no more emailing attachments around. People loved seeing how easily Docusign and Slack now talk to each other using this extension. Another popular one was our Monday.com app. With it, as soon as an agreement is signed, you can trigger actions in Monday – like assigning onboarding tasks for a new client or employee. Essentially, signing the document kicks off the next steps automatically. These integrations showcase why IAM is not just about Docusign’s own features, but about an ecosystem. App Center already includes connectors for popular platforms like Salesforce, HubSpot, Workday, ServiceNow, and more. The apps we built for Monday, Slack, Jira, etc., extend that ecosystem. Each app means one less custom integration a developer has to build from scratch. And if an app you need doesn’t exist yet – well, that’s an opportunity. (Shameless plug: we’re happy to help build it!) The key takeaway here is that Docusign is positioning itself as a foundational layer in the enterprise software stack. Your agreement workflow can now natively include things like project management updates, CRM entries, notifications, and data syncs. As a developer, I find that pretty powerful. It’s a shift from thinking of Docusign as a single SaaS tool to thinking of it as a platform that glues processes together. Not Just Another Contract Tool – Why IAM Matters for Business After absorbing all the Momentum keynotes and sessions, one thing is clear: IAM is not “just another contract management tool.” It’s aiming to be the platform that automates critical business processes which happen to revolve around agreements. The use cases discussed were not theoretical – they were tangible scenarios every developer or IT lead will recognize: - Procurement Automation: We heard how companies are using IAM to streamline procurement. Imagine a purchase order process where a procurement request triggers an agreement that goes out for e-signature, and once signed, all relevant systems update instantly. One speaker described connecting Docusign with their ERP so that vendor contracts and purchase orders are generated and tracked automatically. This reduces the back-and-forth with legal and ensures nothing falls through the cracks. It’s easy to see the developer opportunity: instead of coding a complex procurement approval system from scratch, you can leverage Docusign’s workflow + integration hooks to handle it. Docusign IAM is designed to connect to systems like CRM, HR, and ERP so that agreements flow into the same stream of data. For developers, that means using pre-built connectors and APIs rather than reinventing them. - Faster Employee Onboarding: Onboarding a new hire or client typically involves a flurry of forms and tasks – offer letters or contracts to sign, NDAs, setup of accounts, etc. We saw how IAM can accelerate onboarding by combining e-signature with automated task generation. For instance, the moment a new hire signs their offer letter, Maestro could trigger an onboarding workflow: provisioning the employee in systems, scheduling orientation, and creating tasks in tools like Asana or Monday. All those steps get kicked off by the signed agreement. Docusign Maestro’s integration capabilities shine here – it can tie into HR systems or project management apps to carry the baton forward. The result is a smoother day-one experience for the new hire and less manual coordination for IT and HR. As developers, we can appreciate how this modular approach saves us from writing yet another “onboarding script”; we configure the workflow, and IAM handles the rest. - Reducing Contract Auto-Renewal Risk: If your company manages a lot of recurring contracts (think vendor services, subscriptions, leases), missing a renewal deadline can be costly. One real-world story shared at Momentum was about using IAM to prevent unwanted auto-renewals. With traditional tracking (spreadsheets or calendar reminders), it’s easy to forget a termination notice and end up locked into a contract for another year. Docusign’s solution: let the AI engine (Iris) handle it. It can scan your repository, surface any renewal or termination dates, and proactively remind stakeholders – or even kick off a non-renewal workflow if desired. As the Bringing Intelligence to Obligation Management session highlighted, “Missed renewal windows lead to unwanted auto-renewals or lost revenue… A forgotten termination deadline locks a company into an unneeded service for another costly term.” With IAM, those pitfalls are avoidable. The system can automatically flag and assign tasks well before a deadline hits. For developers, this means we can deliver risk-reduction features without building a custom date-tracking system – the platform’s AI and notification framework has us covered. These examples all connect to a bigger point: agreements are often the linchpin of larger business processes (buying something, hiring someone, renewing a service). By making agreements “intelligent,” Docusign IAM is essentially automating chunks of those processes. This translates to real outcomes – faster cycle times, fewer errors, and less risk. From a technical perspective, it means we developers have a powerful ally: we can offload a lot of workflow logic to the IAM platform. Why code it from scratch if a combination of Docusign + a few integration apps can do it? Why Developers Should Care about IAM (Big Time) If you’re a software developer or architect building solutions for business teams, you might be thinking: This sounds cool, but is it relevant to me? Let me put it this way – after Momentum 2025, I’m convinced that ignoring IAM would be a mistake for anyone in enterprise software. Here’s why: - Faster time-to-value for your clients or stakeholders: Business teams are always pressuring IT to deliver solutions faster. With IAM, you have ready-made components to accelerate projects. Need to implement a contract approval workflow? Use Maestro, not months of coding. Need to integrate Docusign with an internal system? Check App Center for an app or use their APIs with far less glue code. Docusign’s own research shows that connecting systems via App Center and Maestro can cut development time dramatically (from ~12 months of custom dev to mere weeks or less). For us developers, that means we can deliver results sooner, which definitely wins points with the business. - Fewer custom builds (and less maintenance): Let’s face it – maintaining custom scripts or one-off integrations is not fun. Every time a SaaS API changes or a new requirement comes in, you’re back in the code. IAM’s approach offers more reuse and configuration instead of raw code. The platform is doing the hard work of staying updated (for example, when Slack or Salesforce change something in their API, Docusign’s connector app will handle it). By leveraging these pre-built connectors and templates, you write less custom code, which means fewer bugs and lower maintenance overhead. You can focus your coding effort on the unique parts of your product, not the boilerplate integration logic. - Reusable and modular workflows: I love designing systems as Lego blocks – and IAM encourages that. You can build a workflow once and reuse it across multiple projects or clients with slight tweaks. For instance, an approval workflow for sales contracts might be 90% similar to one for procurement contracts – with IAM, you can reuse that blueprint. The fact that everything is on one platform also means these workflows can talk to each other or be combined. This modularity is a developer’s dream because it leads to cleaner architecture. Docusign explicitly touts this modular approach, noting that organizations can easily rearrange solutions on the fly to meet new needs. It’s like having a library of proven patterns to draw from. - AI enhancements with minimal effort: Adding AI into your apps can be daunting if you have to build or train models yourself. IAM essentially gives you AI-as-a-service for agreements. Need to extract key data from 1,000 contracts? Iris can do that out-of-the-box. Want to implement a risk scoring for contracts? The AI can flag unusual terms or deviations. As a developer, being able to call an API or trigger a function that returns “these are the 5 clauses to look at” is incredibly powerful – you’re injecting intelligence without needing a data science team. It means you can offer more value in your applications (and impress those end-users!) by simply tapping into IAM’s AI features. Ultimately, Docusign IAM empowers developers to build more with less code. It’s about higher-level building blocks. This doesn’t replace our jobs – it makes our jobs more focused on the interesting problems. I’d rather spend time designing a great user experience or tackling a complex business rule than coding yet another Docusign-to-Slack integration. IAM is taking care of the plumbing and adding a layer of smarts on top. Don’t Underestimate Agreement Intelligence – Your Call to Action Momentum 2025 left me with a clear call to action: embrace agreement intelligence. If you’re a developer or tech leader, it’s time to explore what Docusign IAM can do for your projects. This isn’t just hype from a conference – it’s a real shift in how we can deliver solutions. Here are a few ways to get started: - Browse the IAM App Center – Take a look at the growing list of apps in the Docusign App Center. You might find that integration you’ve been meaning to build is already available (or one very close to it). Installing an app is trivial, and you can configure it to fit your workflow. This is the low-hanging fruit to immediately add value to your existing Docusign processes. If you have Docusign eSignature or CLM in your stack, App Center is where you extend it. - Think about integrations that could unlock value – Consider the systems in your organization that aren’t talking to each other. Is there a manual step where someone re-enters data from a contract into another system? Maybe an approval that’s done via email and could be automated? Those are prime candidates for an IAM solution. For example, if Legal and Sales use different tools, an integration through IAM can bridge them, ensuring no agreement data falls through the cracks. Map out your agreement process end-to-end and identify gaps – chances are, IAM has a feature to fill them. - Experiment with Maestro and the API – If you’re technical, spin up a trial of Docusign IAM. Try creating a Maestro workflow for a simple use case, or use the Docusign API/SDKs to trigger some AI analysis on a document. Seeing it in action will spark ideas. I was amazed how quickly I could set up a workflow with conditions and parallel steps – things that would take significant coding time if I did them manually. The barrier to entry for adding complex logic has gotten a lot lower. - Stay informed and involved – Docusign’s developer community and IAM documentation are growing. Momentum may be over, but the “agreement intelligence” movement is just getting started. Keep an eye on upcoming features (they hinted at even more AI-assisted tools coming soon). Engage with the community forums or join Docusign’s IAM webinars. And if you’re building something cool with IAM, consider sharing your story – the community benefits from hearing real use cases. My final thought: don’t underestimate the impact that agreement intelligence can have in modern workflows. We spend so much effort optimizing various parts of our business, yet often overlook the humble agreement – the contracts, forms, and documents that initiate or seal every deal. Docusign IAM is shining a spotlight on these and saying, “Here is untapped gold. Let’s mine it.” As developers, we have an opportunity (and now the tools) to lead that charge. I’m incredibly excited about this new chapter. After seeing what Docusign has built, I’m convinced that intelligent agreements can be a foundational layer for digital transformation. It’s not just about getting documents signed faster; it’s about connecting dots and automating workflows in ways we couldn’t before. As I reflect on Momentum 2025, I’m inspired and already coding with new ideas in mind. I encourage you to do the same – check out IAM, play with the App Center, and imagine what you could build when your agreements start working intelligently for you. The future of agreements is here, and it’s time for us developers to take full advantage of it. Ready to explore? Head to the Docusign App Center and IAM documentation and see how you can turn your agreements into engines of growth. Trust me – the next time you attend Momentum, you might just have your own success story to share. Happy building!...

Apr 29, 2025

14 mins

Software Engineering

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Introducing the express-typeorm-postgres Starter Kit

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Caching

Queue

When to use this kit

Conclusion

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