For the last decade, modern web APIs have grown from solutions like Flickr, to robust platforms that generate new business models. Throughout this period of growth, most APIs have been limited to request-response over HTTP. We are now seeing a move back to eventing with the popularity of webhooks to connect SaaS solutions, the introduction of technologies such as Kafka to drive internal messaging, and the need for integrating IoT devices.
API eventing completely changes the way API consumers interact with our APIs, creating new possibilities that request-response cannot. Let’s examine the driving factors contributing to the rise of API eventing in greater detail, along with the opportunities that may inspire you to consider adding API event support to your API.
How companies are adding realtime capabilities to their products and building realtime APIs
Mirroring the rise of API-driven applications, realtime is becoming an emerging, omnipresent force in modern application development. It is powering instant messaging, live sports feeds, geolocation, big data, and social feeds. But, what is realtime and what does it really mean? What types of software and technology are powering this industry? Let’s dive into it.
What Is Realtime?
For the more technical audience, realtime traditionally describes realtime computing, whereby “hardware and software systems are subject to a realtime constraint, for example from event to system response” (Source). For this article, we’re framing realtime from the perspective of an end-user: the perception that an event or action happens sufficiently quickly to be perceived as nearly instantaneous.
Moreover, realtime could be defined in a more relative temporal sense. It could mean that a change in A synchronizes with a change in B. Or, it could mean that a change in A immediately triggers a change in B. Or… it could mean that A tells B that something changed, yet B does nothing. Or… does it mean that A tells everyone something changed, but doesn’t care who listens?
Let’s dig a bit deeper. Realtime does not necessarily mean that something is updated instantly (in fact, there’s no singular definition of “instantly”). So, let’s not focus on the effect, but rather the mechanism. Realtime is about pushing data as fast as possible — it is automated, synchronous, and bi-directional communication between endpoints at a speed within a few hundred milliseconds.
- Synchronous means that both endpoints have access to data at the same time.
- Bi-directional means that data can be sent in either direction.
- Endpoints are senders or receivers of data (phone, tablet, server).
- A few hundred milliseconds is a somewhat arbitrary metric since data cannot be delivered instantly, but it most closely aligns to what humans perceive as realtime (Robert Miller proved this in 1986).
With this definition and its caveats in mind, let’s explore the concept of pushing data.
We’ll start by contrasting data push with “request-response.” Request-response is the most fundamental way that computer systems communicate. Computer A sends a request for something from Computer B, and Computer B responds with an answer. In other words, you can open up a browser and type “reddit.com.” The browser sends a request to Reddit’s servers and they respond with the web page.
In a data push model, data is pushed to a user’s device rather than pulled (requested) by the user. For example, modern push email allows users to receive email messages without having to check manually. Similarly, we can examine data push in a more continuous sense, whereby data is continuously broadcasted. Anyone who has access to a particular channel or frequency can receive that data and decide what to do with it.
Moreover, there are a few ways that data push/streaming is currently achieved:
HTTP streaming provides a long-lived connection for instant and continuous data push. You get the familiarity of HTTP with the performance of WebSockets. The client sends a request to the server and the server holds the response open for an indefinite length. This connection will stay open until a client closes it or a server side-side event occurs. If there is no new data to push, the application will send a series of keep-alive ticks so the connection doesn’t close.
WebSockets provide a long-lived connection for exchanging messages between client and server. Messages may flow in either direction for full-duplex communication. This bi-directional connection is established through a WebSocket handshake. Just like in HTTP Streaming and HTTP Long-Polling, the client sends a regular HTTP request to the server first. If the server agrees to the connection, the HTTP connection is replaced with a WebSocket connection.
Webhooks are a simple way of sending data between servers. No long-lived connections are needed. The sender makes an HTTP request to the receiver when there is data to push. A WebHook registers or “hooks” to a callback URL and will notify you anytime an event has occurred. You register this URL in advance and when an event happens, the server sends a HTTP POST request with an Event Object to the callback URL. This event object contains the new data that will be pushed to the callback URL. You might use a WebHook if you want to receive notifications about certain topics. It could also be used to notify you whenever a user changes or updates their profile.
HTTP long-polling provides a long-lived connection for instant data push. It is the easiest mechanism to consume and also the easiest to make reliable. This technique provides a long-lived connection for instant data push. The server holds the request open until new data or a timeout occurs. Most send a timeout after 30 to 120 seconds, it depends on how the API was setup. After the client receives a response (whether that be from new data or a timeout), the client will send another request and this is repeated continuously.
Is pushing data hard? Yes, it is, especially at scale (ex. pushing updates to millions of phones simultaneously). To meet this demand, an entire realtime industry has emerged, which we’ll define as Realtime Infrastructure as Service (Realtime IaaS).
Here is a compilation of resources that are available for developers to build realtime applications based on specific languages / frameworks:
Realtime Infrastructure as a Service
According to Gartner, “Infrastructure as a service (IaaS) is a standardized, highly automated offering, where compute resources, complemented by storage and networking capabilities are owned and hosted by a service provider and offered to customers on-demand. Customers are able to self-provision this infrastructure, using a Web-based graphical user interface that serves as an IT operations management console for the overall environment. API access to the infrastructure may also be offered as an option.”
We often here PaaS (Platform as a Service) and SaaS (Software as a Service), so how are they different than IaaS?
- Infrastructure as a Service (IaaS): hardware is provided by an external provider and managed for you.
- Platform as a Service (PaaS): both hardware and your operating system layer are managed for you.
- Software as a Service (SaaS): an application layer is provided for the platform and infrastructure (which is managed for you).
To power realtime, applications require a carefully architected system of servers, APIs, load balancers, etc. Instead of building these systems in-house, organizations are finding it more cost-effective and resource-efficient to purchase much of this systemic infrastructure and then drive it in-house. These systems, therefore, are not just IaaS, but typically provide both a platform and software layer to help with management. Foundationally speaking, their core benefit is that they provide realtime infrastructure, whether you host it internally or rely on managed instance
It all comes down to the simple truth that realtime is hard for a number of reasons:
- Customer Uptime Demand – Customers that depend on realtime updates will immediately notice when your network is not performant.
- Horizontal Scalability – You must be able to handle volatile and massive loads on your system or risk downtime. This is typically achieved through clever horizontal scalability and systems that are able to manage millions of simultaneous connections.
- Architectural Complexity – Maintaining a performant realtime system is not only complex, but it requires extensive experience and expertise. This is expensive to buy, especially in today’s high demand engineering market.
- Contingencies – Inevitably, your system will experience some downtime, whether due to an anticipated load spike or a newly released feature. It is important, therefore, to have multiple uptime contingencies in place to make sure that the system knows what to do, should your primary realtime mechanism fail to perform.
- Queuing – When you’re sending a lot of data, then you likely need an intermediate queuing mechanism to ensure that your backend processes are not overburdened with increased message loads.
Realtime Application IaaS
Realtime app infrastructure sends data to browsers and clients. It typically uses pub/sub messaging, webhooks, and/or websockets — and is separate from an application or service’s main API. These solutions are best for organizations that are looking for realtime messaging without the need to build their own realtime APIs.
These systems also have more well-built platform/software management tools on top of their infrastructure offerings. For instance, the leading providers have built-in configuration tools like access controls, event delegation, debugging tools, and channel configuration.
Benefits of Realtime App IaaS
- Speed – typically explicitly designed to deliver data with low latencies to end-user devices, including smartphones, tablets, browsers, and laptops.
- Multiple SDKs for easier integration.
- Uses globally distributed realtime data delivery platforms.
- Multiple protocol adapters.
- Well-tested in production environments.
- Keeps internal configuration to a minimum.
While some of the platforms out there function differently, here are some of the most typical use cases:
- Realtime Chat – In a microservice environment, a realtime API proxy makes it easy to listen for instant updates from other microservices without the need for a centralized message broker. Each microservice gets its own proxy instance, and microservices communicate with each other via your organization’s own API contracts rather than a vendor-specific mechanism.
- IoT Device Control – Securely monitor, control, provision and stream data between Internet-connected devices.
- Geotracking / Mapping Realtime Updates – Integrates with other realtime APIs like (Google Maps) to construct rich realtime updates.
- Multiplayer Game Synchronization – Synchronize communications amongst multiple simultaneous players to keep play fluid.
Realtime API IaaS for API Development
Realtime API infrastructure specifically allows developers to build realtime data push into their existing APIs. Typically, you would not need to modify your existing API contracts, as the streaming server would serve as a proxy. The proxy design allows these services to fit nicely within an API stack. This means it can inherit other facilities from your REST API, such as authentication, logging, throttling, etc and, consequently, it can be easily combined with an API management system. In the case of WebSocket messages being proxied out as HTTP requests, the messages may be handled statelessly by the backend. Messages from a single connection can even be load balanced across a set of backend instances.
All in all, realtime API IaaS is used for API development, specifically geared for organizations that need to build highly-performant realtime APIs like Slack, Instagram, Google, etc. All of these orgs build and manage their infrastructure internally, so the IaaS offering can be thought of as a way to extend these capabilities to organizations that lack the resources and technical expertise to build a realtime API from scratch.
Benefits of Realtime API IaaS
- Custom build an internal API.
- Works with existing API management systems.
- Does not lock you into a particular tech stack.
- Provides realtime capabilities throughout entire stack.
- Usually proxy-based, with pub/sub or polling.
- Add realtime to any API, no matter what backend language or database.
- Cloud or self-hosted API infrastructure.
- It can inherit facilities from your REST API, such as authentication, logging, throttling.
While some of the platforms out there function differently, here are some of the most typical use cases:
- API development – As we’ve discussed, you can build custom realtime APIs on top of your existing API infrastructure.
- Microservices – In a microservice environment, a realtime API proxy makes it easy to listen for instant updates from other microservices without the need for a centralized message broker. Each microservice gets its own proxy instance, and microservices communicate with each other via your organization’s own API contracts rather than a vendor-specific mechanism.
- Message queue – If you have a lot of data to push, you may want to introduce an intermediate message queue. This way, backend processes can publish data once to the message queue, and the queue can relay the data via an adapter to one or more proxy instances. The realtime proxy is able to forward subscription information to such adapters, so that messages can be sent only to the proxy instances that have subscribers for a given channel.
- API management – It’s possible to combine an API management system with a realtime proxy. Most API management systems work as proxy servers as well, which means all you need to do is chain the proxies together. Place the realtime proxy in the front, so that the API management system isn’t subjected to long-lived connections. Also, the realtime proxy can typically translate WebSocket protocol to HTTP, allowing the API management system to operate on the translated data.
- Large scale CDN performance – Since realtime proxy instances don’t talk to each other, and message delivery can be tiered, this means the realtime proxy instances can be geographically distributed to create a realtime push CDN. Clients can connect to the nearest regional edge server, and events can radiate out from a data source to the edges.
Realtime is becoming an emerging, omnipresent force in modern application development. It is not only a product differentiator, but is often sufficient for product success. It has accelerated the proliferation of widely-used apps like Google Maps, Lyft, and Slack. Whether you’re looking to build your own API from scratch or build on top of an IaaS platform, realtime capabilities are increasingly becoming a requirement of the modern tech ecosystem.
This online resource is a unique way to frame a conceptual model for evented APIs. Sam Curren and Phillip J. Windley discuss the fundamentals of evented APIs, how evented systems work, and a proposed protocol.
Events indicate something has happened. In this they differ from the request-response interaction style popular on the Web. Event-based systems are declarative whereas request-response systems are interrogatory. The difference between events (“this happened”) and requests (“will you do this?”) offers benefits in looser coupling of components as well as semantic encapsulation (see On Hierarchies and Networks for more detail).
APIs have become an economic imperative for many companies. But APIs based solely on request-response style interactions limit integrations to those where one system always knows what it wants from the other. The calling service must script the interaction and the APIs simply follow along.
We envision a world where applications integrate multiple products and services as equals based on event-driven interactions. Evented APIs, following the form described in this document, enable building such applications.
From the Fanout Blog
It’s becoming the new normal that messaging and collaboration apps and platforms are available across multiple devices.
Business tools like Slack and JIRA offer feature-rich mobile apps, and users increasingly consume content from social networks like Facebook on their mobile devices instead of a desktop or laptop.
This isn’t a surprise – and we’re here to share our perspective on how developers can use realtime data to provide cross-platform users with the best notification experience.
Mary Meeker’s 2017 Internet Trends Report tracks the trend towards increasing mobile adoption:
What’s not stated explicitly in this slide is that that much of this engagement occurs simultaneously – it’s not uncommon for users to have an app open on their desktop and phone at the same time.
‘Dumb’ notifications produce a poor user experience
Simultaneous use of cross-platform apps has created a user experience issue that many of us are familiar with. When a new Trello card is assigned to me, I get a push notification on my phone, a ping in the Trello interface, and an email in my inbox. Due to my Trello integration with Slack, things quickly get worse – I get a notification on Slack on each of my devices. I can get up to 6 notifications tied to a single event.
This isn’t ideal – and as more devices become connected, the problem will only be compounded. Imagine a future where your phone, smartwatch, smart TV, and smart thermostat are all buzzing simultaneously. It doesn’t need to be this way.
Collaboration and messaging app developers can get smart
We didn’t come up with the idea of ‘smart’ notifications (entire companies like Intercom and OpenBackare built to enable them) – but we do have a perspective on how app developers can use realtime data to enable them.
Realtime data is already present in many chat or collaboration apps – typing indicators, read receipts, and live editing are all features that we take for granted. The next step for developers is taking a wider variety of realtime data into account when building notifications into their user experiences.
Luckily, mobile devices offer a wealth of realtime data to developers who want to do this:
Presence and attention-awareness (knowing which device a user is active on) allows a single ping to that device, instead of a ping to all devices. Results-driven logic can drive a secondary notification to another device or channel in the instance the first notification is not responded to. This can lead to some pretty complex logic, as in the case of Slack’s notification tree below:
Slack’s blog post on how they built a lightweight desktop client to handle the complex interactions between team, channel, and user preferences and states when sending notifications is worth reading.
Time and location data is crucial – work notifications don’t need to be sent on the weekend, and pop-up notifications for events or sales are only relevant in bounded areas. Slack enables manual setting of ‘Do Not Disturb’ hours in order to keep notifications from taking over user’s lives. Context can be user-generated (like in the Slack example) or learned based on prior interactions with notifications.
Device and connection state information is underutilized. Know a user has low battery life? Maybe the notification to download the latest game update can wait. Users on Wifi are more likely to interact with rich notifications than those on cellular connections. If a user loses connectivity and many notifications are queued, they may no longer all be relevant when the user is back in range.
Realtime is a crucial component for smart notifications
As users constantly switch devices and platforms, realtime knowledge of their status is key to providing intelligent notifications. Developers who do this well will continue to retain user interest, and those who don’t will have a hard time keeping their attention.
Many software developers are familiar with realtime, but we believe that realtime concepts and user experiences are becoming increasingly important for less technical individuals to understand.
At Fanout, we power realtime APIs to instantly push data to endpoints – which can range from the actual endpoints of an API (the technical term) to external businesses or end users. We use the word in this post loosely to refer to any destination for data.
We’re here to share our experience with realtime: we’ll provide a definition and current examples, peer into the future of realtime, and try and shed some light on the eternal realtime vs. real-time vs. real time semantic debate.
The simple definition
Realtime refers to a synchronous, bi-directional communication channel between endpoints at a speed of less than 100ms.
We’ll break that down in plain[er] english:
- Synchronous means that both endpoints have access to data at the same time (not to be confused with sync/async programming).
- Bi-directional means that endpoints can send data in either direction.
- Endpoints are senders or receivers of data: they could be anything from an API endpoint that makes data available to a user chatting on their phone.
- 100ms is somewhat arbitrary: data cannot be delivered instantly – but under 100ms is pretty close, especially with respect to human perception. Robert Miller proved this in 1986.
An example of a realtime user experience
A simple example of a realtime user experience is that of a chat app. In a chat app, you ‘immediately’ (sub 100ms) see messages from the person (endpoint) you’re chatting with, and can receive information about when they read your messages (synchronous, bi-directional).
Realtime vs. request-response
Web experiences are beginning to move from request-response experiences to live, realtime ones. Social feeds don’t require a refresh (a request) to update, and you don’t need to email documents as attachments that need to be downloaded (request) and sent back with edits (response) – you just use collaboration software that works in realtime.
More realtime experiences
Realtime user experiences are everywhere you look – especially where near-instant access to information is valuable. You’ll find realtime in:
- Collaboration: realtime access to internal and external information from your team is becoming the norm. It’s accepted that a sales inquiry (data) can be instantaneously relayed from live chat on your website, into your customer service portal and then into Slack.
- Finance: stock tracking and bitcoin wallets require immediate access to information. Applications like high-frequency trading exist specifically because of the ability of certain parties to access and act on data faster than others.
- Events: second-screen experiences for sports, including live betting with realtime odds updates, are becoming increasingly common.
- Crowdsourcing: distributed collection, analysis, and dissemination of data from distributed endpoints (think reports from WeatherUnderground stations or from the traffic app Waze) is only valuable when it occurs in realtime.
Realtime in the future
As we see it (and admittedly, we are a little biased), realtime is quickly becoming the new normal. Up-to-date information is expected by businesses and end users. Realtime is the natural complement to trends like:
Big Data: as the number of digitally connected businesses, experiences, and devices rises, so does the amount of data generated. Data becomes more valuable as the three V’s of a dataset (velocity, volume, variety) increase – and realtime transmission is central to the velocity component.
In the past, companies benefitted from hoarding data, but increasingly data is becoming most valuable when shared (and monetized). The companies that can aggregate and share the most data, as quickly as possible, will be successful.
Proliferation of APIs: businesses sharing data are increasingly going to do so through APIs. Entire businesses are being built on APIs by platform providers like Twillio (they only have an API) or they are coming to comprise substantial portions of existing businesses (like Salesforce’s API).
An elegant end-user experience is increasingly the product of data that’s being moved through multiple APIs – and the number of APIs is only going to increase as they trend towards becoming less technical and more accessible and interoperable. The APIs that provide access to data or move it through their system as quickly as possible will rise over those that cannot.
Realtime vs. real-time vs. real time
The endless debate – what’s the correct way to write what we’ve been discussing? We use realtime, because we believe that “real time” refers to something experienced at normal speed and not condensed or sped up. For example, watching grass grow in ‘real time’ is not very exciting – but a time lapse is.
We also don’t like hyphenating – so we went with realtime instead of real-time (and it looks like most of the industry agrees with us).