Welcome!

@DevOpsSummit Authors: Liz McMillan, Pat Romanski, Dalibor Siroky, Jignesh Solanki, Dana Gardner

Related Topics: @DevOpsSummit, Linux Containers, Containers Expo Blog, @ThingsExpo

@DevOpsSummit: Blog Feed Post

APIs Are Not Web Pages | @DevOpsSummit #API #IoT #M2M #DNS #DevOps

Even though web pages might be built from APIs, they are not the same

There’s a tendency, particularly for networkers, to classify applications by the protocols they use. If it uses HTTP, it must be a web app. The thing is that HTTP has become what it was intended to be: a transport protocol. It is not an application protocol, in the sense that it defines application messages and states. It merely transports data in a very specific way.

That’s particularly important in the age of the API and, increasingly, the age of things that might be using APIs. You see, APIs are primarily data centric constructs while web pages (think any HTML-based app) are document centric constructs.

Data centric constructs tend to exchange, well, data. And document centric constructs… yes, exchange documents. Both might use HTTP as a mechanism to do that, but the actual payload carried differs dramatically. That’s because data centric constructs are concerned with exchanging data that is not necessarily meant for human consumption. It’s meant to provide the application with information that it can then process and display or act on accordingly. Document centric constructs, on the other hand, are meant to be consumed by human beings. Because of that they tend to include all the stuffs required to format, display, and present information.

Now, some web apps are a combination of both. There’s a framework composed of HTML that lays out the user interface, and then scripting that exchanges and processes data via APIs. The initial “load” grabs the document, subsequent interactions exchange data.

The reason I’m being so pedantic about this difference (ignoring that pedantry is my superpower) is because this distinction is critical when architecting for scale. The load generated by these interactions is different. Loading a single page is no trivial task these days. HTTP Archive, which tracks these fascinating kinds of numbers, notes that the average page required 35 TCP connections to load.

35 TCP connections.

That may be because the average document size was 24kB, comprising 889 elements.

So not only do we need to open a lot of connections, we’re taking a lot of time transferring data over those connections.

Now it is true that APIs also get objects. The thing is that except for images, almost all data is a far more compact form and it is data, not visual elements of a document or UI. For APIs, JSON is universally favored right now, and it adheres to a fairly consistent key:value paradigm, with appropriate embedded lists (arrays) of objects within it. Pagination and a smaller screen size dictate generally smaller pieces of data at a time, displayed in preparation for user interaction. The interface already exists, the data is simply used to populate that interface. This is not the same as HTML, where both interface and data presentation often need to occur as the result of transferring the objects.

Dependencies, too, are different. Many of the optimization techniques used by ADCs and front-end optimization services focus on the web of interdependencies that exist naturally in an HTML document. You can’t layout the page until you’ve loaded the style sheet that dictates it (CSS), and scripts may need to execute before data is processed for display (or as part of that process), and so on. The display of one object might depend on the existence of another that is not yet loaded. Hence the focus on optimizing the transfer of objects in an order that allows the UI to begin parsing and presenting information as soon as possible, giving the illusion, at least, of greater speed whether or not reality matches the illusion.

In other words, the API returns a single, large chunk of data. It may or may not trigger additional calls to retrieve additional objects. A web page, by design, automatically will.

So… to sum up this comparison, APIs exchanging JSON are not the same as HTML even though both are using HTTP as the transport layer.

What does that mean?
It means, kids, that optimizing an API is not the same as optimizing a web page. It means that techniques like minification (stripping out white space and comments) isn’t necessarily going to improve performance of APIs, nor will reordering objects or inlining scripts and style sheet elements. It means that optimization an API depends a whole lot on design (which networkers can’t do that much about) and on the intermediaries you use to scale and secure that API.

A significant number of APIs are geared toward mobile devices. Mobile devices are infamously plagued by poor performance largely due to excessive round trip times (RTT) from DNS and the overhead of connection establishment. APIs delivered via HTTP can stand to be connected with longer TCP idle times to prevent requiring re-establishment of the underlying TCP session during the application experience. To offset the impact on capacity that has (servers can only serve so many concurrent connections, after all), using an intermediary (a full proxy) that effectively splits the interaction between “client” side and “server” side can reduce the impact of longer-lived sessions while simultaneously improving performance by eliminating the extra round trips required to establish a TCP session by employing TCP multiplexing techniques (similar to HTTP/2).

Compression, too, if your API is returning significantly large chunks of data, can be a bonus. Many API optimizing blogs and articles point out that for some reason, compression is rarely “on” at the server. There are reasons for this, good reasons, but that doesn’t mean compression shouldn’t be used at all. When appropriate, let the intermediary (proxy) apply compression, as it is usually far enough upstream to avoid the potential negative impact of doing so.

The big deal here is that optimizing an API for performance is not necessarily the same as optimizing a web application, even though both use HTTP. So if you’re really looking for a performance boost for APIs and you can’t get developers to change what they’re doing, look to the network and, as is increasingly the case today, to the architecture.

Read the original blog entry...

More Stories By Lori MacVittie

Lori MacVittie is responsible for education and evangelism of application services available across F5’s entire product suite. Her role includes authorship of technical materials and participation in a number of community-based forums and industry standards organizations, among other efforts. MacVittie has extensive programming experience as an application architect, as well as network and systems development and administration expertise. Prior to joining F5, MacVittie was an award-winning Senior Technology Editor at Network Computing Magazine, where she conducted product research and evaluation focused on integration with application and network architectures, and authored articles on a variety of topics aimed at IT professionals. Her most recent area of focus included SOA-related products and architectures. She holds a B.S. in Information and Computing Science from the University of Wisconsin at Green Bay, and an M.S. in Computer Science from Nova Southeastern University.

@DevOpsSummit Stories
As Marc Andreessen says software is eating the world. Everything is rapidly moving toward being software-defined – from our phones and cars through our washing machines to the datacenter. However, there are larger challenges when implementing software defined on a larger scale - when building software defined infrastructure. In his session at 16th Cloud Expo, Boyan Ivanov, CEO of StorPool, provided some practical insights on what, how and why when implementing "software-defined" in the datacenter.
ChatOps is an emerging topic that has led to the wide availability of integrations between group chat and various other tools/platforms. Currently, HipChat is an extremely powerful collaboration platform due to the various ChatOps integrations that are available. However, DevOps automation can involve orchestration and complex workflows. In his session at @DevOpsSummit at 20th Cloud Expo, Himanshu Chhetri, CTO at Addteq, will cover practical examples and use cases such as self-provisioning infrastructure/applications, self-remediation workflows, integrating monitoring and complimenting integrations between Atlassian tools and other top tools in the industry.
The need for greater agility and scalability necessitated the digital transformation in the form of following equation: monolithic to microservices to serverless architecture (FaaS). To keep up with the cut-throat competition, the organisations need to update their technology stack to make software development their differentiating factor. Thus microservices architecture emerged as a potential method to provide development teams with greater flexibility and other advantages, such as the ability to deliver applications at warp speed using infrastructure as a service (IaaS) and platform as a service (PaaS) environments.
The use of containers by developers -- and now increasingly IT operators -- has grown from infatuation to deep and abiding love. But as with any long-term affair, the honeymoon soon leads to needing to live well together ... and maybe even getting some relationship help along the way. And so it goes with container orchestration and automation solutions, which are rapidly emerging as the means to maintain the bliss between rapid container adoption and broad container use among multiple cloud hosts. This BriefingsDirect cloud services maturity discussion focuses on new ways to gain container orchestration, to better use serverless computing models, and employ inclusive management to keep the container love alive.
A strange thing is happening along the way to the Internet of Things, namely far too many devices to work with and manage. It has become clear that we'll need much higher efficiency user experiences that can allow us to more easily and scalably work with the thousands of devices that will soon be in each of our lives. Enter the conversational interface revolution, combining bots we can literally talk with, gesture to, and even direct with our thoughts, with embedded artificial intelligence, which can process our conversational commands and orchestrate the outcomes we request across our personal and professional realm of connected devices.