The Evolution of APM
In today's hyper-competitive application atmosphere, every business strives to launch faster and smarter than their competitors. From the rise of Agile development practices like DevOps and DevSecOps to the use of automation in the SDLC, businesses crave speed. But speed comes with consequences. Launching faster requires constant monitoring to prevent security threats and breakpoints from destroying your finished product. What good is rapid launch speeds if you're producing sub-par apps?
That's where application performance monitoring comes into play. With application performance monitoring, you can launch faster AND smarter.
What is Application Performance Monitoring?
Application Performance Monitoring (APM) is any software tool or service that monitors your applications. We know! That definition sounds incredibly vague. And, to be perfectly honest, it is. There isn't a consensus on the definition of APM, and various vendors throughout the years have flown their software solutions under the APM flag. There isn't even a consensus on the words that make up APM. Some vendors call it application performance monitoring, some call it application performance management, and others call it application portfolio management.
The definition that Gartner gives for APM is:
Application performance monitoring (APM) is a suite of monitoring software comprising digital experience monitoring (DEM), application discovery, tracing and diagnostics, and purpose-built artificial intelligence for IT operations.
In other words, application performance monitoring is a subset of digital experience monitoring. Because of this, we prefer the term application performance monitoring — not application performance management. Given its direct relation to digital experience monitoring, applying the moniker "monitoring" to both terminologies breeds consistency (in our humble opinion).
Some brands claim that application performance management is the ability to track the performance of all applications in relation to one another, and you'll hear other brands claim that application performance management is a more comprehensive (i.e., "code plus") version of application performance monitoring. We don't want to go deep into the architecture of the definitions, and we certainly don't want to create more confusion by adding in our own elements to the definition to help promote our product line.
For those purposes, we're settling for this definition. Application Performance Monitoring/Management (APM) is any software tool or service that monitors your application performance in some capacity.
Note: You'll notice that Wikipedia currently uses the "Application Performance Management" moniker. This has led to a rise in the number of companies that use "management." That being said, Gartner, DynaTrace, and other APM leaders use "Application Performance Monitoring." This is really just a poh-tay-toe, poh-ta-toe situation.
A Short History of Application Performance Monitoring
Application performance monitoring solutions first popped up in the 90s when companies like Precise Software Solutions and Optier started selling solutions packaged as APM. The mid-2000s saw the rise of today's more robust APM offerings from companies like AppDynamics and DynaTrace. It was during the second rise of APM that the terminology APM shifted from management to monitoring.
After 2010, the number of APM solutions started to swell. Today, there are thousands of APM offerings. To help clarify how these software solutions can help businesses, Gartner adjusts its definition to APM yearly. In 2019, Gartner defines an APM "suite" as a tool that combines:
- Digital experience monitoring (DEM): Gartner defines the DEM component of APM as a software tool that "supports the optimization of the operational experience and behavior of a digital agent, human or machine, as it interacts with enterprise applications and services." This includes two primary tools — synthetic user monitoring and real-user monitoring.
- Application discovery, tracing, and diagnostics (ADTD): These tools seek to understand the relationships between applications using methods like bytecode instrumentation (BCI).
- Artificial intelligence for IT operations (AIOps): These tools use machine learning (ML) to support IT in the SDLC.
For clarification, an APM tool DOES NOT have to contain all three of these functions. To be an "APM suite," it does. In reality, each of these (on their own) could suffice as an APM tool. But these three categories should give you some clarity on what APM does in the business space.
Why Bother Monitoring Your Apps?
Let's be honest. You don't have time to dive deep into the nitty-gritty details of APM. And, you probably don't care about all the industry back-and-forth over definitions (we'll be honest: it's petty). You care about how it helps you. Why should your business bother purchasing an APM solution, adding it to your already bulging tech stack, and training your employees on it? It has to be pretty valuable if you're going to do that, right?
Well, let's start with these stats.
- The average app loses around 95% of its customers in the first 90 days.
- 67% of businesses say "poor experiences" are the primary reason it left a company
- A 1 to 10-second delay in load time increases bounce rates by 123%
- 32% of loyal customers will leave after one poor experience
- 21% of mobile apps have only ever been used ONCE
What do all of these statistics have in common? APM can help you solve them. But not all APM solutions are built the same. Despite the plethora of all-in-one APM packages (which cost a pretty penny or two), solving your app UX frictions typically only requires one APM solution — synthetic user monitoring.
Why Synthetic Monitoring?
The two most common APM monitoring solutions are synthetic user monitoring and real-user monitoring (RUM). We won't dive deep into the difference between them in this post (there's a handy-dandy post we wrote about it here), but we'll mainly focus on synthetic monitoring. Why? Because we believe it's a better all-around solution. That being said, we definitely recommend that you try them both out (and possibly use them both simultaneously) to increase the scope of your monitoring capabilities.
Synthetic monitoring is an APM methodology that simulates users to test your application(s). In other words, with synthetic monitoring, robots simulate the actions of real users browsing your applications via machine learning. Then, you get feedback that shows you UX issues, breakpoints, and other issues with your app. You can use this iteratively throughout your SDLC (highly recommended) or ad-hoc after updates or code changes. There are several benefits to using synthetic robots, including:
- Increased revenue: When your team is creating an app, any small issue can turn into a massive revenue leak. For example, back in 2012, Amazon admitted that a single 1-second delay in load time caused them to lose $1.6 billion. For clarity, this number has almost certainly increased exponentially. You can't afford to cycle broken apps into the launch phase.
- Branding and reputation: When users have a poor experience with your app, they're probably not going to tell you. In fact, 92% of them will just leave (possibly forever). It's not all bad. 39% of customers will only leave your company for 2 years due to a single mistake... Yeah. Perfection matters. Synthetic monitoring detects problems throughout your entire SDLC to help you create more compatible, customer-centric apps.
- Reduced IT debt: What happens when you let app issues slip through the cracks? You get tickets. Beautiful, wonderful, evil tickets. Every IT ticket is a cost. Not only do you have to hire people to handle them, but if you don't solve them fast enough, you lose customers. In fact, 57% of people leave a brand because they're issue went unnoticed. Synthetic monitoring helps alleviate that pain by preventing issues from happening in the first place. Forget reactive. Get proactive.
- Increased productivity: Not only does synthetic monitoring allow you to monitor for issues earlier during the app cycle, but it lets you reduce labor during the testing phase to allocate to more critical app components (like development). This creates an upstream and downstream productivity boom.
- DevOps agility: One of the core tenants of DevOps is testing earlier and executing smarter. With shift left automated synthetic user monitoring, you can test earlier rather than later.
To be frank, APM is a baked-in requirement of DevOps. In fact, we would go so far as to say that shift left monitoring is an essential part of any Agile development strategy. And, we're past the point of calling synthetic user monitoring disruptive; it's the norm. If you aren't automating app testing, your competitors are. It's that simple.
But, what if you don't have time? After all, coding a new instance for every app takes time. And you may already have a workhorse team of testers. Does it really make sense to pull them out of testing and retrain them on coding a testing tool? It seems counterproductive, right? It is! That's why we're seeing the rise of no-code across app types, but especially in the APM testing space.
The Rise of No-code APM Solutions
The no-code market is booming. In fact, we would consider no-code the next logical evolution in the software ecosystem. So, naturally, no-code is also part of APM's evolution. Simply put, companies don't have time to deal with coding. What's the value of a synthetic monitoring solution if you have to spend time coding it for every new app cycle?
You have the need for speed. You want to hack your launchpad, not add another piece of luggage to it. Luckily, code-free synthetic user monitoring tools have started to worm their way into the business consciousness. So how is it possible? How are there no-code synthetic user monitoring like 2 Steps that gives you 24/7 monitoring for all of your apps without the need for code?
Well... it's a bit of a trick.
You're still coding. You just don't know you're coding.
2 Steps team of programmers built 2 Steps with foundational coding models that let you drag-and-drop and instantly run sequences without diving into any lines of code. But your coding when you make changes to the interface. In other words, it's invisible coding that anyone can do. We do this by utilizing image recognition software.
How 2 Steps Can Help You Realize the No-code Synthetic User Monitoring Renaissance
Here's the question. Do you want to create an environment of shift left testing that improves efficiencies, productivity, security, and speed? At 2 Steps we started with a simple question. How can we make APM easier for the average business? We built our software to handle the most complex app testing atmospheres without requiring a single line of code. Then, we made our tool instantly integrate with Splunk to give you a single pane of truth for all of your testing needs.
Imagine being able to automatically test your UX for breakpoints, sniff out bad code, and reduce the number of touchpoints without ever lifting a finger. That's the power of 2 Steps. We believe that no-code synthetic user monitoring is the future of DevOps and Agile work environments. Are you ready to join the revolution? Contact us to learn more. And, check out the rest of our blog where we touch on some of the most important issues facing businesses in today's DevOps-heavy development ecosystem.
Let's embrace the future — one app at a time.