The "APM" solutions we've come to love over the last 2 decades can't handle Serverless Functions or deliver the same performance and operational details that they deliver for other architectural constructs — including App Servers, Frameworks, Cloud, even Containers. And the reason is that they're methodologies for collecting performance data simply won't operate with the same characteristics as it would in persistent code.
Start with: Can APM Really Handle Serverless? - Part 1
And Then There's "Observability"
There are three ways conventional tools deliver service performance data to your monitoring tools:
1. API built into the platform — the consummate example of this is Lambda and Xray. This at least provides some level of performance detail, but it's nowhere near the richness and depth DevOps teams are used to (or need). PLUS: X-Ray provides data about the specific instance, AND ONLY the specific instance; but applications are distributed connected things — getting information about a single service without any knowledge of connected systems doesn't help understand what is getting in the way of distributed performance issues.
2. Pre-instrument the code — Like the way that some application monitoring tools tackled the container incompatibility issue, you could always run the code through an instrumentation step. While this allows the APM solution to get its hooks into the code, it loses the benefit of years of technology advancement in real-time instrumentation which allows decisions to be made on how much (or how little) to measure.
3. Open Source Observability — one or more of the observability APIs could always be put into place — of course, this requires some, if not a ton of, developer time to put the API instrumentation into their code:
■ Deciding what to instrument
■ Selecting which metrics to provide
■ Coding it in
■ Identifying those metrics for the tool
■ Selecting a visualization (If possible)
■ Analyzing logs for serverless events
All three of these approaches actually run counter to the value and efficiency promise of using Serverless Functions in a distributed application.
Option (1) simply doesn't have the juice to provide the detailed information needed for complex applications — and ZERO information about distributed functions, their dependencies (upstream and downstream) with other services, and no context or understanding of traces or end users to examine performance against.
(2) and (3) have similar visibility problems, depending on how much instrumentation is turned on and how much time you're willing to invest in your developers writing performance monitoring instead of their functional code. However, even though those decision points aren't trivial, the real problem comes in the way of cost and performance overhead.
After all, regardless of whether you load code pre-instrumented with a tool or code that your developers added monitoring lines of code, you are essentially operating at 10, 20, even 50% more code, cycles, overhead and cost than just your functional code. Replicate that overhead enough times and not only are you impacting your user service levels, you're blowing through all your serverless "savings" by paying for additional non-functional code.
There Are Options
Look, all is not doom and gloom. There are methods and ways to get the performance data you need across your distributed application, without blowing your budget or your error budget. Look for non-traditional APM tools that don't rely on either legacy instrumentation methods OR open source observability (BONUS, though, if the tool can actually run its own monitoring AND support observability instrumentation).
The key to these tools is that they're more intricately connected with the serverless infrastructure than a legacy APM tool might have. Good news — this means that there are solutions out there that can instrument serverless on the fly, using their connections with the infrastructure. Bad news — if the tool and infrastructure don't match up, you're back to square one. Sometimes that means you may change your infrastructure choice — and sometimes, that means you have to go with the basic instance-based metrics — and use your EUM to the best of your ability.
Anyway, don't be discouraged by this. You can still effectively use Serverless functions to create a more cost effective and efficient multi-cloud application ... and you don't necessarily have to give up that application visibility you've become accustomed to seeing. You will have to check (up front, hopefully) that you have the right tools and right infrastructure to do both. Happy Serverlessing!!!!
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