I recently watched a reaction video about an article. This got me thinking about how the architecture of the systems at my last employer changed over the years, and if they qualify as microservice-ish.
Background
At Mexpro, I worked on the same application for ~15 years. Over the years, feeling like I was being “left behind” working on a Perl app, I fell into hype cycles. I tried implementing parts of the system in Python, NodeJS, and Ruby on Rails, essentially creating either microservices, or micro-frontends (islands?). The stack at the time rested on 2005 technology, so how did I build out services and frontends without modern “cloud” techniques?
- When not running, each app scales to zero.
- Nearly-instant cold-boot times.
- Language agnostic.
- Interface standardized in 1995.
- Each app is was deployed independently.
- Not exhibited in the sample app.
What was built
The core app was a Perl monolith, using Mason templates, and the Prototype Javascript “framework”, but had several microservices tacked on:
- Python microservice for interacting with Docusign.
- Ruby microservice for white-labeling the application for Affiliates.
- Go microservice for tracking page view events.
An important aspect here is that the Perl monolith did not call out to the other services.
Implementation
What is this amazing technology? CGI.
The core of the implementation is Apache’s httpd.
httpd enables both Server Side Includes, and CGI execution allowing the
“islands” implementation, where the Perl monolith could output
special HTML comments
which httpd would render call into the CGI scripts, and include the output in
the page.
I put together a dead-simple sample application to demonstrate the approach and benchmark execution. This consists of four “services” (they’re “hello world” levels of complexity), written in Bash, Go, Perl, and Rust, and composited into a single page. This means that each page load in the data below includes a call to four microservices.
Performance
I used the
Apache Benchmark
utility which ships with httpd to run tests. Each test ran for 100,000
requests.
1 vCPU
On a single-core, $4/mo, Digital Ocean droplet:
Single User
| Metric | min | mean | [+/-sd] | median | max |
|---|---|---|---|---|---|
| Connect: | 0 | 0 | 0.0 | 0 | 3 |
| Processing: | 19 | 22 | 2.1 | 21 | 104 |
| Waiting: | 2 | 3 | 0.6 | 3 | 22 |
| Total: | 19 | 22 | 2.1 | 21 | 104 |
5-Users
| Metric | min | mean | [+/-sd] | median | max |
|---|---|---|---|---|---|
| Connect: | 0 | 0 | 0.1 | 0 | 4 |
| Processing: | 23 | 61 | 8.0 | 61 | 199 |
| Waiting: | 2 | 15 | 4.2 | 15 | 137 |
| Total: | 23 | 61 | 8.0 | 61 | 199 |
25-Users
| Metric | min | mean | [+/-sd] | median | max |
|---|---|---|---|---|---|
| Connect: | 0 | 0 | 0.1 | 0 | 5 |
| Processing: | 204 | 351 | 49.5 | 354 | 901 |
| Waiting: | 2 | 95 | 26.7 | 91 | 605 |
| Total: | 208 | 351 | 49.5 | 354 | 901 |
As we’d expect, the requests slow down as we increase concurrency. Single CPU, this is bound to happen. Keep in mind that the benchmark was performed on the same machine as the server was running on.
4 vCPU
On a four-core, $48/mo, Digital Ocean droplet:
Single Users
| Metric | min | mean | [+/-sd] | median | max |
|---|---|---|---|---|---|
| Connect: | 0 | 0 | 0.0 | 0 | 3 |
| Processing: | 9 | 20 | 5.0 | 21 | 75 |
| Waiting: | 2 | 3 | 1.0 | 3 | 42 |
| Total: | 9 | 20 | 5.0 | 21 | 75 |
5-Users
| Metric | min | mean | [+/-sd] | median | max |
|---|---|---|---|---|---|
| Connect: | 0 | 0 | 0.0 | 0 | 2 |
| Processing: | 9 | 17 | 5.3 | 15 | 54 |
| Waiting: | 2 | 4 | 1.5 | 3 | 24 |
| Total: | 9 | 17 | 5.3 | 15 | 54 |
25-Users
| Metric | min | mean | [+/-sd] | median | max |
|---|---|---|---|---|---|
| Connect: | 0 | 0 | 0.0 | 0 | 4 |
| Processing: | 30 | 70 | 10.8 | 69 | 184 |
| Waiting: | 2 | 16 | 4.7 | 15 | 150 |
| Total: | 30 | 70 | 10.8 | 69 | 184 |
Requests time still increases with concurrency, but this time we can see that vertically scaling the CPU allows the app to scale as well.
The Future
There is nothing stopping CGI from continuing to be a viable option for this
type of service composition. In addition, an upgrade to nginx can enhance the
situation with parallel processing Server Side Includes.