My Choice of Programming Languages

When I was a kid, I used to spend days tinkering with woodworking tools. I was lucky enough to have a wide set of tools at my disposal. However, there was no one around to give me a hint about what tool to use when. So, I quickly came up with a heuristic: if my fingers and a tool survived an exercise, I've used the right tool; if either the fingers or the tool got damaged, I'd try other tools for the same task until I find the right one. And it worked quite well for me! Since then, I'm an apologist of the idea that every tool is good only for a certain set of tasks.

A programming language is yet another kind of tool. When I became a software developer, I adapted my heuristic to the new reality: if, while solving a task using a certain language, I suffer too much (fingers damage) or I need to hack things more often than not (tool damage), it's a wrong choice of a language.

Since the language is just a tool, my programming toolbox is defined by the tasks I work on the most often. Since 2010, I've worked in many domains, starting from web UI development and ending with writing code for infrastructure components. I find pleasure in being a generalist (jack of all trades), but there is always a pitfall of spreading yourself too thin (master of none). So, for the past few years, I've been trying to limit my sphere of expertise with the server-side, distributed systems, and infrastructure. Hence, the following choice of languages.

Language logos

Read more

Rust - Writing Parsers With nom Parser Combinator Framework

I've been working on my new Rust side-project for several months now, and I've got some learnings to share. The project is called pq - it's a command-line tool to parse and query log files as time series. It comes with its own domain-specific language that is highly influenced by PromQL. A typical pq usage may look like this:

tail -f /var/log/nginx/access.log | pq '
/...some fancy regex.../
| map {
    .0 as ip,
    .1:ts,
    .2 as method,
    .3:str as status_code,
    .4 as content_len
  }
| select topk(
      10,
      sum(
          count_over_time(
              __line__{method="GET", status_code="200"}[1s]
          )
      ) by (ip)
  )
| to_json
'

pq has many components, including various log parsing strategies and a pretty sophisticated query execution engine. But surprisingly or not, about half of the time I've put into this project so far was dedicated to writing the parser of the pq's own query language. To be honest, when I was starting the project, I didn't see that coming...

nom logo

Luckily, writing a parser in Rust was mostly a pleasant experience, thanks to a crate concisely named nom. Although learning how to write parsers with nom wasn't completely seamless. So here is my journey.

Read more

pq - parse and query log files as time series

I often find myself staring at Nginx or Envoy access logs flooding my screens with real-time data. My only wish at such moments is to be able to aggregate these lines somehow and analyze the output at a slower pace, ideally, with some familiar and concise query language. And to my surprise, I haven't met a tool satisfying all my requirements yet. Well, I should be honest here - I haven't done thorough research. But if there would be a tool as widely known as jq for JSON, I wouldn't miss it probably.

So, here we go - my attempt to write a full-fledged parsing and query engine and master Rust at the same time. Yes, I know, it's a bad idea. But who has time for good ones?

First things first - a usage preview:

Read more

Understanding Rust Privacy and Visibility Model

I spent the last couple of months writing code in Rust. It was probably my third or fourth attempt to write something substantial in this language. And every time my level of understanding of things deepened. I'm by no means a Rust expert so probably I'll be extremely inaccurate in the terminology here. And likely I'll get lots of technical details wrong too. But I had this epiphany moment of how the visibility and privacy model works in Rust so I can't help but think of sharing it with someone else.

Read more

Implementing Container Runtime Shim: Interactive Containers

In the previous articles, we discussed the scope of the container runtime shim and drafted the minimum viable version. Now, it's time to move on and have some fun with more advanced scenarios! Have you ever wondered how docker run -i or kubectl run --stdin work? If so, this article is for you! We will try to replicate this piece of functionality in our experimental container manager. And as you have probably guessed, the container runtime shim will do a lot of heavy lifting here again.

conman - interactive container demo

Read more