Navigating the Challenges of Rapid Growth and Software Development
As a seasoned IT professional, I’ve seen my fair share of software startup challenges. From managing memory usage and CPU spikes to addressing language adoption and documentation shortcomings, there’s no shortage of pitfalls that can derail a young company’s progress. But with the right strategies and a proactive approach, you can tame these issues and keep your programs up and running, even as your startup scales.
Mastering Memory Management in Go
One of the common challenges startups face is balancing performance and memory usage, especially when working with memory-managed languages like Go. The team at Akita Software experienced this firsthand when their API traffic monitoring tool, built with Go, started to balloon in memory usage as their users pushed more traffic through the system.
The key to taming Go’s memory management lies in understanding the nuances of its garbage collector and finding creative ways to optimize your memory footprint. As the Akita team discovered, setting reasonable limits on things like the TCP reassembly buffer and carefully managing memory allocations can make a significant difference.
“Goâs focus on simplicity means that there is only a single parameter, SetGCPercent, which controls how much larger the heap is than the live objects within it. This can be used to reduce memory overhead at the cost of greater CPU usage, or vice versa.”
By profiling their application and identifying hot spots, the Akita team was able to make targeted improvements, such as:
- Optimizing Reassembly Buffers: They set limits on the maximum size of the reassembly buffer per connection and across all connections, preventing memory spikes during periods of high traffic.
- Reducing Temporary Allocations: The team identified areas where they could avoid unnecessary memory allocations, such as compiling regular expressions once instead of on each use.
- Optimizing Hash Computations: By generating custom hash functions for their specific data structures, they were able to significantly reduce memory usage compared to using a more generic hashing library.
These steps ultimately helped the Akita team keep their agent’s memory usage in check, even in their production environment, without resorting to a complete rewrite in a more memory-conscious language like Rust.
Addressing the Rust Rewrite Dilemma
Speaking of Rust, the decision to rewrite a system in this language is one that many startups grapple with. As the author of the Medium article highlighted, Rust can bring significant benefits in terms of safety and performance, but it also comes with a steep learning curve and potential productivity challenges, especially for teams in a rapid growth phase.
“Rust is supposed to be the best thing since sliced bread, so why was it not working so well for us? I’ve worked in dozens of languages in my career, and with few exceptions most modern, procedural languages (C++, Go, Python, Java, etc.) all very similar in terms of their basic concepts. Each language has its differences but usually it’s a matter of learning a few key patterns that differ across languages and then one can be productive pretty quickly. With Rust, though, one needs to learn entirely new ideas — things like lifetimes, ownership, and the borrow checker.”
The decision to use Rust ultimately comes down to weighing the potential benefits against the cost in terms of team productivity and velocity. For startups where rapid iteration and feature delivery are critical, the productivity hit from adopting Rust may outweigh the advantages, at least in the short term.
“I am a pragmatist. I would much rather have my team sink time into debugging the occasional memory leak or type error for code written in, say, Python or Go, than have everyone on the team suffer a 4x productivity hit for using a language designed to avoid these problems entirely.”
That said, Rust can be an excellent choice for certain types of projects, such as those requiring high-performance, safety-critical systems. The key is to carefully evaluate your startup’s needs and priorities before making the decision to rewrite in Rust or stick with a more familiar language like Go or Python.
Overcoming Documentation and Library Ecosystem Challenges
Another pain point that can plague startups working with newer technologies is the relative immaturity of the supporting documentation and library ecosystem. As the author noted, the Rust community has made great strides, but the docs for many popular libraries can still be sparse, and understanding how to use them is often a challenge.
“The docs for a lot of popular libraries are pretty sparse, and one often needs to read the source code of a given library to understand how to use it. This is bad. Rust apologists on the team would often say things like ‘async/await are still really new’ and ‘yeah the docs for that library are lacking’ but these shortcomings impacted the team pretty significantly.”
This is a common issue that can arise when working with cutting-edge technologies, whether it’s Rust, a new web framework, or an emerging programming language. The solution often involves a combination of patience, community engagement, and a willingness to dive into the source code when necessary.
“No matter how great the core language documentation and tutorials are, if you can’t figure out how to use the libraries, it doesn’t much matter (unless you’re planning to write everything from scratch, of course).”
To overcome these challenges, startups can consider the following strategies:
- Invest in documentation and knowledge sharing: Encourage your team to contribute to the open-source projects they rely on, helping to improve documentation and share their learnings.
- Leverage community resources: Stay involved in online forums, GitHub discussions, and other channels where users can learn from each other and get support.
- Prototype and experiment: Don’t be afraid to try different approaches, even if it means digging into the source code. Rapid prototyping can help you find the right solutions faster.
By addressing the gaps in documentation and library support, startups can avoid getting bogged down in technical debt and keep their development efforts moving forward.
Balancing Performance and Productivity
At the end of the day, the key for startups is to find the right balance between performance, safety, and productivity. While languages like Rust offer compelling advantages, the associated learning curve and productivity hit may not be the best fit, especially in the early stages of rapid growth.
“Rust is a great choice for things like kernel modules, firmware, game engines, etc. where performance and safety are paramount, and in situations where it may be hard to do really thorough testing prior to shipping. For individual projects, or very small (say, 2–3 person) teams, Rust would likely be just fine.”
For many startups, a more pragmatic approach, like the one taken by the Akita team, may be the better option. By carefully optimizing their existing systems, leveraging the strengths of languages like Go and Python, and addressing performance issues through targeted improvements, startups can keep their programs running smoothly without sacrificing productivity or velocity.
Remember, there’s no one-size-fits-all solution when it comes to software development. The key is to stay agile, experiment with different approaches, and always keep the needs of your users and the overall success of your startup in mind.
To learn more about optimizing your software systems and tackling common startup challenges, be sure to visit https://itfix.org.uk/, where you’ll find a wealth of informative articles and resources from seasoned IT professionals.
