Tech Debts VS More Features

Load Balancing vs Load Leveling vs Load Shedding
www.smiah.wiki/p/load-balan...

When traffic spikes, something breaks, or a service you rely on goes down, what stops your system from crashing?

The answer is a layered approach to resilience. Let’s break it down.

www.smiah.wiki/p/upstream-r...

But CTRL+F on Stack Overflow was divine.

Oh, and if ChatGPT calls you brilliant, don’t just trust it blindly. It is a trained prediction engine, more about keeping you happy than nailing the truth.

Because ChatGPT doesn’t care if it is right or not.

𝗬𝗼𝘂𝗿 𝗦𝘆𝘀𝘁𝗲𝗺 𝗗𝗶𝗱𝗻’𝘁 𝗙𝗮𝗶𝗹, 𝗜𝘁𝘀 𝗗𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝗰𝗶𝗲𝘀 𝗗𝗶𝗱

Downstream resiliency ensures a component can continue to function correctly even if the services it depends on experience issues.

Let’s break down a few key practices that make all the difference 👇

Resiliency is an outcome, not a practice. Resiliency Engineering is the practice of designing and building systems to achieve resiliency. Ensuring they can handle failures, adapt to disruptions, and recover gracefully without major downtime.

Anything that can go wrong will go wrong.
- Murphy’s Law

Things get tricky in distributed systems with multiple servers, especially across regions. If each server has its own rate limiter, it can lead two main issues:

• Inconsistent limits
• Race conditions

How does distributed rate limiting solve these challenges?

Passion is overrated.

It doesn’t last. It comes in waves, and when it crashes, it’s exhausting.

What sustains us isn’t passion. It's discipline.

Not glamorous, but it works.

You don’t need to be obsessed to be great.

Just care enough to do it well and keep learning.

That’s enough.

Smart folks are the ones who can effortlessly collect millions of users' personal pics freely to teach their AI.

Kudos to them.

Serverless: Built to be used less?

No need for a team to run servers. Serverless functions promise simplicity and cost-efficiency. You pay only when they work.

Sounds great, right? But here’s the catch: the more they run, the more you pay. If your Lambda is running constantly, it’s a red flag.

𝗧𝗿𝗮𝗻𝘀𝗮𝗰𝘁𝗶𝗼𝗻 𝗟𝗼𝗰𝗸𝗶𝗻𝗴 𝘃𝘀. 𝗔𝘀𝘆𝗻𝗰𝗵𝗿𝗼𝗻𝘆: 𝗧𝗵𝗲 𝗛𝗶𝗱𝗱𝗲𝗻 𝗖𝗼𝘀𝘁 𝗼𝗳 𝗖𝗼𝗻𝘁𝗿𝗼𝗹

Markets move in milliseconds. Every millisecond matters. Choosing wrong approach can cost you more than just latency. This isn’t just about database locks or async messaging. It’s a fundamental design choice.

𝗥𝗼𝗯𝘂𝘀𝘁 𝗼𝗿 𝗥𝗲𝘀𝗶𝗹𝗶𝗲𝗻𝘁? 𝗪𝗵𝗶𝗰𝗵 𝗢𝗻𝗲 𝗧𝗿𝘂𝗹𝘆 𝗠𝗮𝗸𝗲𝘀 𝗮 𝗦𝘆𝘀𝘁𝗲𝗺 𝗨𝗻𝗯𝗿𝗲𝗮𝗸𝗮𝗯𝗹𝗲?

→ 𝗥𝗼𝗯𝘂𝘀𝘁𝗻𝗲𝘀𝘀: can the system perform within predetermined expected boundaries.
→𝗥𝗲𝘀𝗶𝗹𝗶𝗲𝗻𝗰𝘆: can it adapt when the capacity to work is exceeded.

Or, Combine both - robustness to withstand and resiliency to recover?

𝗣𝗿𝗶𝗼𝗿𝗶𝘁𝘆 𝗤𝘂𝗲𝘂𝗲𝘀 𝗕𝗼𝘁𝘁𝗹𝗲𝗻𝗲𝗰𝗸𝘀: 𝗪𝗵𝗲𝗻 𝗽𝗿𝗶𝗼𝗿𝗶𝘁𝘆 𝗾𝘂𝗲𝘂𝗲 𝗹𝗼𝘀𝗶𝗻𝗴 𝗽𝗿𝗶𝗼𝗿𝗶𝘁𝘆

The idea from Chris G.'s Ph.D. dissertation. This shows how priority queues lose priority: bottlenecks can delay high-priority tasks and process lower-priority ones first.

𝗛𝗼𝘄 𝗱𝗼𝗲𝘀 𝗶𝘁 𝗹𝗼𝗼𝗸 𝗽𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗮𝘁𝗶𝗰𝗮𝗹𝗹𝘆: bit.ly/3R04KWn

𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗶𝗻𝗴 𝗰𝗼𝗱𝗲 𝗶𝘀𝗻'𝘁 𝗷𝘂𝘀𝘁 𝗮𝗯𝗼𝘂𝘁 𝘄𝗿𝗶𝘁𝗶𝗻𝗴 𝗶𝘁.

A key aspect of performance tuning is selecting the right data structure. I profiled stack implementations to optimize performance, and the results were mind blowing.

Here's what I found -

Software should be correct first, then clear, then fast. Factored is nice to have.

Your writing does the job it was designed for. It is written to be as easy to understand as possible. It does its job quickly.

It is structured into modular, reusable, well-organized, and maintainable components.

The most useful form of patience is persistence.

Patience implies waiting for things to improve on their own.

Persistence implies keeping your head down and continuing to work when things take longer than you expect.

@jamesclear.bsky.social

If your team waits for direction instead of stepping up, you’re not fostering accountability. In software engineering, teams thrive when they feel safe to take risks, share ideas, and be vulnerable in front of each others.

Empower teams to step up and support each other, be there for each other.

Software engineering wisdom start to kick in when we realize that smart tools can amplify productivity and precision in engineering workflows, whether through AI or other technologies.

All are just force multipliers.