Take a step back & look at reason for budget constraint. I categorize the next step in 2 sections 1) when budget constraint is determental for existence of business 2) when it is not Let's say in case 1. It's simple we can't have house design ac vents when it's on fire. So take practical approach. Descope & identify most practical & atmost necessary aspects of arch to keep business running. In case 2... I suggest job of architecture is to do right thing for long term. So keep pushback on need of doing right thing. Having said that ... building skill to determine which case it is , is the most sort after skill comes with experience & learning from mistakes. If you start getting it right, you have arrived in elite class of architects.

To balance cost-cutting with quality in system architecture: Leverage Open Source: Use open-source tools to save on licensing without compromising features. Adopt Modular Design: Enable incremental upgrades to aviod expensive system maintenance. Optimize Vendor Contracts: Negotiate for discounts or longer-term agreements for better rates. Strategic planning ensures cost efficiency without undermining robustness.

If I need to cut costs in system architecture, assuming compliance allows open-source solutions, my first step is to evaluate paid technologies in the architecture and identify equivalent open-source alternatives that provide similar capabilities without compromising quality. I would then optimize the development cycle by streamlining or minimizing phases, ensuring this does not introduce technical debt that could affect long-term scalability or maintainability. Additionally, I would create a roadmap to deliver a Minimum Viable Product (MVP) as the initial phase, focusing on core functionalities. Subsequent phases would be scheduled in a flexible timeline, allowing adaptation to budget constraints while ensuring incremental value delivery.

To optimize cloud costs, specifically AWS Costs when you're facing budget constraints: Right-sizing: adjust instance sizes Spot and reserved: for savings and predictable loads Serverless: when it's needed Auto-scaling: enable dynamic scaling Storage tiering: use Intelligent-Tiering or Glacier Savings plans: commit to usage Monitoring: set up cost explorer, budgets, and alarms AI Forecasting: use AWS Cost Anomaly Detection + AI Tools Tagging governance: implement and use Eliminate waste: identify and terminate unused instances, volumes and IPs Use graviton: if possible Custom budgets: set cost limits with automated actions Networking: optimize data transfer costs. Optimize DBs: pick appropriate solution: serverless, RDS or EC2

Focus on key elements and purpose - don't get bogged down in process box-ticking. Diagrams and artifacts should be accurate and understandable first and foremost. To maintain and improve - look for big wins, rank by benefit and difficulty. Sacrifice perfection for improvement - just because you cannot deliver to every standard immediately doesn't mean you shouldn't move things forward. Staged maintenance and change - reduce complexity with transition stages. Map out each stage in adequate, but not excessive detail so the roadmap is well-defined and understood. Follow through - don't retain interim states as this leaves technical debt increasing complexity and costs permanently. Automate highly repetitive or manually onerous tasks.