Web Dev Rundown: Pure Silicon Demos, Error Logging Philosophy, and Self-Hosting Postgres

Three interesting technical discussions caught attention on Hacker News this week: a pure silicon demo coded without CPU or memory, a thoughtful take on error logging philosophy, and practical advice on self-hosting Postgres. Each offers insights for developers building modern web applications.

Pure Silicon Demo Coding: No CPU, No Memory, Just 4k Gates

A fascinating hardware project demonstrates demo effects coded directly in silicon logic gates—no CPU, no memory, just combinatorial logic generating VGA output. The project uses only 4,096 logic gates to create animated graphics.

Why This Matters for Web Developers

While most web developers won't be designing custom silicon, this project illustrates important principles:

Constraints Drive Creativity: Working within extreme limitations forces elegant solutions. The same principle applies to web performance—constraints like mobile bandwidth or slow devices push us toward better architectures.

Understanding the Stack: Knowing what happens below your abstraction layer helps you write better code. Understanding how browsers render, how JavaScript engines optimize, or how CDNs cache makes you a better web developer.

Direct Hardware Manipulation: WebAssembly and technologies like WebGPU are bringing web developers closer to hardware. Projects like this remind us that understanding low-level concepts remains valuable even in high-level development.

The Hacker News discussion shows developers appreciating the technical achievement while discussing practical applications of hardware-level optimization.

Log Level 'Error' Should Mean Something Needs Fixing

An insightful article argues that error logs should only contain errors that require human intervention. If something appears in your error logs but doesn't need fixing, it shouldn't be logged as an error.

The Problem with Noisy Error Logs

Many applications log everything as errors:

• Expected validation failures
• Transient network issues that retry successfully
• User input errors that are handled gracefully
• Rate limiting responses
• Cache misses

When error logs contain routine operational events, real problems get buried in noise. Teams stop reviewing error logs because they're full of "errors" that aren't actually problems.

Practical Implications for CMS Development

For content management systems and web applications, this philosophy matters:

Content Operations: When a user submits invalid data, that's not an error—it's expected behavior. Log it as info or debug, not error.

API Integrations: When an AI generation request times out but succeeds on retry, that's not an error requiring investigation—it's normal distributed system behavior.

Media Processing: When image optimization takes longer than usual but completes successfully, that's not an error—it's information about system load.

Authentication: When a user enters wrong credentials, that's not an error—it's expected user behavior. Logging it as error creates noise and false alerts.

The extensive discussion reveals that many teams struggle with this. Developers share stories of error logs so noisy that real production issues go unnoticed for hours or days.

Implementation Strategy

Structure your logging with clear severity levels:

ERROR: Something broke that requires immediate human intervention

• Database connection failed and retries exhausted
• Payment processing failed with no fallback
• Critical service unavailable
• Data corruption detected

WARN: Something unusual happened but the system handled it

• Retry succeeded after initial failure
• Fallback mechanism activated
• Approaching resource limits
• Deprecated API usage

INFO: Normal operational events

• Request processed successfully
• Scheduled job completed
• User logged in
• Cache invalidated

DEBUG: Detailed information for troubleshooting

• Request/response payloads
• State transitions
• Algorithm decisions
• Performance metrics

For Cosmic's platform, we follow this philosophy strictly. Our error logs contain only genuine problems that need investigation. Expected operational events—AI generation requests, content updates, media uploads—log at appropriate levels based on outcome.

Go Ahead, Self-Host Postgres

An article making the case for self-hosting Postgres challenges the assumption that managed database services are always the right choice. The author argues that modern Postgres is stable, well-documented, and manageable for teams with basic operational capabilities.

The Case for Self-Hosting

Cost Predictability: Managed services charge for convenience, and costs can escalate quickly with storage, IOPS, and bandwidth. Self-hosted infrastructure has predictable costs.

Performance Control: You control hardware specs, connection limits, and optimization settings directly rather than working within managed service constraints.

Data Sovereignty: Your data stays on infrastructure you control, which matters for compliance, privacy, and vendor lock-in concerns.

Learning Opportunity: Running your own database teaches you how it actually works, making you better at optimizing queries and schema design.

When Self-Hosting Makes Sense

The Hacker News discussion reveals nuanced perspectives:

Good Candidates for Self-Hosting:

• Teams with infrastructure expertise
• Applications with predictable database loads
• Projects with compliance requirements
• Organizations running other self-hosted infrastructure
• Workloads with high database I/O costs on managed services

Better Managed Service Candidates:

• Small teams focused on product development
• Applications needing global multi-region replication
• Startups prioritizing speed over cost optimization
• Teams without database expertise
• Applications with highly variable loads

Practical Considerations

Self-hosting Postgres requires handling:

Backups: Automated backup schedules, testing restore procedures, offsite backup storage

High Availability: Replication setup, failover procedures, connection pooling

Monitoring: Query performance tracking, resource usage alerts, replication lag monitoring

Upgrades: Version upgrades, patch management, migration testing

Security: Access control, encryption at rest and in transit, vulnerability patching

The Middle Ground

Modern infrastructure platforms offer alternatives between full self-hosting and managed services:

Kubernetes Operators: Tools like CloudNativePG or Zalando's Postgres Operator handle operational tasks while giving you control.

Infrastructure as Code: Terraform and similar tools let you automate database provisioning and management while maintaining control.

Hybrid Approaches: Run Postgres on your infrastructure but use managed backup services, monitoring platforms, or connection poolers.

Connecting the Themes: Infrastructure Philosophy for AI-Enabled CMS

These three discussions share common themes relevant to building modern content platforms:

1. Understanding Your Stack

The silicon demo reminds us that knowing how lower levels work makes you better at higher levels. For CMS platforms:

• Understanding how browsers cache enables better content delivery strategies
• Knowing how databases index helps optimize content queries
• Grasping how CDNs work improves media delivery architecture

2. Signal vs. Noise

The error logging philosophy extends beyond logs to all aspects of system design:

• API Responses: Don't expose internal errors to users; provide actionable error messages
• Monitoring Dashboards: Show metrics that matter, not everything you can measure
• AI Operations: Distinguish between expected model limitations and actual failures

3. Appropriate Abstractions

The self-hosting debate highlights that the right level of abstraction depends on your context:

• Small teams benefit from managed services that hide complexity
• Larger teams with expertise may prefer control and cost optimization
• The best platforms provide both options—simple defaults with deep control when needed

Takeaways for Modern Development

This week's discussions reveal principles that apply across web development:

1. Understand Your Constraints: Whether it's 4k logic gates or mobile bandwidth limits, constraints drive better solutions.

2. Optimize for Signal: In logs, monitoring, and user interfaces, show what matters and hide what doesn't.

3. Choose Appropriate Abstractions: Managed services aren't always best; self-hosting isn't always worth it. Evaluate based on your team and context.

4. Learn the Layers: Understanding what's below your abstraction layer makes you more effective at your current layer.

5. Design for Humans: Whether it's error messages, API responses, or operational procedures, optimize for the humans who will interact with your system.

Conclusion

From silicon demos to database hosting choices, this week's technical discussions remind us that good engineering combines deep understanding with practical judgment. The best platforms—whether for content management, application development, or infrastructure—provide simple interfaces backed by solid foundations.

As you build your next project, consider:

• Are your error logs actionable, or just noisy?
• Do you understand the layer below your current abstraction?
• Are you using managed services because they're better for your context, or just because they're default?
• Do your systems optimize for human understanding and intervention?

These questions lead to better architecture regardless of whether you're building websites, managing content, or designing silicon demos.

Ready to experience a CMS that gets infrastructure philosophy right? Start building with Cosmic and focus on your application instead of operational complexity.