IT Consulting and Technical Audits

Good technology decisions save months of work. Bad ones haunt you for years. An independent consultant brings a fresh perspective on your code, architecture, and processes, spotting problems and blind spots that internal teams naturally miss. Having worked across dozens of projects, I find issues faster and know what actually works in practice.

I cover the full range: security and performance audits, code review, technology selection, and architecture planning for new projects. I work with both engineering teams and business stakeholders, turning technical complexity into clear business language.

Technical audits - what we review

What we actually look at

A technical audit digs into your application's code, architecture, security, and performance. The goal is simple: find problems before they get expensive.

→ Code Audit

• Code quality and readability
• Adherence to standards and best practices
• Technical debt and its impact
• Testing and test coverage

→ Security Audit

• Application vulnerabilities (OWASP Top 10)
• API and authentication security
• Personal data protection (GDPR)
• Encryption and secrets management

→ Performance Audit

• Bottlenecks and slow queries
• Database optimization
• Caching and caching strategies
• Load testing and scalability

→ Infrastructure Audit

• Server and cloud configuration
• CI/CD and deployment processes
• Monitoring and alerts
• Backup and disaster recovery
• Azure cost optimization

After completing the audit, you receive a detailed report with prioritized issues and concrete recommendations for solutions. The report also includes cost and time estimates for implementing changes, allowing you to plan next steps.

Architecture selection for your project

Architecture decisions are hard to undo. Pick wrong, and you'll spend years fighting scalability problems, slow feature development, or spiraling maintenance costs. I've written more about this in my article on microservices vs monolith in 2025.

How do we choose the right architecture?

Business requirements analysis

We start by understanding your business goals, expected traffic, budget, and timeline. There is no universal architecture. Every project needs its own approach.

Team competency assessment

The best architecture is one your team can actually build and maintain. We look at existing skills and figure out what training gaps need filling.

Technology and pattern selection

We recommend what has worked in practice: monoliths, microservices, serverless, event-driven architecture. Every pattern has trade-offs, and we match them to your specific situation.

Planning for growth

Your architecture needs room to evolve. We plan for realistic growth scenarios and business pivots so you avoid expensive rewrites down the road.

Common architectural dilemmas

Monolith vs Microservices: Start with a monolith if you're at an early stage. Microservices mean greater complexity and costs - they're worth reaching for only when justified by scale.

SQL vs NoSQL: The choice depends on data structure and requirements. Relational databases (PostgreSQL, SQL Server) are a safe choice for most projects. NoSQL works well at large scale and with flexible schemas.

Cloud vs On-premise: Cloud offers flexibility and scalability but can be more expensive with high traffic. On-premise gives more control but requires investment and an operations team.

IT department support

Not every company has architects or senior engineers covering every technology. I offer flexible IT department support, from short consultations and code review to long-term collaboration on important projects. Common needs include legacy system modernization or .NET application migration.

For startups and small companies

✓Help choosing tech stack for MVP
✓Verification of solutions proposed by agencies
✓Technical due diligence before investment
✓Recruiting first developers - assessment help

For medium and large companies

✓Support in designing new systems
✓Code review for critical features
✓Process optimization and CI/CD pipelines
✓Team training - best practices and new technologies

"A few hours of consultation can save weeks of wrong decisions and expensive fixes. Teams get tunnel vision on their own code. An outsider catches what they miss."

Code review and optimization

Code review goes beyond bug hunting. It is a chance for the team to learn, share knowledge, and raise quality standards together. I analyze code for readability, performance, security, and whether it follows established best practices.

What do I focus on during code review?

Code quality and readability

Code gets written once but read dozens of times. I check whether it is understandable, well-named, and consistent with project conventions.

• Variable, function, and class naming
• Code structure and organization
• Comments and documentation

Design patterns and SOLID

I check whether the code uses appropriate design patterns and follows SOLID principles, making it easier to extend and test.

Security and vulnerabilities

I identify potential security gaps: SQL injection, XSS, CSRF, unsecured APIs, personal data leaks.

Performance and optimization

I look for inefficient queries, N+1 queries, unnecessary memory allocations, missing database indexes.

Tests and test coverage

I check whether critical functions are covered by unit and integration tests, and whether tests are meaningful and valuable.

Feedback comes as detailed code comments with concrete improvement suggestions and documentation references. The point is never to criticize, but to help the team grow.

Case study: e-commerce system audit and optimization

The problem

A client came to me with an e-commerce performance problem. Their site took 8-12 seconds to load, which meant a high bounce rate and a 40% drop in conversion.

What we did

1. Database Audit

Identified missing indexes on frequently used columns, causing full table scans on every query. Added 8 key indexes.

2. Query Optimization

Refactored queries eliminating N+1 query problems. Applied eager loading and join optimization, reducing queries from 200+ to 15 per page.

3. Caching Implementation

Implemented Redis for catalog data and user sessions. Cache-aside strategy for products and categories with 1-hour TTL.

4. Frontend Optimization

Image lazy loading, CSS/JS minification, CDN implementation for static assets, Gzip/Brotli compression.

Results

85%

Load time reduction

(from 10s to 1.5s)

93%

Fewer database queries

(from 200+ to 15)

+35%

Conversion increase

(after 2 weeks)

The entire audit and implementation process took 2 weeks. The client saved on server costs (60% load reduction) and significantly improved user experience.

Need Consulting?

Let's talk about your project. I offer a free 30-minute consultation where we'll look at your situation and figure out the best next step.

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