Hybrid development in enterprise: balancing custom code and low-code
How to combine the flexibility of custom development with the speed of low-code while maintaining engineering discipline, version control, and robust system architecture.
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58 publications
How to combine the flexibility of custom development with the speed of low-code while maintaining engineering discipline, version control, and robust system architecture.
How to protect corporate LLM integrations from data leaks and new attack vectors using NIST AI RMF, MITRE ATT&CK frameworks, and Security by Design architecture.
How to balance technical cyberattack containment with strict compliance reporting requirements during the critical first 24 hours after threat detection.
We analyze common pitfalls in implementing monitoring tools and certifications without making real changes to daily security team processes.
A practical approach to overcoming SOC alert fatigue through MITRE ATT&CK mapping, SOAR automation, and NIST CSF 2.0 business prioritization.
How to protect legacy infrastructure from unauthorized access and lateral movement without major code refactoring using Identity-Aware Proxy and microsegmentation.
Combining NIS2 directives, ISO/IEC 27001 processes, and KSZI requirements without redundant workflows. A practical approach to security architecture.
A practical analysis of architectural patterns for connecting legacy systems to modern ecosystems: how to avoid point-to-point chaos and why RPA is only a temporary solution.
The success of AI initiatives depends on data lineage transparency and Data Governance maturity. Learn how to avoid poor data quality traps and prepare enterprise IT architecture for AI scaling.
How to transition from fragile point-to-point connections to a managed integration layer using API gateways and schema registries to ensure enterprise system stability.
Comparing Kafka and RabbitMQ for building reliable event-driven architectures. Learn how to avoid integration issues and ensure data integrity.
The transition to decentralized architectures and AI integration has revealed a critical bottleneck: the lack of clear data ownership undermines the reliability of enterprise systems.