Technology Stack
Proven, battle-tested technologies suited for high-scale production environments. Each technology is selected based on project requirements, not trends.
Orchestration
Kubernetes
Production container orchestration for all major deployments. We design and operate Kubernetes clusters handling thousands of pods with custom auto-scaling, health monitoring, and zero-downtime deployment strategies.
Containerization
Docker
Standard containerization across all projects. Custom base images optimized for security and size, multi-stage builds for production artifacts, and container security scanning integrated into CI pipelines.
Caching & Data Store
Redis
High-performance caching, session management, and real-time data structures. Redis Cluster deployments for distributed workloads requiring sub-millisecond access times and high availability.
Relational Database
MySQL / MariaDB
Primary relational database for transactional workloads. Expertise in replication topologies, query optimization, partitioning strategies, and high-availability configurations for mission-critical systems.
PostgreSQL
Advanced relational database for complex data models. Used in projects requiring advanced indexing, JSON processing, full-text search, and strong consistency guarantees.
Analytical Database
ClickHouse
Columnar analytical database for real-time analytics on large datasets. Deployed for dashboards and reporting systems requiring sub-second query performance across billions of rows.
Event Streaming
Apache Kafka
Distributed event streaming for high-throughput, fault-tolerant data pipelines. Used in event-driven architectures, real-time data integration, and systems requiring exactly-once processing guarantees.
Observability
Prometheus & Grafana
Full observability stack for metrics collection, alerting, and visualization. Custom dashboards for infrastructure and application monitoring across all deployed systems.
Infrastructure as Code
Terraform
Infrastructure provisioning and management across cloud providers. GitOps-based workflows with state management, plan reviews, and compliance scanning.
Backend Framework
Java / Spring Boot
Enterprise-grade backend development for high-throughput services. Used in systems requiring robust concurrency handling, extensive ecosystem integration, and long-term maintainability.
Backend Language
Go
High-performance backend services where low latency and efficient resource usage are critical. Used for infrastructure tooling, API gateways, and data processing services.
Data & Automation
Python
Data pipeline development, ETL orchestration, and automation scripting. Used with Apache Airflow for workflow management and with analytical libraries for data processing.
Technology Selection Philosophy
Our technology choices prioritize production reliability over novelty. We select tools with strong community support, proven track records at scale, and clear operational characteristics.
For each project, we evaluate technologies against specific requirements: expected scale, latency constraints, operational complexity, team expertise, and long-term maintainability. We avoid adopting technologies purely based on market hype.
When existing tools meet requirements, we prefer established solutions. When projects demand custom solutions, we build them with the same rigor applied to production infrastructure.