Platform Modernization on Kubernetes
Reduce recurring cloud infrastructure markups, improve operational control, and increase architectural flexibility by deploying best-in-class, production-ready open-source Kubernetes operators (PostgreSQL, Trino) when in-house platform familiarity exists.
Production-Proven Enterprise Database Architectures
Operator-backed Kubernetes database deployments deliver the high availability, automated failover, and resilience of managed cloud platforms while preserving infrastructure-level cost control.
Operator-Based Cluster Management
Leverage best-in-class, production-ready open-source Kubernetes operators tailored to your workload for declarative cluster provisioning, automated leader election, self-healing, and failover.
Declarative Infrastructure-as-Code
Codify database clusters, persistent volume storage classes, network isolation policies, and IAM permissions using Terraform and GitOps practices for consistent multi-environment deployments.
Automated Upgrades & Patching
Implement minor version rolling update automation designed to minimize downtime and validated major version upgrade automation across development, staging, and production estates.
High Availability & Disaster Recovery
Architect multi-zone high availability with continuous Write-Ahead Log (WAL) archiving and verifiable Point-in-Time Recovery (PITR) to cloud object storage (Amazon S3, Google Cloud Storage, or Azure Blob).
Database Observability & Operational Intelligence
Informed by nearly 30 years of production database operations and management experience, we design monitoring around actual database behavior, rather than simply infrastructure availability. We instrument query latency, transaction throughput, lock contention, replication lag, connection pressure, cache efficiency, and IOPS profiles with Prometheus, Grafana, and workload-specific alerting thresholds.
Extension & Ecosystem Flexibility
Unlock greater extension flexibility to run advanced open-source extensions (such as pgvector, PostGIS, and timescaledb) without cloud provider catalog restrictions.
Analytical Warehouse Modernization (Trino)
Migrate high-cost data warehouse workloads from Snowflake or Google BigQuery to open-source Trino operators running on Kubernetes over open lakehouse formats (such as Apache Iceberg on Amazon S3 or Google Cloud Storage), easily saving 50%+ depending on query usage and concurrency.
Optimizing Development & Testing Environments
In many organizations, non-production environments consume as much cloud spend as production due to full storage volume duplication across staging, QA, and feature testing.
Full Disk Storage Duplication
- • Outside specialized features (like Aurora fast cloning or Cloud SQL Instant Snapshots), each staging environment requires full volume allocation.
- • Standard snapshot restorations involve lengthy creation times and separate billing line items.
- • Full storage costs accumulate even when testing environments sit idle overnight.
- • Manual sanitization and synchronization scripts create recurring operational overhead.
Lower-Environment Storage Optimization
- • Where supported by the selected storage architecture, Copy-on-Write cloning can reduce lower-environment storage duplication and provisioning time.
- • Lower environments share baseline data pages and store only delta changes made during testing.
- • Ephemeral development, QA, and UAT databases can be spun up in seconds for validation.
- • Reduces redundant multi-terabyte disk allocations and cuts idle non-production spend.
Managed Cloud Database Services vs Kubernetes Operators
Understanding the real trade-offs between proprietary cloud managed services and open-source operator-backed Kubernetes architectures.
| Evaluation Dimension | Managed Cloud Database (Cloud SQL / RDS / Aurora) | Kubernetes Database Operators |
|---|---|---|
| Pricing & Markup | Significant pricing markup on compute, RAM, and IOPS, plus standby instance overhead and billable cross-zone, cross-region, and client data transfer where applicable. | Direct compute and persistent storage costs without managed database markups; standard cloud network pricing applies. |
| Team Prerequisite | Standard cloud infrastructure skills; minimal database admin effort. | Standard cloud engineering skills with some in-house Kubernetes familiarity. |
| Non-Production Branching | Often requires full-volume snapshot restores with separate storage allocations, though Amazon Aurora and Google Cloud SQL (via Instant Snapshots) offer fast cloning in supported configurations. | Where supported by the selected storage architecture, Copy-on-Write cloning can reduce lower-environment storage duplication and provisioning time. |
| Vendor Portability | Tied to proprietary cloud APIs, snapshot formats, and vendor configuration constraints. | Improved portability across Kubernetes environments compared with proprietary managed services. |
| Extension Freedom | Restricted to cloud vendor approved extensions and specific version combinations. | Greater extension flexibility (pgvector, PostGIS, pg_partman, timescaledb) without cloud vendor catalog constraints. |
| Operational Automation | Cloud provider automates failover and backups at a steep 50% to 150% compute surcharge. | Kubernetes operators automate failover, backups, and healing natively at standard cloud compute pricing. |
Operator & Tooling Technologies
We select and integrate proven tools based on your specific infrastructure environment.