Cloud Database Optimization, Migration & Modernization
We help technology leaders determine whether their current cloud database architecture is the most economical and operationally appropriate way to run their workloads — and help them optimize in place, migrate engines, or modernize hosting across PostgreSQL, MySQL, Oracle, Microsoft SQL Server, and Neo4j.
Initial Engagement: Estate Audit & Economics
Cloud Database Cost Assessment
A thorough, evidence-based audit of your cloud database estate across Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure to identify compute overprovisioning, storage bloat, unmetered IOPS, idle replicas, and expensive licensing overhead.
What We Analyze Across Engines:
- • Compute and memory utilization curves across primary and standby nodes
- • Storage allocations and provisioned Input/Output Operations Per Second (IOPS)
- • Non-production storage duplication and branching feasibility
- • Commercial per-core licensing overhead (Oracle Database & Microsoft SQL Server)
- • Active read replica sizing and idle standby capacity
- • Reserved instances, savings plans, and committed-use discount coverage
Key Deliverables Produced:
- • Current-state Total Cost of Ownership (TCO) financial model
- • In-place rightsizing opportunities without platform disruption
- • Engine migration & hosting modernization feasibility analysis
- • Architecture alternatives with explicit trade-offs and operational prerequisites
- • Prioritized step-by-step engineering roadmap with risk mitigation plans
Implementation & Execution Services
Targeted engineering engagements designed to implement the recommendations identified during your assessment.
In-Place Database Optimization
Maximize the efficiency of your existing Google Cloud SQL, Amazon RDS, Aurora, or Azure database instances without the operational disruption or risk of migrating engines.
Optimization Scope:
- • Rightsizing compute instances to align with empirical baseline utilization
- • Trimming overprovisioned IOPS and auto-expand storage volumes
- • Scheduling non-production and development database instances
- • Structuring committed-use discounts and reserved instance portfolios
Key Benefits:
- • Rapid financial impact without application architectural changes
- • Zero database migration risk or schema alterations
- • Preserves familiar managed operational workflows
Platform Modernization on Kubernetes
Deploy production-proven PostgreSQL and MySQL operators on Kubernetes, and assess modern decoupled architectures (like Neon for PostgreSQL) to support rapid development branching and infrastructure cost control.
Engineering Capabilities:
- • Production deployments of CloudNativePG and StackGres operators on GKE, EKS, and AKS
- • Declarative Infrastructure-as-Code (Terraform) and GitOps cluster management
- • Neon serverless Copy-on-Write branching for non-production development environments
- • Direct cloud object storage backup integration (S3, GCS, Azure Blob)
Skill Prerequisites & Context:
- • Recommended primarily for teams with existing in-house Kubernetes maturity
- • Substantially reduces infrastructure-level markups over managed database instances
- • Requires internal responsibility for Day-2 storage class and operator maintenance
Database Engine & Platform Migration
Execute risk-mitigated migrations from proprietary commercial databases (Oracle, SQL Server) to modern PostgreSQL, or between cloud hosting environments, with minimal cutover downtime.
Migration Scope:
- • Oracle Database → PostgreSQL / Aurora migration planning and execution
- • Microsoft SQL Server → PostgreSQL schema and stored procedure translation
- • MySQL → Aurora / PostgreSQL estate consolidation
- • Managed cloud to containerized database platform transitions
Verification & Safety:
- • Pre-migration compatibility assessment and workload profiling
- • Cutover rehearsals, data reconciliation, and automated validation tests
- • Explicit rollback procedures to eliminate operational risk
Reliability, Performance & Advisory Services
Ongoing technical advisory and deep engineering support for critical database infrastructure.
Reliability & Disaster Recovery
Validate Recovery Point Objectives (RPO) and Recovery Time Objectives (RTO), verify Point-in-Time Recovery (PITR), automate Write-Ahead Log (WAL) archiving, and test failover runbooks.
- • Backup verification & automated restore drill pipelines
- • Cross-region replication and split-brain prevention
- • High-availability architecture reviews
Performance & Capacity Tuning
Diagnose query bottlenecks, connection pool saturation (PgBouncer, ProxySQL), buffer allocation, lock contention, and storage latency before resorting to costly instance upgrades.
- • Execution plan analysis and index design
- • Buffer pool tuning (PostgreSQL, MySQL, Neo4j pagecache)
- • Autovacuum tuning and bloat remediation
Cloud Data Platform Advisory
Strategic advisory across Cloud Data Operations (DataOps), infrastructure automation with Terraform, cloud observability (Prometheus / Grafana), and long-term data platform governance.
- • Declarative database infrastructure via Terraform
- • Telemetry and alert design with Prometheus & Grafana
- • FinOps database cost tracking and estate governance
How We Engage With Your Team
Engagements are designed to be low-friction, technically rigorous, and non-disruptive to active development and production workloads.
Discovery & Scoping
Initial technical alignment to understand your cloud environment, database engines, operational constraints, and commercial concerns.
Telemetry & Estate Audit
Read-only inspection of performance metrics, query profiles, storage configurations, replication architectures, and billing line items.
Economics & Recommendations
Delivery of the Total Cost of Ownership model, architecture recommendations, risk mitigation assessments, and implementation roadmap.
Partnered Execution
Collaborative implementation alongside your internal engineering team to execute optimization, rightsizing, or migration milestones.