Slash infrastructure spend by 40-60% while modernizing legacy systems for the cloud era.

Financial services firms operating on legacy on-premises infrastructure face escalating hardware refresh cycles, capacity planning bottlenecks, and mounting operational costs. Aging data center contracts lock organizations into rigid spending with little visibility into actual resource utilization, which typically hovers at just 15-25% of provisioned capacity. Compliance requirements unique to finance add friction to any migration effort, while the lack of cloud-native skills internally stalls transformation initiatives. Without a structured migration and FinOps strategy, organizations risk ballooning cloud bills that exceed their on-premises costs within the first year.
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Hubungi KamiMicrocosmWorks can deliver a phased cloud migration program that pairs a thorough discovery and assessment phase with a hybrid lift-and-shift and refactor execution strategy. We begin with automated infrastructure scanning and dependency mapping to classify every workload by migration disposition—rehost, replatform, refactor, or retire. A dedicated FinOps practice is embedded from day one, establishing cost allocation tags, budgets, alerts, and reserved instance purchasing strategies before a single workload moves. Post-migration, we implement continuous cost governance dashboards and anomaly detection to ensure savings persist over time.
The architecture follows a landing zone model with a multi-account structure that enforces security boundaries, network segmentation, and cost isolation by business unit. A centralized governance account aggregates billing, compliance checks, and audit logs, while workload accounts host migrated applications behind private subnets with controlled egress.
| Layer | Technologies |
|---|---|
| Backend | Python, Go, AWS Lambda, Step Functions |
| AI / ML | Anomaly detection for cost spikes, ML-based rightsizing recommendations |
| Frontend | React, Grafana dashboards, AWS QuickSight |
| Database | Amazon RDS (PostgreSQL), DynamoDB, Redis |
| Infrastructure | Terraform, AWS Control Tower, AWS Organizations, CloudFormation, GitHub Actions |
The engagement follows a four-phase delivery over 12-16 weeks. Weeks 1-3 focus on discovery and assessment, running automated infrastructure scans, dependency mapping, and workload classification across the on-premises estate. Weeks 4-9 execute the core migration factory, moving rehost workloads via AWS MGN while parallel refactoring sprints modernize high-value applications for containers or serverless. Weeks 10-13 establish the FinOps control tower, configuring cost allocation tags, reserved instance strategies, anomaly alerts, and governance dashboards. Weeks 14-16 cover optimization tuning, knowledge transfer, and handoff of runbooks to the internal operations team.
| Metric | Improvement | Detail |
|---|---|---|
| Infrastructure cost | 40-60% reduction | Right-sizing, reserved instances, and elimination of idle resources |
| Deployment velocity | 5x faster | Automated provisioning replaces multi-week hardware procurement cycles |
| Resource utilization | 65-80% average | Dynamic auto-scaling replaces static over-provisioning |
| Disaster recovery RTO | 90% reduction | Cloud-native backup and cross-region replication versus tape-based recovery |
| Compliance audit time | 70% reduction | Automated compliance checks and continuous evidence collection |
Pertahankan data sensitif di lingkungan on-premises sekaligus membuka kelincahan cloud untuk yang lainnya—tanpa mengorbankan kepatuhan.
MicrocosmWorks conducts workload profiling that evaluates each application across six dimensions: compute utilization patterns, data gravity and latency requirements, compliance and data residency constraints, licensing implications (especially for Oracle and SQL Server), team readiness, and total cost of ownership over a 3-5 year horizon. Applications with variable demand patterns, modern architectures, and no data sovereignty restrictions are prioritized for cloud migration, while legacy mainframe workloads or applications with restrictive vendor licensing may be better suited for on-premises optimization or hybrid approaches. This assessment prevents the common mistake of lifting-and-shifting everything to cloud and discovering higher costs than on-premises.
MicrocosmWorks clients typically achieve 25-40% infrastructure cost reduction within the first year of a properly executed cloud migration, with additional 15-25% savings in year two through reserved instance optimization, rightsizing, and architecture modernization. The key word is 'properly executed' — naive lift-and-shift migrations often result in cloud costs exceeding on-premises costs because VM sizing, storage tiers, and network egress are not optimized for cloud pricing models. MicrocosmWorks builds cost optimization into the migration plan from day one rather than treating it as a post-migration cleanup exercise.
MicrocosmWorks evaluates each database for migration feasibility to cloud-native alternatives (Aurora, Cloud SQL, Azure SQL) versus managed lift-and-shift (RDS, Cloud SQL for SQL Server), considering factors like PL/SQL complexity, linked server dependencies, licensing costs, and performance requirements. For Oracle workloads, we analyze whether migrating to PostgreSQL or Aurora PostgreSQL can eliminate expensive Oracle licensing — a decision that depends on the depth of Oracle-specific feature usage like Advanced Queuing, Spatial, or RAC. Database migration including schema conversion, data migration, application query testing, and performance validation typically represents 30-40% of total migration effort at rates of $30-$50/hr.
MicrocosmWorks deploys FinOps platforms (leveraging tools like CloudHealth, Spot.io, or native cloud cost management) with automated rightsizing recommendations, unused resource detection, reserved instance / savings plan coverage analysis, and anomaly alerting that catches cost spikes within hours rather than at end-of-month billing surprise. The system generates weekly optimization recommendations prioritized by savings potential, and can auto-execute approved actions like shutting down non-production environments outside business hours or purchasing reserved capacity when commitment thresholds are met. Ongoing FinOps management typically saves 15-30% on top of initial migration optimization.
MicrocosmWorks typically completes cloud migrations for mid-size estates (50-200 servers) in 4-8 months, broken into assessment (2-4 weeks), architecture design and landing zone build (3-4 weeks), wave-based migration execution (2-5 months depending on complexity), and optimization/cutover (2-3 weeks). The timeline depends heavily on application interdependencies, database complexity, compliance requirements, and change management processes rather than raw server count. MicrocosmWorks uses wave-based migration planning that groups related applications together to minimize cutover risk and business disruption, with each wave typically migrating 10-30 workloads.