Cloud Migration & Modernization
Transition to the Cloud With Precision, Speed, and Zero Regret
Client Results and Success

Production-Ready Kubernetes Architecture
The platform was designed to support scalable production deployments with minimal resource consumption, enabling faster environment provisioning and operational stability.
3
environments K8s setup
95%
environments K8s setup
35%
savings over managed Kubernetes alternatives
Our Migration Assessment Covers Three Critical Dimensions
- Current state mapping: Server inventory, virtualization layers, networking topology, and storage dependencies
- Cloud fit analysis: Workload classification by migration pattern — rehost, replatform, refactor, retire, or retain
- Dependency chain identification: Inter-service communication, shared databases, and legacy integration points
- Network and connectivity planning: Latency requirements, hybrid connectivity options, and firewall migration considerations

- Application complexity scoring: Coupling levels, technology stack age, containerisation readiness, and refactoring effort estimates
- Database migration assessment: Schema compatibility, replication strategies, cutover window requirements, and managed service suitability
- API and integration mapping: Third-party dependencies, internal service contracts, and breaking change risk analysis
- Modernization prioritization: Sequencing recommendations balancing business value, technical risk, and migration effort

- Team capability assessment: Existing cloud skills, training gaps, and capacity available to support migration execution
- Governance and compliance alignment: Data residency requirements, regulatory constraints, and cloud policy frameworks
- Change management readiness: Stakeholder alignment, communication planning, and rollback decision authority
- Post-migration operating model: Target support structures, cloud operational tooling, and knowledge transfer requirements

Recurring Patterns We Uncover Across FinOps Engagements
12-16 wks
Average timeline extension caused by undiscovered dependencies during migration execution
60-70%
Proportion of application portfolios containing modernisation candidates misclassified as simple lifts
1 in 3
Migrations that encounter significant data migration complications not identified during planning
35%
Average reduction in post-migration costs when sequencing is planned rather than improvised
Migration Outcomes We Are Accountable For Delivering
Migrate Without Fear of What You Missed
Accelerate Cloud Adoption Without Business Disruption
Land in a Cloud Architecture Built to Last
Modernize While You Migrate, Not Years Afterward
Industries Across Which We Deliver Migration and Modernization Impact
Migration Assessments Delivered by Engineers Who Have Moved 1000+ Production Systems to the Cloud
Our Offerings in DevOps Consulting and Services
Our Latest Thinking

The Reality of Healthcare Transformation in the AI Era - Rakshith Gowda
Not every problem deserves an AI solution. Inside AI consulting for healthcare: data quality, clinician trust, and knowing where AI should not go.

Scaling Down Before Scaling Up: Why Bigger Servers Don’t Fix Bad Architecture
This blog explores how inefficient backend architecture can cause performance issues even under low traffic, covering practical ways to reduce database load, API latency, and resource usage before scaling infrastructure.

GeekyAnts Joins the Claude Partner Network to Advance Secure, Production-Ready AI Product Development
GeekyAnts joins the Claude Partner Network as a registered Services Track member, strengthening its work in secure, production-ready AI product engineering.

What ISO Compliance Means When You Work With GeekyAnts
An explainer on GeekyAnts' ISO 9001:2015, ISO/IEC 20000-1:2018 and ISO/IEC 27001:2022 certifications, what each one covers, and how they shape quality, service management and information security across client engagements.

AntFlow AI: An Agentic Development Framework That Turns Software Requirements into Reviewed Code
A look at how AntFlow AI turns software requirements into reviewed code using AI agents, human approval gates, dependency-aware execution, and end-to-end traceability from brief to pull request.

Building Local LLMs Using Dart FFI And llama.cpp: Beyond Wrapper Packages
Build local LLMs in Flutter with Dart FFI and llama.cpp, and see how native bridges, GGUF models, memory management, and token streaming enable private, on-device AI.




