Modern Services for Connected, Agile Enterprises

We deconstruct legacy monoliths into modern microservices — with CI/CD pipelines, built-in observability, and fault tolerance for continuous delivery.

Microservices Architecture, re-imagined at scale

In today’s digital era, the difference between being reactive and being proactive comes down to architecture. With fragmented legacy systems, slow-release cycles and brittle dependencies, many enterprises find themselves locked into monolithic models that force slower time-to-market and block innovation.

At Techment, we transform legacy applications into service-led ecosystems, built on independent, deployable services — enabling you to deliver business value faster, with confidence and scale.
 

Our Microservices Architecture service ensures your enterprise moves from tightly-coupled codebases to lean, autonomous services with full observability, continuous integration/delivery and fault-resilient operations. 

Transform your application backbone into a flexible growth engine.

The Challenge 

Legacy systems may still “work”, but they are often invisible brakes on innovation, cost and resilience
Enterprises often struggle with
  • Large monolithic applications that hamper scalability and agility. 
  • Slow manual release cycles with high operational overhead.
  • Tightly coupled modules and shared databases inhibit independent deployments. 
  • Poor visibility into service health, leading to cascading failures and downtime. 
  • Security, compliance, and governance gaps in hybrid-cloud or multi-cloud deployments. 
  • Difficulty in evolving architecture without disruption or risk. 
A modern microservices architecture ensures
  • Domain-aligned, loosely coupled services that enable independent development, deployment, and scaling. 
  • Rapid time-to-market, continuous delivery, and agile experimentation. 
  • Built-in resilience: failure of containment, graceful degradation and fault diversity. 
  • Technology-agnostic service stacks, containerization, orchestration and API-first design. 
  • Observability, monitoring, and governance baked into the service lifecycle. 

A proven 5-step Microservices Engineering Framework

Discovery & Assessment

We conduct a deep audit of existing applications, code-modules, data dependencies, runtimes, workflows and release pipelines. From this, we define a blueprint that highlights service candidates, domain boundaries, bottlenecks, and risk-profiles. 

Service Definition & Architecture Design

We design a target microservices architecture: define bounded-contexts, service boundaries, APIs, data ownership, event streams, CI/CD pipelines and run-time observability. We align this with your business outcomes, release cadence and change-resilience. 

Pilot & Modular Build-out

We develop and deploy a subset of services as a live pilot: containerised services, API gateways, service-mesh or orchestration, monitoring and rollback safety. This phase validates real-world readiness, integration and team readiness. 

Full-Scale Roll-Out

We migrate additional modules from monolith to microservices, deploy across environments (cloud, hybrid, on-premises) with automated pipelines, versioning, service discovery and governance guardrails. We ensure minimal business disruption via dual-run, phased cut-over and fallback plans. 

Post-Launch Enablement & Evolution

We embed full observability, performance tracking, fault-tolerance, cost-optimisation and ongoing evolution paths (adding new services, scaling up, refactoring). This ensures your microservices backbone continues to support innovation and future business models. 

 

Engineered to accelerate delivery, reduce architectural risk and unlock business agility. 

Our Expertise in Data Migration

Category
Capabilities
Architecture & Strategy

Service-boundary definition, API-first design, domain-driven architecture, team topology alignment 

Service Development & Platform Engineering

Microservices build-out, containerization (Docker/Kubernetes), service mesh / API Gateway, CI/CD pipelines 

Data & Workflow Decoupling

Decentralized data ownership, event-driven messaging (Kafka/RabbitMQ), orchestration across services 

Observability & Reliability Engineering

Logging/tracing (OpenTelemetry), monitoring dashboards, fault-isolation patterns (circuit breaker, bulkhead)

Cloud-Native & Hybrid Ecosystem

Multi-cloud/hybrid deployments, service-scaling, infrastructure as code, serverless as needed

Assurance & Continuous Evolution

DevSecOps, automated testing, service versioning, component lifecycle management, runtime governance 

Why Choose us

Service-First Mindset

We don’t just migrate code — we build services that enable agility, scalability and business alignment.

Independent of Vendor Lock-in

While we’re fluent in industry platforms, our approach remains tool-agnostic and business-driven.

Enterprise Governance at Scale

Proven frameworks, architectural governance, compliance strategies and QA at enterprise scale. 

Automation & Observability Built-in

We embed pipelines, monitoring and telemetry from day one — not as an afterthought. 

Industry-Focused

Deep experience across regulated sectors (finance, healthcare, manufacturing) where reliability and change-governance matter most. 

Stay Ahead with Insights

Comprehensive solutions to accelerate your digital transformation journey

Blogs

Guide to Microsoft Fabric Data Quality and Purview Governance
Microsoft Fabric Data Quality & Purview Governance Guide 

Introduction: Data Quality Has Become a Board-Level Priority  Data quality has always mattered — but as we move towards 2026 and beyond, it has become a board-level concern for organizations scaling analytics, automation, and AI. Enterprises are no longer asking “Do we have enough data?” but rather:  Research supports this shift. IDC’s 2024 analysis revealed that poor-quality data costs enterprises an average of […]

Webinar

The Future of Decision Intelligence: AI Copilots for Business Leaders 
Transform data into strategic advantage with AI-powered decision intelligence

Whitepaper

Transforming Data Quality Through AI: The Future of Automated Data Preparation 
This paper unpacks the massive shift organizations are experiencing as AI moves from experimentation to everyday operations. The biggest bottleneck isn’t the models — it’s the data powering them.

Frequently Asked Questions

Q1. Will migrating to microservices disrupt business operations?

No — we adopt phased roll-out, dual-run strategies and safe fallback mechanisms to ensure minimal disruption and business continuity. 

We embed observability, telemetry, automated regression testing, version-management and runtime fault-isolation patterns to ensure service integrity and continuous improvement. 

We support all major public clouds (AWS, Azure, GCP), hybrid/on-premises environments, container orchestration (Kubernetes, ECS, AKS), service-mesh technologies (Istio, Linkerd), runtime observability (Prometheus, OpenTelemetry), and various microservices stacks (Java, .NET, Go, Node). Our architecture is designed to be tool-agnostic and adaptable. 

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