Cloud migration

Boost enterprise agility and speed to market. Increase reliability and stability of applications and data analytics by migrating to the cloud.

Our clients

Manufacturing & CPG

Cloud migration strategy

The cloud migration journey starts with analyzing the current application and data assets portfolio and identifying candidates for initial migration and modernization. 

Cloud migration strategy
ReplatformModernize Lift-and-shiftRetain
What Old applications that work well as-is. Old applications that experience reliability issues in the datacenter. Legacy or modern applications and services. Legacy monolithic applications and services.
Technology Not cloud-friendly or SaaS. Not cloud-friendly. Mixed, cloud-native, and not cloud-friendly. Monolithic, non-cloud-native.
Future plans Limited to no development plans. Limited to no development plans. Major development plans, innovation is required. Major development plans, innovation is required.
Migration plan Leave on-premises to keep using as SaaS, potentially lift-and-shift by VMs with the least priority. Lift-and-shift by VMs, or lift-and-shift with deployment automation modernization. Modernize, migrate to containers and cloud-native technology stack. Replatform to modern microservices architecture and cloud-native technology stack.
We recommend starting with applications or data analytics use cases that would benefit the most from the cloud migration. The best first candidates for migration usually satisfy four key requirements:
Doesn’t have extraordinary security or compliance limitations to avoid the steep cost of the initial investment. Has high fluctuations in performance requirements during a day, week, or year, to take advantage of dynamic scalability. There is a demand for active development and innovation so that it can benefit from increased speed to market. Loosely coupled with the rest of the system to allow for higher latency between the cloud and datacenter interconnect.
During the planning phase, all applications targeted for migration with modernization or replatforming are estimated from the migration effort perspective based on the size, complexity, technology stack, and other non-functional requirements. For example, here are the five t-shirt sizing buckets:
What A modern service or application currently hosted in containers and using a cloud-native technology stack, with a small set of integrations. A modern service or application currently hosted in containers, using a non-cloud native persistence layer (DB). Service or application outside of containers, using non-cloud native persistence layer (DB). A legacy service or application that uses a non-cloud native technology stack and needs heavy modernization or replatforming. A legacy system that uses a non-cloud native technology stack and needs heavy modernization or replatforming.
Plan Move to cloud k8s and test. Replace DB with cloud-native DB, move to k8s, and test. Migrate to containers, replace DB with cloud-native DB, deploy in the cloud, and test. Replatform or migrate to a modern technology stack and k8s, replace DB with cloud-native DB, deploy in the cloud, and test. Analyze and decompose into XS-L applications.
Timeline 2 weeks 4 weeks 8 weeks 12 weeks
After the migration strategy and plan are created, we outline five major areas of change that companies have to go through to fully realize the benefits of the cloud.
Adjust roles and responsibilities of the IT team.
Setup regions, projects, networking, security.
Setup microservices platform for application development.
Choose application technology stack and guidelines.
Setup continuous delivery platform and establish the process.
While some activities, such as infrastructure and platform setup, can be performed at the beginning of the migration process, others such as changing organization structure, roles, culture, and skills, can take much longer. While working with clients on cloud migration, we lead by example and help gradually change the culture, establish DevOps and SRE processes, and acquire the right skills.
We provide a set of accelerators, frameworks, and libraries to increase companies’ speed to market so they can get to the cloud faster.
Microservices platform
Pre-integrated microservices platform based on Kubernetes, Istio, and continuous integration / continuous delivery tooling.
Modular pipeline library
A set of extensions for Jenkins to enable quick creation of CICD pipelines on demand for application teams from predefined components and modules.
Test automation toolkit
Automation tools covering end-to-end testing, including unit testing, API-level functional testing, performance testing, web UI testing, mobile app testing, and wearable devices testing.
Test data management
The environment-agnostic framework enables uniform access to simulated and real product-like data.
Analytical data platform
A pre-integrated cloud-native analytics platform that enables DataOps and MLOps methodologies and supports an end-to-end data lifecycle.
Data quality
Increase trust in data by monitoring production data flows and enforcing quality with pre-defined business rules, comparison with system of records, or anomaly detection.
Anomaly detection
Unsupervised and supervised deep-learning-based anomaly detection platform that works on monitoring and logging data from test and production environments.
Continuous Delivery Blueprint
Continuous Delivery Blueprint
This book is a comprehensive guide to building a robust and efficient change management process at scale.


We bring more than 10 years of experience in migrating Fortune-1000 enterprises from on-premise environments to the cloud while modernizing applications from legacy monoliths to microservices architectures. We achieved a 10x speed to market and efficiency increase by implementing open-source-based cloud-native technology.

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