Cloud migration

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

speed to market boost
Fortune-1000 implementations
of services
of data
Boost speed to market by 10x

Boost speed to market by 10x

The best way to reap the full benefits of the cloud infrastructure and technology stack is to modernize applications, deployment, and change management processes during the migration. Splitting the legacy monoliths to microservices, moving to containers, and implementing autonomous application best practices helps boost speed to market by 10x, while increasing enterprise agility and minimizing costs.

Increase efficiency and reliability

Increase efficiency and reliability

Modernization may be a long term strategy but for some companies migration to the cloud should be done fast to retire a datacenter or increase reliability and scalability. For legacy applications that don’t require active development, investment in modernization won’t pay off even in the long run. In these cases, a lift-and-shift strategy can be beneficial, or serve as a good starting point in the cloud migration process.

Increase speed to insights

Increase speed to insights

On-premise data lakes and EDWs are becoming a thing of the past. They come with high maintenance costs and stability issues, coupled with lack of scalability and limited technology stack options for DataOps and MLOps. Migrating on-premise data processing to a cloud based solution reduces total cost of ownership, increases data quality and accessibility, and re-focuses company resources on building differentiating value.

Innovate with AI

Innovate with AI

Demand for AI-powered innovation often triggers cloud adoption for advanced analytics use cases. The ease of provisioning infrastructure and AI platforms, scaling model training, and establishing proper MLOps processes makes cloud the perfect choice for AI. DataOps and MLOps help further increase the quality of data pipelines and help data scientists consistently and repeatedly turn data into insights.

Optimize cloud costs

Optimize cloud costs

After migrating to the cloud, enterprises often discover they’re now facing increased infrastructure costs. But by modernizing applications to take advantage of containers and auto-scaling, implementing lightweight continuous delivery, establishing proper cloud account structure, and implementing cost monitoring, it’s possible to achieve ongoing cost efficiency gains.

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
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. What
Not cloud-friendly or SaaS. Not cloud-friendly. Mixed, cloud-native, and not cloud-friendly. Monolithic, non-cloud-native. Technology
Limited to no development plans. Limited to no development plans. Major development plans, innovation is required. Major development plans, innovation is required. Future plans
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. Migration plan
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:
A legacy system that uses a non-cloud native technology stack and needs heavy modernization or replatforming. A legacy service or application that uses a non-cloud native technology stack and needs heavy modernization or replatforming. Service or application outside of containers, using non-cloud native persistence layer (DB). A modern service or application currently hosted in containers, using a non-cloud native persistence layer (DB). A modern service or application currently hosted in containers and using a cloud-native technology stack, with a small set of integrations. What
Analyze and decompose into XS-L applications. Replatform or migrate to a modern technology stack and k8s, replace DB with cloud-native DB, deploy in the cloud, and test. Migrate to containers, replace DB with cloud-native DB, deploy in the cloud, and test. Replace DB with cloud-native DB, move to k8s, and test. Move to cloud k8s and test. Plan
12 weeks 8 weeks 4 weeks 2 weeks Timeline
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.

We provide flexible engagement options to plan and execute cloud migration at the enterprise scale. While keeping the focus on application modernization, advanced analytics, AI, DevOps, and MLOps, we help companies move quickly by providing fast lift-and-shift services followed by deep modernization. Clients take advantage of our accelerators to increase their speed to market and reduce overall risk. Contact us today to start with a workshop, discovery, or PoC.


If you want to move to the cloud, but aren’t sure where to start, we recommend a 2 to 3 week discovery phase where we can take a  deeper look at the current application and analytics stack, design your solution, and build out the optimum roadmap.


If you have already identified a specific use case for cloud migration, we can start off with a 4 to 8 week proof-of-concept project to deliver tangible results for your company.


We offer free half-day workshops with our top experts in cloud, microservices, data, and DevOps to discuss your cloud migration strategy, opportunities, and industry best practices.


We offer free demos of our accelerators. As a part of a demo, we will share our point of view on the most effective and efficient cloud migration strategies and discuss case studies from Fortune-1000 clients.