Migrating Data to the Cloud | Cloud Migration

10x

speed to market boost

10+

Fortune-1000 implementations

1000s

of services

10PB

of data

APPLICATION MODERNIZATION

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.

LIFT-AND-SHIFT

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.

DATA ANALYTICS MIGRATION

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.

ENTERPRISE AI AND MLOps

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.

CONTINUOUS EFFICIENCY

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.

Our clients

Retail

Hi-tech

Manufacturing

Finance

Healthcare

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

	Replatform	Modernize	Lift-and-shift	Retain
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.

Organization

Adjust roles and responsibilities of the IT team.

Infrastructure

Setup regions, projects, networking, security.

Platform

Setup microservices platform for application development.

Technologies

Choose application technology stack and guidelines.

CICD

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.

Book

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.

Finance and insurance

Digital transformation is accelerating in financial services companies, requiring higher enterprise agility. While security is still a concern for many, cloud has become industry accepted and the new norm. Grid Dynamics has experience working with Fortune-1000 US banks and financial services companies to move applications, data, and AI to the cloud, boosting efficiency and speed to market.

Retail and brands

Retailers and brands have to constantly innovate to keep the best customer experience, efficient fulfillment, and accurate analytics. Grid Dynamics helped Fortune-1000 US retailers move omnichannel commerce, fulfillment, and data analytics to the cloud, while modernizing applications, moving to microservices, and adopting DevOps best practices.

Technology and media

Digital-native companies are often starting development in the cloud. They need high efficiency and the ability to scale quickly. Grid Dynamics’ accelerators, such as the microservices platform, test data management, analytical data platform, and AI solutions can help achieve 10x scale, speed to market, and innovation to stay ahead of the competition.

In this article, we describe the benefits of the microservices platform and its key architecture and design details. We also review the capabilities of the platform, and provide a glimpse into early versions of the Grid Dynamics platform accelerator.

Why you need a microservices management platform and how to build it

After completing the initial migration to the cloud, enterprises often discover they’re facing increased infrastructure costs. In this article, we discuss how to overcome this and provide five actionable strategies to reduce cloud costs if they begin to creep higher.

5 strategies to reduce cloud cost

In this article, we review the industry journey from basic data lakes to modern analytical data platforms. We also explore what capabilities data-driven enterprises need to increase the productivity of their teams.

From data lake to analytical data platform

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.

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Why you need a microservices management platform and how to build it

5 strategies to reduce cloud cost

From data lake to analytical data platform

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