What does migrating to the cloud mean?
As in recent years public cloud services are gaining more in popularity over on-premise solutions, more and more companies are exploring the huge opporutinites that public cloud prodivers such as Google Cloud Platform are offering. Moving to Google Cloud Platform can help you save infrastructure and operational costs, help you focus developing your systems and services and leverage cutting-edge technologies such as machine learning. However, in order to access these benefits you need a migration strategy to make the jump.
On this page you will learn about the main benefits of migrating to Google Cloud Platform, how to migrate and how we can help you achieving that through a case study.
Scalability and flexibility
One of the biggest driving factors for companies to migrate to Google Cloud Platform is the scalability of the resources and flexibility that comes with it. Systems and applications these days have to work with a lot more data and traffic than ever before and downtime caused by traffic spikes can cost companies large sums of money.
Studies show that over 80% of all companies are realizing that on-premise systems are not viable anymore and are using cloud based solutions or are planning to take advantage of cloud in the next few years. Google Cloud Platform™ has an infrastructure that can handle any amount of data, provide hight availability and up/down-scaling within seconds that traditional on-premise systems can never achieve.
Focus on your core business
It is no secret that business are more successful when they focus on their core business. Maintaining an IT infrastructure can be burden that slows down your business development and can potentially cost you time and money.
Google Cloud Platform offers a lot of managed services which let you focus and on your business instead of infrastructure. With build in serverless application building tools, auto-scaling, automatic resource and traffic management you can focus on building your systems or applications functionality and leave the backend up to Google.
Leverage cutting-edge technologies
Migrating to Google Cloud Platform comes with numerous opportunities to make your systems and applications smarter by e.g. leveraging Google's numerous powerful machine learning models that have been trained and perfected using Google-scale data sets and are ready to use out-of-the-box. Implementing such functions can be a key differentitor for you service and give you an edge over competitors as well as improve customer experience.
Are you ready to migrate to the cloud?
If you consider to migrate, first you need to access your current environment and find out if it is how mature it is for migrating to the cloud. The chart (by Google) below is devided into 4 categories and can help you access the readiness of your the system/application that you plan to migrate. Determining the cloud maturity can help you with planning and choosing the right migration method.
How to migrate
Deciding the right migration method is key to not only a successful migration but also for the post-migration operations and performance. There are a lot of things to factor in such as the migration object (e.g. application, data sets, servers, database), portability and flexibility of the object (e.g. legacy) and the goal of the migration (e.g. reduce cost, increase flexibility and scalability) and it is recommended to keep these things in mind when choosing the right migration method. In general there are 3 types of migrations, as shown below.
Lift and shift
In the lift and shift method a source environment is moved to the cloud with minor or no changes. This is ideal if there is no need to make changes to the environment or if changes are not possible or would require a lot of work as it is often the case with legacy systems and applications.
Improve and move
In the improve and move method the source environment is modfied and adjusted to take advantage of the cloud to e.g. improve the system's or application's scalability or availability or to improve performance, features, cost, or user experience.
Rip and replace
In the rip and replace migration method the system/application is decomposed and to a large extend rewritten to make it cloud-native. This is the best way to take full advantage of the cloud and use it to it's full potential. However this also takes the most effort and it is necessary to evaluate the benefit compared to the time and cost it takes.
Powerful Google Cloud services to choose from
Easy migration using VM's
Google Compute Engine let's you easily create highly scalable and VM's and is ideal for quick migrations since you can transfer your applications with little to no changes to a new VM on the cloud, for e.g. legacy systems and applications.
Easily deploy applications
Google Cloud's App Engine is ideal for applications and makes deploying them as easy as possible with just a few lines of shell code. It supports many languages and handles the back-end for you as it is highly scalable and offers many manages services to keep your application running smooth and available.
Easy and powerful container orchestration
Google Cloud supports Kubernetes natively with the Google Kubenetes Engine in Google Cloud Platform. You can easily deploy containized applications and offers many managed functions to keep your clusters up and running. This is ideal for modern applciations e.g. microservices architecture or for applciations that are written in a language that is not supported by App Engine.
Cloud Ace - Case Study
Mantan operates popular high traffic websites in Japan with over 10 million monthly visitors. By successfully migrating two high traffic websites to Google Cloud Platform MANTAN was able to run them in a stable and reliable environment while driving down costs.
We were concerned about migrating data for past articles as both sites had a huge amount of content, however the migration went smoothly
The performance was almost exactly as we predicted. Compared to AWS its instance activation is quicker and there’s no let up in the stability of its performance.
One particularly good factor was Cloud Ace’s technical support during the initial testing stages [...] Also, their correspondence with Google [...] helped things progress smoothly.
True Data provides an ID-POS analysis service (Saas) named "Eagle Eye" for manufacturers that builds a platform for purchasing behavior data and provides support for data analysis and utilization. The service was replaced by using BigQuery and other highly scalable GCP services.
With the help of Cloud Ace, a GCP evangelist, we have been able to provide a stable and well-balanced analysis service by utilizing GCP, especially BigQuery.