Our consultants can help you accelerate your journey towards running Mainframe workloads on Google Cloud Platform. Work hand in hand with us where we will guide your team on best practices for a successful implementation. We enable you to gain first-hand experience with the gamut of cloud solutions—including data management, security, application modernization, and analytics, machine learning, infrastructure, and much more.
Benefits of Google Cloud
- Easy data access from any location and execution of various operations due to big infrastructure
- Google Cloud’s large network allows users to migrate their machines also known as “Live Migration”
- Private network offers maximum time and efficiency to the customers
- Network via fiber-optics makes it highly spreadable and bearable for any amount of traffic
- Committed to constant development in the infrastructure to meet their customer’s requirements
- All data is encrypted and strong network of ISPs help Google secure their network
- In-built redundant backups which ensure reliability and durability
- Better pricing availability as compared to other technologies
Google Cloud provides a varied number of services to ensure smooth performance of your services and keep your data safe and protected.
Data Handling and Storage
Google Cloud has made it very convenient for the companies to manage their data and transfer it from cloud services in a seamless manner. Services like BigQuery, Dataproc, Datalab are well suited for big data analysis and data manipulation. Cloud SQL, Cloud Bigtable and Cloud Datastore are used for data and database storage.
Networking and Security
Google Cloud has a number of networking products which are used to provide multiple networking options along with Google Storage. Some of these include Content Delivery Network, Google Cloud Loading Balance and Google Cloud Interconnect. In order to ensure identity safety and security, there are services provided by Google Cloud like Cloud Resource Manager, Cloud IAM and Cloud Security Scanner.
Cloud AI allows you to work on Machine learning models based on mainstream frameworks. It a managed service that enables developers to provide their data which results in them obtaining access to quality trained models by Google’s transfer learning. While data labeling helps you in managing all your labeled data in one place, NAS is used to generate, evaluate and train model architectures for customer applications.