Category: Migration & Transfer Services
Mainframe proprietary storage solutions such as VTLs hold valuable data locked in a platform with complex tools. This can lead to higher compute and storage costs, and make it harder to retain existing employees or train new ones. When mainframe data is stored in a cloud storage service, however, it can be accessed by a rich ecosystem of applications and analytics tools. Model9 enables mainframe customers to backup and archive directly to AWS.
Some Oracle workloads, such as Oracle Real Application Cluster (RAC) or WebLogic application clusters, have specific networking and storage requirements, which can be met with VMware Cloud on AWS. This post details the various considerations and migration options users have for Oracle workloads. Specifically, we examine in-depth how to migrate an Oracle database from an on-premises environment to AWS using AWS Database Migration Service (AWS DMS).
As AWS adoption continues to grow, the need for highly reliable workload migrations at an accelerated pace is paramount. This is particularly true for enterprises turning to AWS to host mission-critical and legacy applications. Organizations need a solution that expedites the migration process, without introducing further risk. TDS TransitionManager with CloudEndure Migration is an AWS solution that accelerates cloud migration projects while reducing risk through automated processes.
Amazon Redshift is a fast, scalable, easy-to-use data warehouse solution built on massively parallel processing (MPP) architecture and columnar storage. SnapLogic is an easy-to-learn data integration tool that allows business analysts and integration specialists to accomplish data ingestion from various sources into Redshift. The SnapLogic Redshift Bulk Load Snap (pre-built connector) is part of the SnapLogic Intelligent Integration Platform and enables loading large volumes of data rapidly into Redshift all at once.
Dynatrace is an AWS migration partner and provides an artificial intelligence-powered platform which delivers full-stack, automated monitoring that goes beyond collecting data. It can help you address challenges in operations, DevOps, cloud migration, and customer experience. In this post, we focus on how Dynatrace shaped their cloud migration and autonomous cloud operations capabilities through their own migration journey from legacy on-premises enterprise application to cloud-native services running on AWS.
Customers that still have business-critical data locked in mainframes want to exploit this data with AWS agile services. Fortunately, Treehouse Software’s tcVISION replicates data in real-time and bi-directionally between mainframes and AWS to allow for these new use cases. Learn about the solution, customer use cases, and explore a practical example of how to replicate data in real-time from DB2 z/OS to Amazon Aurora.
Save on Your AWS Spend with Enterprise Cloud Migration and Infrastructure Management from Turbonomic
Migrating workloads to the cloud and adopting infrastructure management allows businesses to leverage the scalability and rapid innovation of AWS. Turbonomic’s autonomic platform collects usage data from applications and processes it using AI, making full stack aware decisions across available compute, storage, and database resources without user intervention. In this post, learn how a Fortune 500 company achieved migration milestones and reduced their AWS spend by 40 percent using Turbonomic.
Mainframe cold storage based on disks and tapes is typically expensive and rigid. Model9 improves the economics and flexibility by leveraging AWS storage for archival, backup, and recovery of mainframe data. Model9 enables mainframe customers to leverage modern cloud technologies and economics to reduce data recovery risks and improve application availability by providing a software-defined solution for archive, backup, and recovery directly from AWS.
Today’s businesses deal with many different varieties of data, including structured datasets stored in various repositories like a relational databse management system (RDBMS) or enterprise resource planning (ERP); semi-structured datasets like web logs and click-stream datasets; and unstructured datasets like images and videos. AWS provides a secure, scalable, comprehensive, and cost-effective portfolio of services that enable customers to build their data lake in the cloud.
Ippon Technologies has successfully re-written a large mainframe third-party software package to Java Angular Spring Boot microservices. The package supported 130 TPS and 1,800 MIPS, catered to over 5,000 users, and housed more than 5 TB of business-critical data. Ippon helped the customer define the approach and architecture, and then developed the microservices along with the CI/CD pipeline on AWS. Learn about the project’s technical aspects, methodologies, and lessons learned.