TeamWork Version 5.1 Released by @DBmaestro | @DevOpsSummit #DevOps #ContinuousDelivery
New version widens database release automation to provide significantly higher interoperability
Jul. 6, 2016 11:00 AM
DBmaestro has announced the release of TeamWork Version 5.1, which improves its database release automation interoperability to support seamless integration with all sources of database changes, while predicting the success of database deployments and alerting for configuration drift. Additionally, Version 5.1 includes dozens of security upgrades and improvements to integrations with solutions such as Jira, Jenkins and CA Release Automation.
DBmaestro's DevOps for Database solution offers a comprehensive approach to the database development life cycle, providing enterprises the ability to deliver changes faster. DBmaestro has been at the forefront of Continuous Delivery for the Database, with a solution that provides complete database source control, governance, and compliance, and ultimately reduces application downtime caused by database-related human errors by 80%, while speeding up the time to market of database driven business applications tenfold.
DBmaestro V5.1 enhanced interoperability empowers customers to turn any existing change process into a stable, predictable and reliable release automation process. Any update package or database update script can be managed by DBmaestro's release automation solution, and leverage its risk evading smart validators and drift detectors before and after deployments. TeamWork provides support for smart deployments between different environments, labels and user stories, as well as support for rollbacks in case of need.
"With the increased need to improve time to market, budget tightening and tolerances for database downtime approaching zero, companies of all shapes and sizes are ready to make a change when it comes to implementing continuous delivery for the database," said Yaniv Yehuda, DBmaestro's co-founder and CTO. "With our new upgrade, DBmaestro is allowing customers to substantially improve the performance, scalability, reliability and cost-efficiency of their DevOps for database solution."
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