by Sue Dunnell.
The days when IT operations only existed to support the back office are over. Today IT is a driver for meeting organizational strategy, revenue and customer satisfaction goals.
New technology certainly plays a role in IT’s increasing importance. Apps can be delivered more quickly with the new tools and processes for DevOps implementation.
Organizations can rapidly scale to meet demand with cloud deployments, automation has accelerated productivity and more personalized and engaging customer experiences can be built by leveraging AI.
But new tools, automation, and other technologies are only one aspect of the force behind the expanding role of IT.
IT began using data to drive efficiency by automating processes and the business insights realized were valuable. This led to more automation and monitoring of process, giving IT the ability to better predict and prevent outages or failures – which led to more data.
As IT environments have become more complex – spanning hosting sites and technology stacks – new tools emerged to track user behavior, monitor multiple sites, and integrate new and legacy systems. In addition to a lot more data, there is a lot more noise, too.
Complexity coupled with a lack of insight and context brings risk. As the amount of data captured across IT continues to increase exponentially, it is becoming more difficult to manage and understand. Relationships are hard to identify and explore and the business contexts are not captured in traditional IT tools.
The good news is that IT can leverage existing tools and get more value out of them. At TDS, we built a platform, TransitionManager, designed to pull in the data from your current tools, visualize relationships of all IT assets across hosting sites, quickly identify business facts such as RTOs, RTOs or compliance requirements, perform queries, and model changes to your environment.
For example, a large healthcare organization got stuck while trying to consolidate a data center and adopt cloud hosting. Their autodiscovery tool showed one application had over 4,200 dependencies – too many to manage and unravel. When the data was pulled into TransitionManager, where it could be filtered, viewed in context, and only application level dependencies were considered, only two connections were found critical to making the move.
Check out TransitionManager today. Sign up for a demo to see how we can help you sift through the noise and bring meaning to your data.
The methodology and tools you choose for your migration journey will directly impact your goals and measure of success. Download our Data Center Migration Survival Guide now to kick off your journey.
Follow these key cloud migration best practices for successful cloud adoption in your organization.
When executing a cloud strategy it takes time to understand how your apps work, identify those most critical to business, which are best fit for the cloud, and which require modernization before migrating. What if you could accelerate this process by automating your toolchain?
We're thrilled to share exciting developments as we continue to enhance your experience with TransitionManager (TM) and empower you to navigate complex IT transformations with speed and efficiency.
TransitionManager’s Dependency Analyzer offers a visual representation of application dependencies, helping IT professionals understand the intricate relationships between various elements within the system and facilitating informed decision making. Users can now seamlessly switch between GoJS and D3 map plotting engines within Dependency Analyzer, offering greater flexibility in visualizing dependencies according to their specific needs.
TransitionManager supports JSON custom fields, providing developers and integrators with increased leverage to harness the platform's flexibility and extensibility as they orchestrate data center migrations and modernizations.