Support tickets can get bounced around between Level 1, 2, and 3 teams for weeks before enough is known about the problem to identify the root cause. Rocana Ops helps eliminate ‘Support ticket volleyball’ by enabling Level 1 operators to quickly drill down to the likely source of a problem on their own, even if it spans technology stacks and teams. By radically reducing the skill and time required to perform root cause analysis, technologists can resolve problems faster than ever before.
Enterprise applications rely on complex webs of subsystems and infrastructure components. When issues occur in any of the parts, you need to know about it fast – especially if the issue puts the entire system at risk. Rocana Ops’ built-in anomaly detection helps you stay ahead of potential problems by automatically identifying abnormal behaviors anywhere in your system, including parts you might not otherwise monitor. The result is increased application stability, and far fewer missed SLAs.
APM data enables you understand and improve end user experiences. On a busy ecommerce site, that can mean millions of dollars in additional revenue. Rocana Ops helps you to get the most from your APM investment by allowing you to economically retain all your APM data for as long as needed. Analyze APM data from a year ago as easily as data from yesterday. Quickly identify performance bottlenecks by visually correlating APM data with operational data from the underlying application subsystems.
- Rocana has built a platform that can handle very large volumes of operations data, a capability that sets it apart from competitors and should appeal to large enterprises… In delivering automation capabilities relatively early compared with rivals, Rocana can lead the way in demonstrating how automation can improve performance for businesses.
- Today’s CIOs and IT leaders are increasingly responsible for driving business outcomes in a world of ever increasing data volumes and data sources. Rocana was selected for the Ventana Research Technology Innovation Award for its innovative approach to achieve total visibility across IT and business data, using big data and advanced analytics to help IT teams identify anomalies, improve customer experience, and increase security and compliance.
- Companies that adopt modern infrastructures are learning that their IT operations generate huge amounts of potentially valuable data. But many traditional IT tools aren’t able to effectively scale so that businesses can efficiently retain and analyze that information. The result is a missed opportunity for enterprises to glean important business and IT insight from their operational data.
- Wikibon research shows that IT organizations routinely fall into the trap of relying on automation tied to specific products, each in control of its own data, which can severely limit operational visibility. It's time for companies to adopt approaches that increase business opportunities by applying operational data across platforms to multiple classes of hard problems.
- Operational visibility is a tricky business. Having that level of data oversight really can make a difference in how IT can contribute to the top line. Contributing to the business – rather than just supporting the business – should be the goal of IT in terms of relevance in today's environment.
- With rising complexity you need to make sense of data - operational analytics is the key.
- IT analytics lets you manage this complexity by turning Big Data inward.
- As scale and complexity increase with companies moving to the cloud, to microservice architectures, and to transient containers, monitoring needs to go back to school for its Ph.D. to cope with this new generation of IT.
- An application that makes it easier to keep data centers up and running could become the 'killer app' for Hadoop because as companies become more dependent on large-scale customer-facing apps, it’s critical that they be reliable and scale predictably.
- The operational data explosion has sparked a sudden and significant increase in demand for IT operations analytics (ITOA) systems.