The goal of businesses is to provide uninterrupted service to customers as well as to their own employees and to avoid the high costs associated with IT downtime, which a recent estimate showed to be $700B a year in North America alone.
What are the sources of risk to availability? Aren’t solutions, servers, and services becoming more reliable and robust? Indeed they are. The risk, though, is in the sheer number of hardware, software and virtualized components found in an enterprise’s IT environment and the colossal effort required in ensuring they all work together, harmoniously, without glitches – especially those that may cause an IT outage.
Today, the increasingly complex and interconnected nature of IT environments sets the stage for errors and misconfigurations that lead to downtime and outages. Interconnectedness is a fact of IT life. Hardware and software vendors are continually issuing best practice updates to try and ensure their system’s smooth operation. Because there are so many updates (a couple of thousand a year), many are never implemented. In addition, multiple teams, not necessarily working together, perform updates and changes to components and this is another source of potential errors to IT environments.
How can an enterprise gain control over the resilience of its IT environment which, under the surface, may be seething and about to boil over with misconfigurations and single-points-of-failure? Where or what is the organizing structure that will ensure that the environment continues to operate smoothly and without interruption?
Clearly, this challenge cannot be met manually. It calls for automation and deep knowledge.
Wherever an enterprise’s environment resides – in a physical datacenter, on a public or private cloud, or on a combination of these, AvailabilityGuard NXG examines the resiliency of the IT environment to discover the risks to service availability and prevent downtime. The solution proactively identifies misconfigurations, single points of failure and other errors. It provides a detailed protocol for repair so that these errors can be remedied before they cause disruptions to service or IT outages. In doing so, it utilizes deep knowledge of vendors’ best practice recommendations and input from the user-community, and employs AI and ML algorithms.