If there is one thing that can significantly alter the way we interact with systems, it’s DevOps based on Analytics. Though many organizations have just begun to scratch its surface to know its capabilities, people are starting to experience its influence in their daily lives.
When systems gain knowledge from the data fed into them, they refine the way they look for patterns and also the way they process data to become capable of anticipating new problems and modeling possible solutions. Data-driven is the wave of the future, and the wealth of data that is in code repos, issue-tracking systems, and build systems can be used to improve the ability to deliver apps faster and with greater quality.
According to Forrester, the organizations that implemented DevOps have crossed the 50% mark. This adoption rate shows the advantages it brings to its users and is in line with Forrester’s claim that DevOps has reached its Escape Velocity, making 2018 “The Year of Enterprise DevOps”.
Statistical pattern analytics
The power of Analytics lies in the usage of it and here are few of the core ones. Statistical analysis- It identifies patterns in data. For example, the links between different variables, similar attributes among certain groups, etc. This is to draw learnings from the sample that can be generalized to the wider population.
Textual pattern analytics
In this way, we tend to unlock the meaning from all of this unstructured text. It lets one unravel patterns and themes, so you know what people are thinking about. It reveals their wants and needs. With text analytics, one can identify patterns in huge collections of textual data that a human mind could never detect. It starts from text identification and ends at summarization with text mining, categorization, clustering, modeling, analysis and a lot more coming in between.
Configuration analytics can help to capture all the change configurations across the IT environments and analyze configurations to detect the changes made to the system in perfect condition. It can also help to verify the change consistency between environments and oil the friction from desired configuration.
By analyzing the detailed changes and validating the change configuration across the IT environment, IT Ops team can avoid below scenarios:
• Inadequate data of “Infrastructure Changes”, that fails to accommodate the gaps.
• Inconsistent production environment where the changes are made.
• Validating the pre-production environment, i.e. during the time the changes are made in production and operations, how do they get back-reflected into the pre-production environment?
Achieving exemplary business growth can be made possible with investing in predictive Analytics-the next best level of DevOps. Analytics can in fact allow a person sitting in a remote location to monitor the complete delivery pipeline.
The Five Fingers Theory for success in cognitive services has paid off well to many of our clients in the industry. Through our experience in implementing DevOps we have arrived at a stage to follow certain best practices- Download the whitepaper to know more.
Latest posts by Saipavan Grandhi (see all)
- How to apply a templated approach to Release Management? - October 12, 2018
- Top 10 updates you should know about ServiceNow’s London Release - September 19, 2018
- Containerization and DevOps- The Ingredient and The Marvel! - August 6, 2018