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Scaffolding features that support archival of data for use in machine learning, specialized agents for specific DevOps tools and AI algorithm implementations for capabilities like build success prediction, possible failure steps and possible remediation etc. Please note that AI&ML implementation vary from one scenario to another and these features may need heavy customization during actual implementation.
- Return on Investment
Helps you to measure and quantify the effectiveness of a software release. It is an extension of Insights to bring in data beyond CI/CD, ALM tools into Insights ecosystem like Application Performance Management, Log Analytics and Web Analytics Systems with an intention to measure release effectiveness. Software release is often viewed from three different perspectives i.e. engineering, operations and business. Every production/product release has say a defined number of business objectives. An intuitive way to measure effectiveness of a release can be the ratio between the total cost of release to the measurement of the actual impact.
To achieve the above, we define a concept called Milestone and correlate various data related to software development and delivery with the milestone. The change happened in the interested data source in particular point of time is define as Milestone. For a particular feature or product launch there can be one or more milestone. Using the concept of milestone, we correlate data points taken from software delivery pipeline, change management, application lifecycle management, monitoring and log analytics systems.
Technical Impact Measurement – The technical impact could be measured with any of the current application monitoring or log monitoring solutions, which are already in place. The systems could be of wide variety in nature. From a log monitoring solution, the following are the probable standouts – Elastic Search, Splunk and so on. The application monitoring usually refers to the measurement of resources consumed from an infrastructure standpoint. These include but not limited to CPU utilization, heap memory consumption and so on. The tools could range from a simple open source solution like Prometheus to a commercial solution like the New Relic. Some of the technical parameters which are usually measured are Heap Memory Consumption, CPU utilization, Application Usage and Traffic, Response time for a particular URL or method call, No of identified exceptions for a given URL or feature call, No of instances of a particular object created, Transaction Time, Response Time, Throughput or SLA.
Business Impact Measurement - The business impact or Key performance indicators for a given application may vary according to the type of the application and the measurement, which is used. For a web-based application, the measurement has usually been done by using web analytics tool like Google web analytics or the open source version of matomo. For a system, which is not based on web – sometimes the business KPI are even measured using the log management applications. For example, the measurement of a certain type of tags in the logging system can give insights to a business KPI. Some of the sample business KPI for a IT system are No of logins to a particular portal, No of checkouts happening at a given time, No of dropouts during a multi-page registration process, No of views for a particular page, No of subscription renewals for a given period of time, Improved service quality through reduced outages or reduced technical debts, etc.
Insights helps you to correlate the technical impact and business impact from traditional tools with the software delivery pipeline data in order to measure the ROI to calculate ratio that the business is able to equate the cost & impact associated with the features delivered to customers