Monitor & Analyze

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The Monitor & Analyze element provides ongoing analysis of data from the production environment giving needed insight into performance, user behaviors, and potential disruptions.

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Related Mindset:

Operational Excellence

Data-Driven

Segment:

Deploy

Inputs:

A deployed production application which has been configured to provide insight into its performance

Outputs:

Ideas for optimizations and experience improvement

Once an organization releases an experience into production, the greatest support that can be provided is a continual analysis of data that the environment is producing.

This data, when analyzed properly, can help inform decisions around environment capacity, product focus, and emerging trends.

The types of data gathered at this point generally fall within a few categories:

  • Production log data - Modern solutions such as the Elastic Stack enable organizations to keep massive amounts of production log data and analyze them for patterns and trends. This data is critical to gauging the health of an environment, adherence to non-functional requirements (NFR’s), and any errors which are occurring within the environment.
  • Descriptive analytics - Descriptive analytics provide us with a clear understanding of what happened: who visited our systems, how many people were there, what they engaged with, and how they encountered us. All of this is valuable information for both product management, development, and the operations team.
  • Predictive analytics - Prescriptive analytics take our descriptive analytics and use trends to predict a future state or condition. This becomes valuable in predicting product use behavior as well as capacity for environments.

When integrated properly, there is a continual connection between this element and the Data Analysis element within the Idea Generation segment. Continual analysis of this data should lead to new ideas to support the product, the production environment, or development.

Common Pitfalls

Organizations that are effectively gathering and monitoring production data can still be susceptible to a collection of common pitfalls:

  • Data collection without on-going analysis - Most organization’s today understand that there is a need to gather and store most all data that is produced by their systems. However, it is a lot more rare for organizations who continually analyze the data in such a way that it leads to actionable steps that should be taken. Organizations need to place just as much of an investment in tools, training, and talent in data analysis as they are placing in data storage.
  • No data strategy for production data - While great insights can be gathered today from your data, it is likely that the technology and solutions that we will have in the future will excel beyond our current capability. An effective data strategy needs to be in place to ensure that we are storing the data for future consumption and analysis.

Tools

Since an exhaustive list of tools for data gathering and analysis on production data would be extensive, here is a collection of each type of toolset for the types of data needs identified above: