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Six Cornerstones of Control Automation in Application Delivery

Transformations in software development that have resulted in the facilitated delivery pace are impacting the other sections of the product lifecycle. It is specifically characteristic for the companies integrating microservices architecture, in which the development teams are functioning separately in the process of software generation and delivery, which accentuate interacting with the other services to create a more full-fledged application. And the field where it has induced the most significant transformations is control of the applications.

Distribution of the authorities over transformation signifies the conventional model of APM execution – involving two developers who are capable of assessing sophistication of the application, comprehend basal data and get the bottom of the fundamental reason – is not maintained anymore.

According to the experts, this is all about liberalization of the entire APM environment that enables everyone – from the regular user to the highly experienced developer, who is analyzing certain issue, - to approach the data right away, to monitor all internal processes including data collection, and if the error incurs, to find the fundamental cause in seconds. Therefore, there is no longer a centralized authority that is bundling the elements in a combined set and figures out how everything is interconnected. Practical deployment of this approach allows understanding how many factors are impacting each other in the software lifecycle.

The concept of the fast-moving application and transformations is, in fact, one of the problematic issues of control microservices since the elements change continuously and they have to be monitored all the time. The only chance to catch up the transformations in the application is by the deployment of across-the-board automation. In fact, you have to automatize literally everything – starting from the process itself to the elements that have to be controlled throughout the lifecycle. If you fail to automate all these things and still prefer using manual instruments, your application is likely to become obsolete even before the changes are deployed. Nowadays there are clients who are upgrading their products and services several times per day.

These days there is a structural slide in the organization of the software development and delivery teams since now they are more concentrated on becoming faster and reaching Continuous Integration and Continuous Delivery. In the cycles of rolling out the microservices, this transformation leads to automation of each section of the development process, and here control is the last brick.

Due to this precise reason lots of experts rely on control automation. It takes too much time and resources, including manpower and finances, to maintain personnel for coding control configurations every time when the software product is changed. As soon as you change the application, you have to change lots of processes and components in a huge bundle of services, to control efficiently the configurations and the approaches used to detect the issues, and all these have to be grounded. Therefore, you have lots of developers working on the project but instead of focusing on delivery of improved value, they just configure and reconfigure the monitoring. That’s why, nowadays the vendors aspire to automatize all possible sections and components of the delivery process and, consequently, to take this burden off the personnel’s back.

The foundation of the new APM is considered to be intelligence, and creating an intelligent system starts with the capability to understand what is going on in the system which is being controlled. Then, the controlling system has to be aware of how to connect to the element and collect the data from inside automatically, without the involvement of human personnel in configuration.

According to the experts, the vast part of this task is precision of data, that’s why, for example, Instana has created a single-second resolution for all measurements and metadata, therefore its automatization drive can be upgraded continuously. If the change is implemented, the drive will localize the change and re-align the basal graph with the new connections.

The assumption is that automatized control has to be a common item. An only small number of persons are engaged in the jobs related to the control system, but at the same time lots of people are involved in startups and running the systems. As long as the software development industry is leaning toward bundling these two functions, the most innovative vendors are working on the delivery of the full-scale automatization, intelligence, and traceability.

Some vendors are going to deploy the entire APM area in order to gain maximum compatibility with the comprehensive way of application development and delivery. Despite the fact the conventional APM instrument is operational, from the standpoint of process, it is not a proper pick.

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Six cornerstones of control automation

There is only one method to navigate microservice apps efficiently which is an all-force automatization of the control life cycle by integrating Artificial Intelligence into detection, control, and analysis. The experts determine six essential pillars in the Artificial Intelligence integration strategy, and the first three of them are concentrated on automatization:

  • Robotic and Continuous Delivery, and Mapping;
  • Highly precise traceability;
  • Common rolling out cloud, container and microservice techs;
  • Full-stack application data bundling;
  • Control and forecasting of the issues based on AI in the real-time mode;
  • AI-first debugging and troubleshooting support.

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