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Managing DevOps development services requires domain expertise and experience to handle the sheer magnitude of data. It is always difficult for DevOps teams to absorb and implement relevant data to resolve the customer’s issues effectively. They need to spend tens of hundreds of hours in identifying the issue from Exabytes of data. Here, Artificial Intelligence (AI) technology lends a helping hand.
There is no exaggeration in mentioning that AI will drive the future of DevOps transformation processes. As it is not possible to handle the zillions of data and computing manually every day, artificial intelligence will become the right tool for computing and analyzing.
DevOps teams can readily develop, deliver, deploy, and manage applications with the help of AI. But before digging deep into the ways AI drives the DevOps transformation, let’s understand the importance of AI and DevOps combination.
Both AI and DevOps are interdependent concepts. On one hand, DevOps is an approach related to delivering software, and on the other hand, AI technology can enhance the functionality. DevOps development service providers can test, code, release, and monitor enterprise-level software more efficiently with the help of AI. What’s more, AI is useful in bringing automation while resolving various issues and improving collaboration.
AI can play a crucial role in improving the efficiency of DevOps processes. It makes it possible to enable instant development and operations cycles for ensuring better customer experience.
Core DevOps processes like continuous integration (CI) and continuous deployment (CD) of tools can generate a lot of data. Also, different metrics including the number of integrations and their success rate can be analyzed accurately with the help of AI technology.
Let’s go through the top ways AI can remain beneficial in DevOps transformation.
Simply put, AI is an asset to DevOps, and it helps DevOps professionals in multiple ways along with the ML (Machine Learning) concept. Here are the key benefits of DevOps processes-
AI technology is useful in analyzing a zillions of gigabytes of data produced through functional testing, regression testing, and user acceptance testing. AI can easily define the pattern in such data while bringing the outcomes.
It also assists companies to identify mediocre coding practices that can result in unwanted errors or bugs. In a way, AI technology makes software testing more productive for the company and increases efficiency of testers and other DevOps professionals.
DevOps teams work on multiple projects. They need a robust alert system for finding spot flaws quickly. Because of such an advanced system, at times, alerts come in huge numbers and are marked with the same urgency.
Now, AI and ML-based systems can help DevOps teams prioritize their responses based on certain factors like past behavior, alert intensity, and the source of alerts, etc. It is possible to manage such situations efficiently for DevOps professionals when systems are flooded with a massive amount of data.
Seamless and real-time access to data is essential for various DevOps teams while working on multiple projects. AI can help analyze and release data from its organizational silos for big data aggregation.
It is possible to collect data from multiple sources and analyze it properly for offering actionable insights. Such an improved data access can take companies to a new level and increase their productivity.
A major failure in any particular area can weaken the process and slow down the production cycles in DevOps. ML-based models help in predicting data-related errors. AI has an ability to read patterns and DevOps service providers can easily predict the signs of failure, especially when an occurred fault is known to produce definite readings.
AI can ‘see’ indicators that humans cannot perceive. Such predictions and notifications can help the team to identify and resolve the issues before they impact on the SDLC (Software Development Life Cycle).
AI is capable of driving the transition from a rule-based, manual analysis management to self-governed systems. It can simplify the complex processes and increase the level of adaptation for the enterprises. Such execution efficiency can increase productivity and overall profitability of the company over the period.
Root cause analysis plays a critical role in finding the failure in advance and preventing it from happening. With the help of AI, it is possible to determine the root cause based on the patterns between causes and activities. Usually, engineers resolve issues superficially and avoid comprehensive analysis on the root cause. With the help of AI, root cause analysis can be done in a faster way.
It is imperative for developers to release code at high velocity and the operations teams need to ensure that the existing systems do not get disrupted. AI can improve the collaboration between development and operations teams.
The AI-powered systems can aid both the teams by providing a single and unified view into systems. With this, it can improve the understanding and knowledge of anomalies detected. As a result, DevOps professionals can rectify them instantly.
Security plays a vital role in successful software implementation. Here, DevSecOps plays a vital role by providing effective security against breaches and DDoS (Distribution Denial of Services) attacks.
AI is useful in augmenting DevSecOps and enhancing security by recording threats. A central logging architecture powered by AI and ML can detect anomalies with ease. AI can make a proactive strategy by combining AI and DevOps technologies.
DevOps development solutions can leverage the benefits of AI-powered features. There is no exaggeration in mentioning that AI can bring transformational changes in various DevOps processes. All you need to find the right service provider for leveraging such benefits in all the processes and bring agility.
Solution Analysts is a renowned DevOps development solutions provider in India. We have an in-house team of experienced DevOps professionals who can efficiently manage any size of processes related to development and operations. We strive to deliver advanced and complex solutions for bringing automation and transforming core processes of a global corporate clientele.
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