20.2 C
New York
Sunday, September 25, 2022

How AIOps Can Help IT Developers Manage Applications – Programming Insider


Posted in:

In the past few years, the software development industry has undergone several major changes. The biggest of these is that it’s become more complex than ever before. Developers have to deal with an increasing number of issues, such as finding talented IT professionals who can write robust code and implementing new technologies that improve software reliability.
The good news is that many IT organizations are turning to AIOps Artificial Intelligence for IT Operations to help manage their applications. This approach combines machine learning, predictive analytics, and artificial intelligence (AI) tools into a single platform so you can identify potential problems before they occur—and fix them faster when they do happen.
AIOps is a new approach to managing IT operations. It uses machine learning and artificial intelligence to automate many tasks that used to require human intervention, such as detecting and remediating security breaches, identifying performance bottlenecks, or assessing the risk of outages. AIOps also helps IT organizations become more nimble and proactive by providing real-time visibility into their infrastructure, so they can see what’s happening on their networks and make changes before problems occur.
AIOps uses machine learning and AI to analyze large amounts of data. It’s used to detect issues before they happen, which means the IT department can avoid problems and proactively resolve them when they do occur. AIOps can also be used to monitor and predict the performance of applications, as well as track their performance over time.
AIOps allows developers who may not have been previously involved in operations tasks like monitoring application usage or error rates to more easily manage those processes because they rely less on manual reporting and analysis from end users. This makes it easier for developers who aren’t familiar with operations management tools like Splunk or New Relic, which require a lot of training time before employees begin using them effectively on their own​.
Software development has become an increasingly complex process. There are more tools and technologies than ever before, making the process of building a new application more difficult than it used to be. Developers face challenges with managing these tools and technologies, but they also have the potential to help developers create better applications.
The complexity of software development has increased exponentially over the past decade, due to increased demands on applications that need to be built faster, with higher quality standards. The number of technologies available today is staggering compared with even just five years ago—and only getting bigger every day! In addition, there are many more people involved in the development process (programmers as well as business experts). This makes it difficult for teams to work together efficiently enough so that they can deliver high-quality results consistently—leading directly into our next point:
The biggest challenge that developers face today is to ensure that their applications meet customer and business needs. For this, they need to ensure that their applications are reliable and robust. They also need to ensure that the apps are scalable so that they can handle peak loads with the goal of reduced to no downtime. 
The next challenge that developers face is to ensure that their apps are secure. This means they need to make sure that there are no vulnerabilities in their applications so that they can’t be exploited by cybercriminals.
Another challenge that developers face is to ensure that their apps are performant. This means they need to make sure that their apps can handle requests quickly so that users don’t experience lag or delays while using them. 
With the help of a Machine Learning and Artificial Intelligence (ML/AI) platform, IT organizations can gain a deep understanding of the behavior of their applications. They can then use this information to predict future incidents and take action before they occur. For example, if an application has been running unusually long periods of time without crashing in the past week, it may be worth investigating whether there’s a potential issue that could lead to downtime or service disruption in the coming days.
This type of proactive support is only possible through AI-powered monitoring and detection capabilities that easily identify patterns in application performance data. These patterns can then be used by developers as a starting point for further investigation into what might be causing them—and ultimately how to resolve them as quickly as possible.
Blue Chip offers an AI platform called Mist AI from Juniper. Mist AI uses a combination of Artificial Intelligence, Machine Learning, and Data Science Techniques to optimize user experiences and simplify operations across wired access, wireless access, and SD-WAN domains. 
Devices work with Mist AI to optimize user experiences from client to cloud including auto event correlation, root cause identification, self-driving network operations, network assurance, proactive anomaly detection, and more
AIOps helps organizations build more robust, reliable software and prevent outages. The solution is a set of software tools that can help IT teams monitor, analyze and resolve issues faster. AIOps includes:
AIOps is a powerful tool for developers. It helps them reduce the number of bugs in their code, speed up development time and build better software. Since AIOps can detect problems before they happen, it can also help organizations avoid outages and other costly issues that could potentially put their business at risk.
See more
©2022 Programming Insider

source

Related Articles

LEAVE A REPLY

Please enter your comment!
Please enter your name here

Latest Articles