Organic and Artificial Intelligence are both converging at an increasing rate, namely due to considerable strides in computational power improvements, investment into AI research and an expanding pool of data to analyse. Much like the human brain, these AIs are trained to find patterns in the information they analyse—whether auditory, visual or alphanumeric data.
As a result, IT operations services now have a formidable toolset available to expedite system infrastructure and corporate data analysis in the form of AI. With the varying types of use cases that AI can be applied to, there are more benefits than ever to integrating AI into your IT operations management plan.
How will AI will change IT operations?
A critical aspect of IT operations management is assigning the use of system resources in an equal and efficient manner. In the public cloud, companies like Amazon have been actively developing machine learning algorithms designed to automate the load balancing and scaling process. For example, on the Amazon Web Services (AWS) platform, something called Predictive and Auto Scaling is used. This service can analyse data from any servers in their Elastic Compute Cloud platform, which it then uses to predict and actively produce an Auto Scaling plan for your public cloud resources.
In the past, this would’ve been something that IT operations management consulting firms would perform. Significant amounts of time and money would be spent manually analysing trends and creating plans that wouldn’t adapt over time to your networks demand. This type of AI used on AWS allows you to omit the need for costly human IT operations consulting and instead have an automated service with the same function, running 24/7.
The aforementioned automated resource management can also improve energy efficiency in the data center, reducing costs in the process. In both public and private cloud services, the over-purchasing resources is commonplace, leaving you with excess computational power.
In the public cloud, providers generally charge for each specific aspect of a system, including access to networked storage mediums, resource allocations required for virtual machine instances and bandwidth usage both internally and externally. It is tempting to pay extra for more leeway, but AI services like Predictive/Auto Scaling can purchase and allocate resources only when they are needed, reducing your costs.
While the public cloud is primarily used for publicly available services and high-capacity storage, the private cloud is much more useful in low latency applications, such as virtual desktop infrastructures (VDI). In these cases, an IT operations management consulting firm can offer valuable advice on the hardware requirements of your network, since you will need to have extra capacity to futureproof your investment. VDI services like Citrix XenApp and VMWare Horizons utilise server-side artificial intelligence features that allow for predictive resource management on the servers running your virtual desktops. For RAM allocation, something called Dynamic Memory Allocation is used to reassign idle resources on a network. A similar thing for processor resource allocation is available, called Dynamic CPU Allocation.
While IT operations consulting is necessary during the initial hardware selection process, the need for further consulting is negated through these VDI solutions using Dynamic Resource Allocation features powered by Artificial Intelligence and Machine Learning.
The final topic we will discuss is the benefits AI can bring to your IT operations services, through reducing maintenance costs and maintaining performance over time.
For companies with large databases, it can be challenging to maintain the performance levels you experienced at the databases’ fruition. Increased amounts of stored data and I/O operations on your hardware can result in unnecessary system resource usage, which can also reduce longevity. Excess information such as log files can be automatically deleted after a certain amount of time by assigning database administration (DBA) jobs to an AI.
Traditionally, IT support personnel would perform manual administration of your systems, which can be slow and cost significant amounts in wages. There is also the risk of human error: important files accidentally being deleted or even entire systems going into downtime due to a lapse in human judgement. Automating the DBA process can eliminate these costs and risks, requiring only a small amount of system resources to run in the background on any servers. You can also have your DBA running 24/7, meaning your infrastructure is always fully optimised for use.
While automation of DBA can reduce the need for 1st and 2nd line support personnel; other artificial intelligence software is available that can provide self-healing and analysis. IT service operations firms can benefit hugely from this as it frees up DevOps staff so they can focus on development, rather than maintenance. Self-healing AI’s function by analyzing system errors in real time, to predict and resolve issues before they cause any noticeable downtime. The AI can also inform IT staff when it cannot resolve the issue by itself, expediting system repairs. One of the key performance indicators for IT service operations firms is uptime, making these self-healing capabilities hugely beneficial in improving the reputation of their services in terms of reliability.
Contact Us Today
Finding Hidden Patterns and Correlations Innovative technologies such as artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) are transforming the way we approach data analytics. AI, ML and NLP are categorized under the umbrella term of “cognitive analytics,” which is an approach that leverages human-like computer intelligence to identify hidden patterns and correlations in data.Explore
What Is an SQL Query Engine? SQL query engine architecture was designed to allow users to query a variety of data sources within a single query. While early SQL-based query engines such as Apache Hive allowed analysts to cut through the clutter of analytical data, they found running SQL analytics on multi-petabyte data warehouses to be a time-intensive process that was difficult to visualize and hard to scale.Explore
The Cloud is the Key to Transformation Success… Transitioning your applications to the cloud is undeniably a critical factor to a successful digital transformation endeavor. It’s more than just a lift-and-shift, however. Let’s explore several things that you need to consider before migrating your applications to the cloud, including: Readiness of your application portfolio Where to begin – the right business case and migration strategy Technology requirements and considerationsExplore
Application Modernization at Speed and Scale Enterprises are pursuing greater application scalability, cost efficiency, and standardization with containerization and virtualization platforms. So, what’s the difference? Containers are a type of virtualization technology that allows users to run multiple operating systems inside a single instance of an OS. They are lightweight and portable, making them ideal for running applications across different platforms.Explore