Artificial intelligence has been making waves throughout the business world, and for good reason! While AI can help businesses become more efficient, it is also being used to improve customer service via chatbots, help marketers make informed decisions through data analysis and business intelligence, and forecast sales.
Recent advances in computing power and data storage have made it possible to develop and deploy more sophisticated AI applications. Additionally, the increasing availability of data (including big data) has made it possible to train AI systems to be more effective. Finally, there is a growing recognition of the potential of AI to transform businesses and industries.
The web hosting industry is also gradually adopting AI-based solutions for solving complex performance and security problems – while also optimizing resource and energy management. In this article, you will learn more about the potential of AI and how it is reshaping the web hosting world.
Security with Machine Learning
Website security is always a top priority for online businesses. They want to make sure that their website is available to customers and that customer data is safe from cyber threats. AI can help to identify security vulnerabilities and take steps to fix them. It can also help to monitor website traffic for suspicious activity and block malicious users from accessing the site.
Let’s look at some of the tools that use AI for fighting cybercrime.
Monarx is a web security platform that uses AI to identify malware and suspicious traffic patterns in incoming traffic streams. It is an effective suite of tools that is helping many web hosting providers to prevent cyber attacks from harming customers’ websites. Unlike legacy security tools, Monarx is lightweight, as it runs all the heavy tasks in its own cloud to save server resources.
Convesio partnered with Monarx to provide superior web security to all customers’ sites. It provides real-time insights and tackles any suspicious activity before it becomes a threat to our customers’ sites. Besides Monarx, Convesio has also implemented other security measures as well to protect the websites and data of our customers.
Monarx doesn’t use signatures to identify malware; it uses identifying behavior instead. This results in more effective prevention with very few false positives. Monarx consistently detects and blocks malicious activity that other tools miss. This is usually 20-50% more. Monarx is enterprise-grade software designed specifically for hosting providers, integrated directly into the PHP engine. This gives it a complete, real-time view of web application activity
Traffic Patterns, DDoS, Bot Protection
Over 40% of the incoming traffic is generated by bots. Bots can be good or bad, depending on what they do. Good bots collect useful data for indexing web pages, assessing traffic for useful insights, or performing scheduled jobs. Bad bot traffic can imitate human behavior to try to gain access to restricted areas of a website, scrape data, or it can generate fake requests that overload a website’s servers, causing the site to crash also known as a DDoS attack.
Artificial intelligence can help to identify bot traffic and protect websites from cyber-attacks. By analyzing patterns of online behavior, AI can distinguish between human and bot activity. This information can then be used to block bot traffic and reduce the risk of cyber-attacks. By identifying bot traffic and stopping it before it reaches the website, AI can help defend against these powerful attacks. In short, AI is becoming increasingly important in the fight against bot traffic and cyber-attacks.
Deep Neural Networks have been quite successful at classifying objects in complex patterns. They are also used in identifying signatures used by malicious traffic. Since the networks are trained on large datasets of millions of websites, they can effectively flag even the signatures they have never seen before. Furthermore, these models can be trained on new data over time, which makes them even more powerful.
Website Traffic Routing
The public internet is a crowded space and the networks sometimes are congested, which can lead to delays and slow loading times. Routing traffic through such complex paths requires sophisticated computing for picking the fastest path to deliver your site to the end user. AI can help to deliver website content faster over the internet. By analyzing website traffic patterns in real time, AI can route website traffic more efficiently, avoiding congestion.
It is similar to the Traveling Salesman problem but on a much larger scale. AI tackles this problem by creating the most optimized virtual maps of the network. This is done by regressing through thousands of variables to draw the shortest path for the traffic to travel. As opposed to brute force methods, AI can find near-optimal paths. Similarly, AI can also help to optimize website delivery by prioritizing the delivery of high-priority content, such as critical security updates, over lower-priority content.
Managing the infrastructure is critical in the web hosting business, as it powers the large number of sites hosted by the company. But let’s face it, maintaining a web hosting infrastructure is no small feat. There are a lot of moving parts and a lot can go wrong.
AI can help web hosting providers monitor and manage their infrastructure more effectively by improving performance and reducing downtime. By using AI to identify and diagnose problems, web hosting providers can keep their infrastructure up and running smoothly, ensuring optimal availability for their customers.
With the help of Machine Learning, it is now possible to make well-calculated decisions with higher accuracy. This capability can be used to automate the server healing process. Neural Networks can now be trained on large datasets collected over the years which allows them to come up with a good strategy for balancing the additional load either across multiple servers or by creating new instances
AI is playing an increasingly important role in helping to manage power consumption inside these data centers. By using sensors and machine learning algorithms, AI systems can constantly monitor conditions inside the data center and make adjustments to things like cooling and energy usage in real-time. This helps to ensure that data centers are operating as efficiently as possible, which in turn reduces their overall electricity consumption.
A typical data center can host thousands of high-power computers that run 24/7 365 days and require a lot of energy to run. This is expensive and bad for the environment. Over recent years, AI has achieved great milestones in reducing power consumption in data centers. For example, Google deployed DeepMind’s predictive models for optimizing the cooling system inside one of its data centers. These models reduced power consumption significantly.
Similarly, Alibaba Cloud also deployed an ML-based system inside its data center that fed on large datasets of temperature sensors and learned to maintain humidity and cooling in the most efficient manner. By using AI to manage power consumption, cloud providers can reduce their costs and improve their data center operations.
Infrastructure providers leverage AI in developing sophisticated monitoring systems. They not only identify potential risks, vulnerabilities, or failures but also efficiently summarize the errors so that engineers can troubleshoot the problem quickly. This method is more efficient than visually monitoring charts or reading large chunks of sensory data.
AI-powered systems can identify potential problems before they occur. For example, if a server is starting to show signs of wear and tear, AI can flag it for maintenance before it fails completely. In addition, AI can help to optimize server performance by constantly monitoring usage patterns and adjusting resources accordingly. As web hosting infrastructure becomes more complex, AI will play an increasingly important role in keeping data centers running smoothly.
Predicting Server Resources
One of the biggest challenges both website owners and hosting providers face is estimating the required resources correctly. There is no formula available for it, thus, quite often users end up picking the wrong server size for their website. Fortunately, this can be solved now with machine learning. Instead of working through parameters like traffic, sessions, concurrent users, etc, machine learning models analyze a large dataset of the websites and their usage over time to predict the estimated server resources.
Similarly, the models can effectively predict the required server resources based on the session duration, cart activity, the number of concurrent users, etc. This comes in handy, especially for eCommerce stores that are unsure of the resources they require before a promotional event or sale. AI is not only capable of predicting the current consumption of resources, but also of predicting future events. These models can forecast the required RAM, disk space, and a number of CPU cores through time-series algorithms to help the hosting providers prepare for the big event.
Predicting Performance Bottlenecks
Web hosting providers have access to a large amount of data, which they collect anonymously for operational and monitoring purposes. This data contains useful insights for hundreds and thousands of websites about their usage, downtimes, error logs, traffic, number of plugins, etc. The data can be used to train models that predict failures or performance issues before they occur. By analyzing the patterns in traffic, or a sudden change in resource consumption the model could trigger a further investigation for checking bugs in the code or a faulty plugin. In short, with these trained models, it has become easier and easier to interpret large amounts of data and use it to make predictions with high accuracy.
Artificial Intelligence is a tool that is still evolving and just like any other tool is prone to limitations. While it has been widely adopted in the last decade, it is still a novel concept in a lot of industries primarily because they have yet to discover its full potential or lack the expertise to make the transition.
Machine learning relies heavily on the size and quality of the data. A lot of the models train in a continuous process or in batches which means their source of new training data is from the real-world environment. This poses a serious issue. Attackers can poison this data by interacting with the system unethically. This injects noisy data into the system that can affect the predicted quality of the model. For example, if the model is trained to identify anomalies in the traffic, the attackers can slowly skew its classification capabilities by injecting wrong data points so when they execute the real attack, the system is unable to flag it.
ML Pipelines and Expertise
To collect high-quality, large amounts of data, companies need to create data pipelines. These pipelines are used to collect, transform, and process data before feeding it to the machine learning model. Establishing and maintaining such pipelines requires resources. Similarly, companies also need to hire Data Scientists or ML engineers for data exploration, feature extraction, designing, training, and running machine learning models. Outsourcing is not an ideal solution, especially if you’re dealing with sensitive customer data. Therefore, having an in-house team is vital.
AI is definitely a game-changing tool for the web hosting industry. It is capable of solving complex problems in less time and with greater accuracy. The efficiency of these systems is expected to improve with time, which means companies that are adopting machine learning today will definitely have an edge tomorrow.
This article was written with the help of AI.