IT Svit team lends our rich experience with Big Data analytics to help reach your business objectives!
There are two main areas where Big Data analytics can be beneficial for your business: reduction of expenses on cloud infrastructure management or maximization of your product value by adding some AI-powered features to your application or services.
Nevertheless, both cases demand a thorough understanding of the ways Big Data systems function, as well as ample experience with the management of software delivery workflows and cloud infrastructure needed to support Big Data solutions. Over the course of 5+ years, IT Svit was engaged with more than 50 BIg Data and 800 DevOps projects, which resulted in us obtaining significant expertise in these areas.
For example, your customers might need to authenticate themselves as being of legal age to purchase your products or services. This can be done by providing a hi-res photo of them holding their clearly visible government-issued ID like a passport or a driver’s license. With the unrelenting growth and magnitude of fraudulent activities, this kind of authentication gains more and more popularity.
IT Svit can train a Machine Learning model based on Optical Character Recognition and Computer Visions algorithms to identify the face on the photo and compare it with the ID photo. If the two match, the algorithm scans the rest of the ID details, like name and surname, date of birth, place of residence or registration and any other information you might need as a part of the registration process.
We use this mechanism as a part of the CV parser feature of our product — Hurma System, an end-to-end solution for the automation of HR and recruitment workflows. Parsing the CVs +automatically from a variety of text formats helps save a ton of recruiter’s time and is a very popular feature among our customers. IT Svit has ample experience with enabling various features based on Machine Learning and Big Data analytics for our customers.
We can optimize your cloud infrastructure processes with Big Data analytics
The other main area of application for Big Data analytics is cloud infrastructure management optimization. All the machine-generated data from your systems, like the server logs and reports from various monitoring tools are gathered into huge data sets, and the ML model determines the normal operational patterns of several key system parameters, like CPU load, RAM usage, traffic throughput, etc.
After being launched in your production environment, this model monitors all the currently active processes. Once it detects one of the parameters exceeding its normal operational limits (like CPU load increasing along with the spike in traffic intensity) it responds with one of the preconfigured scenarios. For example, it launches additional application instances to spread the traffic between them and balance the workload. If it is a legitimate traffic spike — it will subside once the peak time is over. The model detects the lower CPU power consumption and shuts down the excessive servers to ensure optimal resource allocation.
But if this workload spike is caused by the beginning of a DDoS attack and launching additional application instances does not solve the problem, the AI algorithm switches the front-end of your application to a CDN like Cloudflare or AWS CloudFront and reports the possible DDoS intrusion to their admins, while also shooting down the additional application instances to conserve your resources.
Thus said, ML models can help maximize your profits and minimize your risks and OPEX. This ensures the preemptive problem solving, instead of dealing with the aftermaths of the incidents, which ensures your business saves a ton of time, money and effort and is much more competitive. If you want IT Svit to implement Big Data analytics for your IT operations and help achieve these results — contact us today, we are glad to assist!
