Anomalies don’t have to be a fear factor; they could even present an opportunity to make money. Imagine detecting positive spikes in in-app purchases, conversions, or gaming activity in real-time and then having your business monitoring system identify what caused them 10x faster than you can now – autonomously. With 95% accuracy in the root cause analysis you could replicate and capitalize on the deviation immediately.
AI monitoring technologies have the potential to introduce significant cost savings for CSPs. Based on machine learning and fully autonomous, these monitoring solutions provide high ROI by dramatically reducing Time to Detection (TTR), Time to Resolution (TTR), the total number of alerts, and the number of false positives and negatives.
Though invisible to most users, APIs are the backbone of modern web applications. Developers love them because they facilitate complex integrations between systems and services. The business loves them because integrating disparate systems to create new products and services drives innovation and growth. The challenge with this transformative connectivity is the dependencies that exist between systems. API failure can result in performance degradation, data anomalies, or even system-wide outages.
How much is your company losing by reacting to problems after they’ve had a negative impact on your bottom line? How many customers churn in the time it takes you to notice complaints to your call center? Proactive business monitoring allows you to detect incidents before they have a negative impact on your company’s revenue and reputation.
The pandemic upended business for many or at the very least cast a grim shade of uncertainty, so, as many took to working from home, they also were commissioned with cutting waste. Among the biggest sources of misspend in 2020 – cloud services. And remote work may have actually spurred the problem, as organizations migrate more applications to the cloud to support these workers.
Operating in today’s digital economy often involves dealing with an extensive network of third-party providers and partners. Common types of partner networks include affiliates, vendors, suppliers, marketing platforms, and payment gateway providers. Partner networks involve tracking and analyzing data from multiple providers, each of which creates thousands of metrics and billions of events each day.
Hybrid Fiber Coaxial (HFC) networks are inherently agile and able to adapt to demand spikes. This significant characteristic was most recently demonstrated by their success in handling pandemic-induced traffic surges.
The move to cloud computing has been a no-brainer for many enterprise companies. But cloud computing is an expense that, unlike many other operating costs, is largely variable. Many companies — including the fastest-growing startups, largest enterprises, and leading government agencies — choose AWS to help them streamline fragmented processes, reduce costs, become more agile, and innovate faster.
In the digital age, the speed and performance of apps and websites have a huge impact on the customer experience. To ensure a high level of quality, Application Performance Monitoring (APM) refers to the process of tracking the performance and availability of software systems. Let’s look at what Application Performance Monitoring is, how AI and machine learning are being applied to stay ahead of the competition, and several real-world use cases.
