Critical IT incidents can result in annual costs running into millions of dollars for organizations across all industry sectors. Several major IT incidents crop up in companies with no major warnings, or as a result of multiple minor warnings being ignored, neglected, or missed.
The main reason for this is that the warnings are not correlated/grouped together in an indicative way which depict the risks that businesses and systems face in a dynamic environment.
Despite several efforts to increase the robustness of IT infrastructure, it is a known fact that there still persist a lot of IT incidents that can last from just a few minutes to several days. This can have serious financial implications along with the risk of losing your most valuable asset i.e customers.
Some of the prominent IT incidents that have happened during the span of the last decade include an IT meltdown at RBS for which they had to pay a hefty fine of £56 million. Other incidents include a 5-hour downtime for Delta Airlines in 2016, costing them $150 million. Costo in 2019 lost $11 million of sales due to an outage that lasted more than 16 hours. Major technology companies are also not IT incident proof. A complete 12-hour outage in the year 2015 led to a whopping $25 million loss to Apple. More recently, Facebook had a major outage incident in 2019 which ticked around $90 million.
These companies are the market leaders. They have huge margins and millions of dollars to survive a major IT incident. At the same time, there are companies that are smaller in size that also face the risk of critical IT incidents, which would cost hundreds of thousands or millions of dollars. In fact, most of the smaller companies are at risk of running out of cash due to a major IT incident.
The IT world is changing rapidly and a lot has already been talked about moving to the cloud and the adoption of agile methodologies with dynamic and distributed architectures. These systems have multiple advantages compared to traditional systems including great performance. But the very same systems are also complex and generate a lot of raw data. FYI: By 2025 we will have 80B devices connected which is 10 times the global population. Legacy monitoring systems were not developed to handle this complexity and volume of data.
All complex IT systems require monitoring. As of today, IT engineers use manual reactive solutions (Datadog, Newrelic, ELK, etc) to manually set rules & thresholds to detect IT incidents. Once an incident occurs engineers have to manually analyze TBs of data to find the root cause of the incident in order to resolve it as quickly as possible. This can be really costly for businesses, as downtime can be extremely expensive (a few minutes of downtime can cost hundreds of millions of $ and can have a severe impact on customer churn. Click here to see exactly how much you save if you use PacketAI.) The complete scenario is a common sight for companies using traditional monitoring tools, as they are reactive in nature and rely on engineers to do manual correlation to detect the root cause.
How can PacketAI help me, you may ask. Our solution is proactive in nature compared to the existing solutions in the market.We collect raw data (logs, metrics, and events) using our easy-to-install agent, compress it to remove the noise, process it with our algorithms, and use NLP to understand it.
Once we complete the preprocessing, we use 2 learning methods to make predictions for the incidents:
The first learning methodology is based on supervised learning – algorithms are trained on historical data and will be able to detect future incidents that are similar to the historical ones. This is called deja vu prediction.
The second learning methodology is based on anomaly detection. The algorithms will understand the normal behavior of each parameter and detect anomalies that can cause incidents. This is how AI can predict black swans i.e. critical incidents that the system has never seen before.
Based on these two methods incidents are predicted and alerts are sent out. A typical alert can be of the type: “There is an 80% chance that there will be latency on application A, due to config files errors on the HAproxy”.
In this way, you can predict incidents and avoid the enormous cost of incidents before they impact your business and customers.
Now, let’s go through a real-life case of how much money companies lose due to IT incidents and we will break down the savings estimate for you to understand how our ROI calculator works.
Let us consider an example of a fast-growing e-commerce platform. Their log volume is about 5TB/month, with 500 hosts to be monitored. We also consider that the company faces an average of 2 critical incidents per month costing an average of €120,000 per critical incident, the average mean time to detect a critical incident(MTTD) is 30 minutes per incident and the average mean time to repair(MTTR) is 30 minutes per incident. The company also pays a man-hour charge of €500/day.
Below is the breakdown of potential yearly savings for the e-commerce company if they used a proactive monitoring solution like PacketAI. If you are keen to know how much your potential savings would be you can click here to see.
*1 day = 7 hrs
**Cost to Business based on the size of the company:
The companies that focus to drive innovation, increase agility in operations, and boost productivity are the new world leaders. With PacketAI, you can concentrate on your company vision and core business activities rather than spending your precious time maintaining and analyzing the IT infrastructure.
Regardless of whether your company’s cost per incident is €10,000 or €150 million, being able to significantly reduce the volume of the incidents will generate meaningful savings very quickly. Perhaps more importantly it will keep your company out of the mess of handling infrastructure issues and would allow you to work towards your company goals with a better focus on your core business.
PacketAI is the world’s first autonomous monitoring solution built for the modern age. Our solution has been developed after 5 years of intensive research in French & Canadian laboratories and we are backed by leading VC’s. To know more, book a free demo and get started today!
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