With its flexible trading platforms that provide fast and easy access to financial markets, the social investment company eToro provides a platform for users to observe the financial trading activity of others, copy them and then make their own trades. Every day, eToro’s online platform attracts thousands of new accounts, and its user base has grown to over 4.5 million users in more than 170 countries.

Read Case Study: eToro Director of IT Uses Anodot to Streamline Monitoring as the Fintech Scales

So, how does eToro stay on top with so much changing and vital data to be aware of? We visited their headquarters and met with Elad Gotfrid, eToro’s Director of IT, who shared their approach for handling the company’s data.

More Metrics to be Tracked

As a real time trading company, eToro must be able to provide users with reliable market rates as quickly as possible. They must closely monitor the quality of the connection from both the client and the server side. To track metrics from their Price Stream service that sends price quotes to their users, eToro had been using a variety of open source tools.

They quickly realized that they needed to expand the number of metrics being monitored and faced resource challenges in trying to adapt their traditional monitoring tools to meet these new and growing demands.

“We reached a point where we knew we needed a more flexible solution because we wanted to be able to keep track of all our client activity, and it would have taken a lot of time and money to get our original open source tools to do what we needed them to. It just didn’t make sense to us to invest in building out those tools to handle the performance issues and the amount of data and number of transactions we wanted to send for monitoring.”

– Elad Gotfrid, Director of IT, eToro

AI Analytics Gives eToro Rapid Insights into Massive Amounts of Streaming Data

At eToro, business data is a source of insight, especially when focusing on detecting anomalous incidents that can provide business intelligence. Adhering to stringent regulations under UK’s Financial Conduct Authority (FCA) and the Cyprus Securities Exchange Commission (CySEC), eToro needs to treat any trading error or problem as critical.

Gotfrid explained how the company’s approach to data requires flexible, quick analysis.  In one case, during a deployment change, they noticed an increase in error rates for certain production components. Applying Anodot’s AI analytics, eToro quickly gained critical insights: “Without Anodot, we would not have known about this technical issue until our customers contacted us, and even if a few customers had complained about the error, it would not have been clear to the tech teams that it was system-wide,” Gotfrid said.

Enjoying Anodot’s ease of use, currently several teams at eToro use Anodot’s AI Analytics to keep track of the health of their systems. “The biggest advantage for us with Anodot is that it’s plug-and-play,” said Gotfrid. “With Anodot, we don’t waste time setting static thresholds, we just get straight to the information we need to keep our users happy and engaged.”

Detect Incidents and Get to the Root Cause Faster

For eToro, the combination of Anodot and Splunk has significantly increased the effectiveness of their data analysis. “For us, Anodot means rapid insights from our data, pointing us to where to look at the raw logs in Splunk,” said Gotfrid.

eToro has earned a reputation among the online trading community as one of the most reputable online brokers in the industry. Their services and “OpenBook” trading platform have been featured in numerous international financial periodicals such as Forbes, Financial Times, Finance Magnates, Fintech Finance and CNBC.

Being a pioneer in the social trading industry, eToro relies on Anodot for alerting and correlation while Splunk gives them the tools to drill down into the raw data. This tight connection between the two systems helps them detect incidents and get to the root cause faster.

Next Steps

Click here to the full case study and find out how Anodot’s AI Analytics is helping eToro to track the health of every client request, so eToro can stay ahead of potential problems and meets their regulatory requirements.


Written by Anodot

Anodot leads in Autonomous Business Monitoring, offering real-time incident detection and innovative cloud cost management solutions with a primary focus on partnerships and MSP collaboration. Our machine learning platform not only identifies business incidents promptly but also optimizes cloud resources, reducing waste. By reducing alert noise by up to 95 percent and slashing time to detection by as much as 80 percent, Anodot has helped customers recover millions in time and revenue.

You'll believe it when you see it