For iGaming operators, success depends not only on content and marketing but on their ability to stay online when it matters most. We spoke with a SOFTSWISS expert, Deputy CTO Denis Romanovski, to understand what’s really at stake during high load events, what mistakes others make, and what architectural decisions allow platforms like the SOFTSWISS Game Aggregator to consistently deliver 99.999% uptime – even at peak moments.

When a platform fails under high load, what are the main negative consequences for operators?The fallout hits three fronts at once. First of all, you lose revenue. Every failed bet is a direct GGR gone. In a one-minute outage during peak hours, you could lose tens of thousands of euros before you even spot the issue. Second, frustrated players flood the support team with refund claims and bad reviews. Most of them switch to your competitor. Getting those players back costs far more than keeping them happy in the first place. And third, in the scramble, tech teams try to spin up extra cloud capacity at premium rates or engage pricey third-party consultants. Those crisis-mode costs often hit the usual infrastructure budget for weeks afterwards.

So in short, downtime isn’t just an IT problem – it’s a full-blown business crisis that affects finance, marketing, and customer experience.

How does SOFTSWISS prevent those failures? Which patterns are most effective for operating without breaks?

Our resilience comes from layering proven patterns. We run Kubernetes in multiple regions – Europe, Latin America, and South Africa – so player connections go to the nearest point of presence. Databases replicate asynchronously, enabling instant failover if one zone degrades.

We develop containerised microservices, which means that some of our features and tools run in isolated pods. Rolling updates and canary deployments let us push fixes to a tiny slice of traffic first; if any metric goes beyond the threshold, Kubernetes automatically rolls back.

Static assets and game binaries are cached on regional Content Delivery Networks to reduce the load on central servers. Players receive data from the closest edge node with round-trip times of under 100 milliseconds, even on 3G connections. We also have an efficient system for DDoS Defence. Our stable partnership with Cloudflare provides multi-terabit scrubbing. Malicious traffic is cleanly filtered at the network edge, leaving genuine players uninterrupted.

But one more piece is just as crucial as technology: the team behind it. You can invest in the cutting-edge hardware and build the best architecture, but if engineers lack experience working under pressure, reaction times slow down, and players notice. 

SOFTSWISS brings together experienced SREs, database experts, and network architects with deep knowledge of real-world stress situations. This means we don’t just detect issues quickly – we fix them before operators lose trust.

Together, these layers of design and expertise ensure that, no matter what stress tests occur, our platform consistently delivers on its 99.999% uptime promise.

From an operator’s standpoint, what scenarios trigger the greatest anxiety during traffic surges – flash promotions, major sporting events, or something else?

Operators worry most about the unknown spikes. Scheduled events are planned for, like a Champions League kickoff or a midnight bonus reset. But unexpected surges, for example, when a progressive jackpot hits 10 million euros or a social-media post goes viral, can triple traffic in hours, if not minutes. These are the moments when lobbies freeze and players see spinning wheels that never load. 

The fear is not theoretical. I think every operator is familiar with this feeling when you see the queue at the support service filling up with complaints. Every frozen second undermines the player trust that operators spent months building. That’s why they need a reliable tech partner with proven protocols for handling traffic spikes and a track record of keeping the software running without downtime.

Can you walk us through a real “crash test” you’ve seen: what operators see on their dashboards when systems go down?

I can describe a typical scenario that happens in one form or another quite often. Let’s say it’s a Saturday free spins sale on a new slot, paired with double loyalty points. Traffic can jump from 5,000 to 15,000 concurrent users in ten minutes. On the dashboard, CPU usage rises above 90 per cent, Redis cache miss latency jumps from 5ms to over 50ms, and the error rate exceeds 5 per cent. Players see “502 Bad Gateway” errors or simply blank game tiles.

Behind the scenes, operators struggle to issue refunds, while marketing watches their promotional budget turn into failed KPIs. That kind of slippery slope, where one service slowdown affects another, can turn a simple spike into a full-scale outage.

Another case we had at SOFTSWISS involved a live stream event run by one of our operators. They hadn’t properly forecasted the traffic surge, and the load hit fast. We saw system strain building within minutes – API response times climbing, queues backing up. Our team had to act quickly to rebalance and optimise the infrastructure on the fly by adding resources and redistributing load.

Are there any general recommendations or lifehacks operators can use to ensure the stability of their platforms under high load?

Sure – stability is not just about servers and code; it starts with the way people work together and the processes they follow. Regardless of the platform, there are some crucial questions and data points operators should agree on with their provider’s technical account manager before any big launch. 

First, operators need to track traffic dynamics closely – how many players arrive, how many register, and how many stay in play. They should share these forecasts with their provider and flag any risk of actual traffic far exceeding expectations.

The provider, in turn, will map its load models against planned promotions or events. That way, capacity gets reserved in advance instead of scrambling when reality outpaces the plan. At SOFTSWISS, for example, we continuously monitor load on our core components and build in redundancy to absorb traffic spikes.

Operators also need clarity on which SLAs guarantee that extra capacity or failover will be authorised the moment it’s needed. When seconds count, no one should be hunting for the required approvals.

Finally, a new brand or promo campaign must be introduced gradually. Operators can start with low-traffic markets or off-peak windows, verify performance in real‐world conditions, and only then ramp up traffic. This approach will let them avoid unpleasant surprises when the big day arrives.

Nevertheless, high-load incidents do occur. If this happens, blaming is the last thing to think about. However, the tech partner must provide a copy of its post-mortem playbook with root cause analysis, updated runbooks, and clear remediation steps.

Following these checkpoints, operators can trust their tech partner to handle any traffic surge. Potential failures that once threatened to crash the system become routine operations, no matter how intense the load.