On launch day, your CDN infrastructure provides a critical connection between your game and your players. Every download passes through it, and when something goes wrong, the consequences land at every level of the organization, from operations teams managing incident response in real time to executives tracking revenue and download numbers.
Your teams need to detect and respond to problems quickly, including DDoS attacks, cache misses, and regional performance failures. That requires complete, accurate visibility into how your CDN infrastructure is performing at exactly the moment when it’s under the most pressure.
Traditional observability platforms aren’t designed for that. Launch day telemetry can spike to tens of millions of rows per second, and most platforms respond by sampling heavily, which creates gaps in your data. Short retention windows restrict your ability to do post-event analysis. And if you’re using multiple CDN providers, which most game publishers do, you’re probably correlating across separate CDN dashboards with separate schemas during a live incident.
Hydrolix gives you complete visibility across all your CDN providers at launch day scale, with full-fidelity data, a unified schema across providers for dashboards and queries, and the ability to drill into raw logs in seconds.
Further reading:
Get a Complete Picture of CDN Performance Across All Your Providers
Most major game publishers run multiple CDN providers simultaneously. The redundancy is deliberate. No single CDN has uniform performance across every region, and distributing load across providers gives you the ability to route traffic based on real-time performance, reduce single points of failure, and negotiate better terms with each provider. For launch day, multi-CDN architecture makes it possible to absorb the kind of concentrated, unpredictable demand that a major title drop generates.
While this approach brings more resiliency, it also makes visibility more challenging. If you’re running three CDN providers and you’re relying on separate dashboards for visibility into providers, then you have to manage three separate log streams, three schemas, and three dashboards. And while some observability platforms offer integrations with major CDN providers, they don’t provide unified visibility with the ability to quickly correlate data across all your CDNs.
As a result, during a live incident, determining whether a latency spike is isolated to one provider or showing up across all of them means pulling data from each system separately and reconciling it by hand. This process is time-consuming and prone to error, and your teams are forced to make routing decisions, escalate incidents, and update WAF rules based on a partial picture of what’s actually happening.
CDN Insights gives you a single dashboard across all your CDN providers, with pre-built views for download completion rates, regional throughput, error distributions, and latency by provider and geography. Because log normalization happens at ingest, the same query works across all providers simultaneously without any translation or further standardization needed. An engineer investigating a regional anomaly doesn’t need to know which CDN is serving that region. The data is already unified, and the answer comes back in seconds. When you need to go deeper, you can drill from that dashboard directly into full-resolution raw logs without switching tools or waiting for archived data to come back online.
The next image shows a dashboard with unified visibility across major CDN providers. On launch day, this is the kind of visibility you need to understand how users are interacting with your content and whether they are able to successfully download the latest title.
In this dashboard, all providers are showing green, but when a CDN turns yellow or red, you have the information you need to consider steering decisions, escalation, and deeper investigation.
You can then look at individual regions, ASNs, and other segments to better understand where problems are coming up. The following dashboard shows how an individual ASN is performing. It’s currently orange, which could signal increased demand, issues with caching, or even the beginning of a DDoS attack.
From there, you can quickly drill down into the raw logs to pinpoint issues before they impact your customers.
Full-Fidelity Data Without Gaps From Sampling
At peak launch volume, the failures most likely to affect players, such as a delivery error concentrated in a specific region that affect 5% of downloads, produce a small number of events relative to total traffic. If you’re sampling data or have a fragmented view of CDN traffic, you might not catch the issue at all. Meanwhile, issues that seem small relative to the total amount of traffic can still affect thousands of customers. If you don’t have a complete picture of launch day traffic, issues can quietly pile up, impact revenue, and lead to more support tickets and angry end users.
To solve this problem, you need full-fidelity data without sampling, and that data must be actionable in near real-time without slowdowns or bottlenecks.
Hydrolix gives you full-fidelity data without sampling, even if you’re ingesting tens of millions of lines of telemetry data per second. Typical time to glass, even at Super Bowl scale, is five to ten seconds, and FOX Sports saw median query times of under half a second across 55,000 queries over the 2025 Super Bowl.
One major game publisher operating across five CDN providers coordinates every title release with Hydrolix in advance. Before each launch, they share expected load parameters so infrastructure can be pre-scaled. The ingest spikes that follow, including per-title spikes from additional studios publishing on the same platform, are absorbed without rate limiting or data loss. The same architecture handles the concentrated demand of live broadcast events like the Super Bowl.
In contrast, legacy observability platforms struggle with launch day scale, and sampling is typical for two reasons:
- Full-fidelity data leads to ingest bottlenecks, slower dashboards, and timeouts. By ingesting just a fraction of total log data, you get a partial picture of your infrastructure more quickly.
- Sampling is the simplest lever for cost control if your observability bill is already too high.
These sacrifices are a result of legacy infrastructure decisions and high costs. Your teams shouldn’t be forced to compromise on launch day visibility because traditional observability platforms can’t keep up.
Keep All Data for Post-Event Investigation and Capacity Planning
The benefits of full-fidelity data extend far beyond launch day, but only if you keep it. One game publisher using Hydrolix needed longer retention for GDPR reasons, while another publisher needed data for post-mortems and capacity planning.
CDN data contains a complete history of every HTTP request, giving you insights not just on performance by region but also engagement with your content. The data is valuable for post-event analysis, security investigations, capacity planning, and business intelligence use cases. You can make comparisons across seasonal events and compare data to previous launches. And you can use Hydrolix MCP so that teams across the business can ask natural language questions of the data for use cases beyond operations and capacity planning.
Hydrolix offers 15 months of full-fidelity data retention by default, with all data remaining hot for queries. This is in contrast to the standard retention windows of typical observability platforms, which are often just 30 days. Most teams set retention windows based on what storage costs allow, not what operations actually require. At launch-day ingest volumes, keeping full-resolution data on hot storage gets expensive quickly, and 30 days may seem like a reasonable compromise. But what if you discover that a title underperformed in a specific market, or that there’s evidence that attackers compromised your network? If you need to look back more than 30 days, the data is already gone.
Hydrolix keeps retention costs down by maximizing the benefits of commodity object storage and achieving up to 50x compression on log data. At 20x compression, one terabyte of raw CDN logs compresses to approximately 50 gigabytes on object storage. If you’re currently retaining 30 days of full-resolution data on low-latency SSDs, moving to Hydrolix allows you to extend your retention to 15 months while bringing costs down.
There’s no cold storage tier or no rehydration pipeline to manage. The same query syntax that works against last hour’s data works against data from last year’s launch. Post-mortems are more useful because you’re working from the complete event window. Capacity planning is more accurate because you’re comparing against full traffic patterns from prior launches, not sampled approximations.
See How Hydrolix Performs Against Your Requirements
Hydrolix has production deployments with game publishers that generate some of the biggest launch days in the industry. Multi-CDN monitoring is a common throughline for these publishers. They’ve gone from fragmented visibility into their network infrastructure to complete, unified observability across their CDN providers.
If you’re looking to compare Hydrolix to your current solution or to other vendors in the CDN monitoring space, here are some key questions you should ask.
- Can the platform handle the sustained, massive scale of launch day? That means real-time ingest of more than 20 million rows per second without gaps or sampling with performant queries. You should not be compromising visibility on the most important days of the year.
- How long can you retain data and how accessible is that data for queries? First, identify your retention requirements. How long do you need to keep data for security, compliance, and other use cases? And how long would you ideally keep it (beyond basic needs) for expanded use cases? For long-term retention, does your vendor make historical readily available for hot queries or do you have to rehydrate data first? Choose a vendor that doesn’t force you to choose between data retention and high costs.
- How thorough is CDN coverage? Prioritize vendors that help you get started with minimal set up. CDN data should be standardized and visible in a single dashboard. You shouldn’t need to use valuable engineering hours to do extensive prework to standardize data and set up CDN coverage.
A technical evaluation with Hydrolix typically starts with connecting your CDN log streams to and running queries against your own data. That gives you a direct answer to the questions that matter most: whether data ingest keeps up with your peak volume, how long cross-provider queries take, and what it looks like to drill down into raw logs. Most teams have enough data to make an informed assessment within a few weeks.
To get started, request a technical demo or get a quick value assessment from an expert.
