Introduction: The Blind Spot in Traditional Observability

Enterprises today depend on observability platforms like Splunk, DataDog, and New Relic to keep tabs on the health of their applications. These tools provide deep insights through logs, metrics, and traces — the foundational elements of modern monitoring.

But when performance issues originate in the network, these tools often fall short. They’re built to monitor what happens after the app, not what happens before it reaches the app. For modern, hybrid, and latency-sensitive environments — especially those serving real-time services and AI workloads — that’s a serious limitation.

This is where AlvaLinks CloudRider comes in.

The Challenge: Gaps in Network Observability

While application-level observability is critical, most platforms overlook the real-time state of the network — the very medium that connects users, applications, and cloud services.

Some common gaps:
– Transient issues go unnoticed: Short-lived packet loss or jitter events are missed entirely.
– Post-mortem analysis falls flat: Correlation between logs and actual network behavior is weak or missing.
– Legacy network monitoring lacks context: Traditional tools like SNMP or NetFlow don’t provide real-time, directional insight across modern cloud architectures.

The result? Teams are often blind to the true root cause of performance problems — and they find out only after users are impacted.

CloudRider: A Proactive Overlay to Strengthen Your Stack

AlvaLinks CloudRider is not a replacement for your existing observability tools — it’s a powerful overlay that fills in the gaps.

Here’s what CloudRider adds:
– Real-Time Measurements: Continuous, active measurements of latency, jitter, and loss across actual data paths — not just device metrics or sampled flow data.
– Live + Historical Correlation: CloudRider’s insights can be fed into Splunk, DataDog, or New Relic to enrich their dashboards with network context.
– Early Detection of Degradation: Pinpoint degradation before it impacts customers, especially in multi-cloud and edge deployments.
– Seamless Integration: No need to rip and replace — CloudRider works alongside SNMP, flow, or API-based tools to create a complete observability fabric.

Real-World Example: Solving Latency in a Multi-Cloud App

A global enterprise noticed a sharp increase in response times for its EU users via its DataDog dashboard. Logs and app metrics showed no red flags.

But CloudRider detected intermittent latency and jitter on the transatlantic cloud interconnect between regions — an issue invisible to traditional tools. The network team rerouted traffic within minutes, resolving the user impact before the issue escalated to a full-blown incident.

Call to Action: Strengthen Your Observability Stack Today

If you’re using Splunk, DataDog, New Relic, or any legacy network monitoring tool — you already have a great foundation. Keep your logs, metric and alarm tool untouched, but that foundation needs real-time, proactive visibility into the network layer to be truly complete.

By integrating CloudRider:
– You eliminate blind spots in your current stack.
– You empower your teams to move from reactive troubleshooting to proactive assurance.
– You gain network-level intelligence that is tailored for today’s dynamic, cloud-first world.

Don’t wait for the next outage to expose the limitations of your tools.
Add AlvaLinks CloudRider to your stack and take your observability to the next level.

This article is part of a 3-part series on modern network observability:
1️⃣ Part 1 – What is Proactive Monitoring?
Discover why traditional methods fall short and how proactive monitoring changes the game.
3️⃣ Part 3 – Proactive vs. Traditional Monitoring: A Head-to-Head Comparison
Understand the measurable advantages of combining traditional monitoring with proactive observability.
🔁 Keep reading to see how proactive insights bridge the gaps passive tools can’t reach.
Want to experience CloudRider in action?
Contact us for a personalized walkthrough.