Empowering teams to reliably scale and reduce downtime in production.
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See how our Predictive Scaling works
Overcome autoscaling challenges. Our Predictive Scaling capability ensures you get optimal app performance and meet your SLO’s.
Set performance or SLO goals you want to meet.
AM proactively scales before issues impact your user's experience.
Auto-remediate issues without troubleshooting.

See how Kubernetes scales your application based on Aspen Mesh recommendations.
Benefits to Developers
Aspen Mesh enables developers to work more efficiently and improve app performance. Watch demo.
Reduce Alert Fatigue
Stop reacting to alerts that your app’s performance is degrading. Get peace of mind that your environment is continually optimizing scaling to head-off issues before they become a problem.
- Get a holistic view of the truly critical issues that require action.
- Spend less time troubleshooting by receiving intelligent, app-based incident correlations instead of unrelated infrastructure alerts.
- Reduce application downtime & improve performance.

Aspen Mesh informs you when there is danger of violating an SLO.

Aspen Mesh & K8s HPA
How HPA falls short for autoscaling:
Kubernetes’ Horizontal Pod Autoscaler (HPA) is reactive and lacks the ability to anticipate when to scale.
- Doesn’t begin to scale until after a threshold value is crossed
Threshold-based, reactive scaling to respond to traffic events by adding more replicas is often insufficient. By the time enough replicas are added to handle the load, it’s too late, and significant degradation or outages have already occurred.
- The HPA controller relies on pod-level metrics
Pods often have multiple containers, such as a sidecar, for logging an API. Pod-level metrics can be skewed because performance characteristics are usually much different between containers in the same pod.
The Aspen Mesh + HPA solution
Only Aspen Mesh automatically scales K8s pods ahead of demand to remediate potential issues before they can become a problem.
The Horizontal Pod Autoscaler is a powerful and necessary feature in a cloud-native platform. We make it possible to take full advantage of HPAs’ capabilities. We use the HPA API to give you what you need to turn on HPA and ensure its optimized without locking you into a proprietary solution. Then we apply machine learning and rich telemetry data available from your applications to model your applications’ behavior to provide insight into when applications should be scaled out or in.
As your app patterns change over time, Aspen Mesh automatically adjusts to ensure performance is continually optimized. Create an account now to get started.
Read White Paper: Making HPA not suck and live up to its potential: Overcome the limitations of K8s Autoscaler (HPA) to achieve reliable, dynamic autoscaling.
Integrates easily, no rip and replace needed
Aspen Mesh integrates easily with your cloud platforms, infrastructure monitoring tools and open-source technologies. The Aspen Mesh distribution for OpenTelemetry lets you leverage your existing tooling. It supports both OpenMetrics and OpenTelemetry standards for metrics data.
- No vendor lock-in. Continue to route telemetry data to your existing solutions and Aspen Mesh.
- Seamlessly integrate with Google Kubernetes Engine (GKE), Amazon Elastic Kubernetes Service (EKS), and Azure Kubernetes Service (AKS).
Available now – Get unlimited access to all new features as they are released.
Create an Early Access Account
Set up your account in minutes and get unlimited access to the Aspen Mesh Platform.
Become a Lighthouse User
We’re looking for modern app teams that demand higher application performance Share your biggest problems and help us shape features of our SaaS platform.
Leverage the power of the technologies in their microservices environment.
Get in Touch
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