use case

Monitor Kubernetes

Control the costs and noise that come with monitoring at scale. Analyze and aggregate Kubernetes telemetry data at the source with Edge Delta’s agent fleets. Visualize key Kubernetes metrics and events to gain real-time insights into your environment.

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"One thing that people are running into a lot is there may have been incidental PII in various systems. The ability to either filter that upfront, limit the scope of what you’re looking at, or shape it so that you don’t get personal data coming into the pipeline is going to be huge."

Alex K

Director of Security, Remitly

"“With a tool like this, you are learning from unexpected things that happen and when people finally jump in, the context has already been gathered, so they aren’t running around trying to stitch the picture together.”"

Kyle Welsh

CIO, Seattle Bank

"DevOps is really hard when you’re doing 75% Ops, and 25% Dev. Automating your way out of log analysis, and some detection and reconciliation processes, is great."

Dallas Thornton

Director, Digital and AI, PACCAR

"Data fuels all of AI. With Edge Delta’s AI release, it’s not just a static set of data — the streaming aspect makes it very fresh and most accurate and relevant to the task at hand. "

Mark Relph

Head of Data and AI, Partner GTM, AWS

"I’m very impressed by the sophistication, the innovation that’s happening here, and how valuable this is for the people that are really burdened by doing this work all the time. "

Ece Kamar, PhD

CVP, AI Frontiers Lab Microsoft Research

The Challenge

Kubernetes handles scale; your monitoring solution does not

Kubernetes infrastructure is a complex web of dynamic components, constantly changing to align with workload demands. While providing valuable flexibility, this design makes monitoring Kubernetes environments incredibly tricky. Traditional methods elect to send all Kubernetes telemetry data to a centralized observability platform before bulk processing and analysis. This outdated framework results in:

Muddled Visibility

Too much telemetry data obfuscates the issues within your Kubernetes environment. Many Kubernetes components generate logs, leaving you drowning in a sea of data.

High Costs

Collecting and sending every piece of telemetry data to a centralized platform for processing and analysis is a surefire way to explode your observability bill.

Weak Performance

The “centralize-then-analyze” approach introduces significant delays between data creation and insight generation, wasting time when troubleshooting production issues.

The Solution

Edge-based monitoring

Edge Delta’s distributed architecture is built to support the scale and cardinality of your Kubernetes environment data. Powerful technologies like eBPF are leveraged to collect node-level metrics directly from the kernel, processing it along with all other telemetry as it’s generated at the source. This results in lightning fast query times and AI-powered insights regardless of data volume.

View golden signal dashboards for your Kubernetes workloads right out of the box, and build custom dashboards and alerts to monitor the Kubernetes metrics that matter most to you.

Visualize your Kubernetes environment with ease, and drill down into individual namespaces, workloads, pods, and more.

Query Kubernetes event data in sub-seconds with Edge Delta’s highly performant, time-series optimized search infrastructure.

Get Your AI Team Up and Running

Edge Delta's Collaborative AI Teammates come ready right out of the box. Get your connectors set up in minutes and start sharing context across your team.

Trusted By Teams That Practice Observability at Scale

“This is not just about doing what you used to do in the past, and doing it a little bit better. This is a new way to see this world of how we collect and manage our observability pipelines.”

Ben Kus, CTO, Box

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