
Cribl announced that Cribl Edge, a highly-scalable edge-based data collection system, is now available in AWS Marketplace as an Amazon Elastic Kubernetes Service (Amazon EKS) add-on.
AWS Marketplace is a digital catalog with thousands of software listings from independent software vendors that make it easy to find, test, buy, and deploy software that runs on Amazon Web Services (AWS). As part of Cribl’s relationship with AWS, this milestone helps developers to seamlessly share Amazon EKS data between security and operations teams, optimize observability data collection, and route data to multiple destinations.
Cribl Edge creates a self-service data collection and routing process in EKS, and offers a consistent experience for developers and SREs. Cribl Edge is designed to support today’s modern distributed architectures, giving users the flexibility and control to send data anywhere, instead of being locked in to a single destination. Its intelligent agent efficiently gathers and auto-discovers observability data at its egress point to provide additional cost-effective options for data collection and processing.
Now available as an add-on for Amazon EKS, a managed K8s service to run K8s on AWS and on-premises data centers, users can seamlessly implement observability into new and existing Amazon EKS environments and gain the following benefits of Cribl Edge:
- Simplify data collection by automatically collecting logs, metrics, and application data at scale.
- Reduce vendor lock-in with centrally managed, configured, and version-controlled solution for easy expansion and low cost of ownership.
- Utilize built-in Fleet Management to effortlessly manage tens of thousands of edge nodes.
“Cribl is committed to providing customers with greater choice and control over their data, and this integration with Amazon EKS ensures customers have access to the right tools to manage data collection at scale,” said Ledion Bitincka, Co-Founder & CTO at Cribl. “As the volume of data continues to grow every year, the ability to collect the right data without installing, configuring, and managing multiple, independent agents is critical, and Cribl Edge provides users a seamless solution to achieve the visibility required to manage data collection at scale.”
The Latest
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...
AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...
The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...
Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...
If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...