Edge Delta now natively supports Dynatrace as a destination, including Dynatrace's Grail technology.
This integration enables organizations to optimize telemetry data collection, processing, and analysis, offering a seamless solution to enhance the value of observability data while reducing excess noise and costs.
Edge Delta's integration with Dynatrace gives teams the ability to intelligently collect, pre-process, and optimize log, metric, and trace data before it reaches Dynatrace, ensuring that only the most valuable data is ingested. By combining Edge Delta's advanced data processing capabilities with Dynatrace's powerful Grail technology, teams can significantly improve query performance, enhance monitoring, and reduce unnecessary data volumes.
Ozan Unlu, Co-founder & CEO of Edge Delta, said, "This integration allows organizations to optimize their observability workflows by reducing data overload, lowering ingestion costs, and gaining faster insights — ensuring that teams can monitor their systems more efficiently and effectively."
Key Benefits of Edge Delta and Dynatrace Integration:
- Cost Reduction: Filter, aggregate, and summarize data at the source, reducing the volume of data ingested by Dynatrace and cutting down on associated costs.
- Enhanced Data Clarity: Structure and optimize logs before they reach Dynatrace Grail, enabling more efficient querying and faster insights.
- Faster Issue Detection: Detect anomalies and patterns earlier in the pipeline, surfacing issues before they reach downstream systems and impact user experience.
- Improved Query Performance: Leverage the power of Grail to boost query performance by ingesting only high-value data, streamlining analysis and decision-making.
The integration allows Dynatrace users to take full advantage of Edge Delta's real-time data processing capabilities before telemetry data reaches their monitoring stack. With Edge Delta, teams can:
- Aggregate or filter out low-value datasets to reduce data noise and ingestion costs.
- Route optimized logs, metrics, and traces directly to Dynatrace Grail in a clean, structured format.
- Transform and enrich telemetry data before it's ingested into Dynatrace for enhanced query performance and richer insights.
- Leverage Edge Delta's anomaly detection to surface issues and patterns before they impact users.
The Latest
I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...
Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...
For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...
Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...
Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...
For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...
New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...
Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...
In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ...
In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...