BigPanda has teamed with Datadog to invest in a go-to-market partnership to create a comprehensive solution for monitoring, analytics and incident management.
The partnership includes powerful new integrations for out-of-the-box data-sharing between the two platforms, including alert, topology and change data.
The integration provides support for all eight of Datadog’s monitoring tools, and it’s the first integration to utilize Datadog’s rich topology datasets out of the box. Datadog will offer an in-product “integration tile” to make integration with BigPanda fast and intuitive, allowing users to feed machine learning-driven root-cause changes back to Datadog.
“Event correlation and automation is now simpler on Datadog’s platform,” said Ilan Rabinovitch, VP for Product and Community, Datadog. “With information collected from service dependencies through Datadog APM, BigPanda is able to detect incidents and isolate infrastructure or application changes that may have led to an incident.”
For Datadog users, BigPanda allows them to correlate alerts collected from all Datadog monitoring modules, including Infrastructure, Log Management, and APM. BigPanda also gives Datadog users the ability to collect alerts from other third-party tools along with Datadog alerts into context-rich incidents. This significantly reduces alert noise in users’ environments while reducing Mean Time To Respond (MTTR) and other MTTx metrics.
For BigPanda users, the integration lets them tap into Datadog’s new service-to-service topology map to drive event enrichment, correlation, impact analysis and prioritization. Combined with CMDB data ingested from IT Service Management systems, this integration allows users to visualize the relationship between services in Datadog and other services.
For joint customers such as United Airlines, the BigPanda and Datadog alliance ensures their ability to unlock additional value as the companies introduce new technology integrations that deliver on United’s mission to serve the needs of their customers in today’s world and maintain IT service excellence their customers expect.
“There is great synergy between BigPanda and Datadog because we are both modern platforms built for the modern enterprise and the technology stacks that go along with that,” said Elik Eizenberg, co-founder and CTO for BigPanda. “We are both SaaS-native, cloud-native solutions built to deploy quickly and scale easily in today’s always-evolving IT environments. The market demand made this a no-brainer for us to invest in from the technology side, and we are already seeing tremendous results from the partnership.”
The Latest
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 ...
When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...
Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...
Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...