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Instabug Joins Datadog Marketplace

Instabug announced a new integration with Datadog, now available in the Datadog marketplace.

Datadog consolidates metrics, traces, logs and more to help organizations scale their cloud and hybrid environments, troubleshoot potential issues and provide customers with excellent digital experiences. The Datadog Marketplace connects Datadog customers with unique technology integrations that allow for more customization and flexibility. The Marketplace is a part of the Datadog Partner Network, which features benefits including access to dedicated sales and marketing resources and premium Datadog product training materials.

Building this Datadog offering differentiates Instabug as a Datadog Partner Network (DPN) member that has demonstrated success integrating with Datadog’s products, helping Datadog customers evaluate and use their technology productively, at scale and varying levels of complexity.

The Instabug integration helps mobile teams deliver superior user experiences by giving Datadog users deep insights into the performance of their mobile apps while simultaneously streamlining the collection of user feedback.

Through the Instabug widget, Datadog teams can track an App Apdex score, a single performance metric indicating the mobile user’s perceived quality of the app. The widget also displays specific user feedback, including automatically captured details to help identify the root cause of a bug or crash. These mobile insights help teams understand user-impacting events and—when combined with Datadog’s log analytics and infrastructure monitoring—arm engineering teams with the information needed to prioritize and resolve critical issues quickly.

“Instabug’s integration enables our joint customers to monitor user experiences in their mobile applications,” said Alex Vetras, Senior Product Manager at Datadog. “In addition to the distilled Apdex score, Instabug provides a breakdown of user sessions by level of success and a stream of the most recently filed bug reports. Together with Datadog, customers can now tie Instabug’s user feedback with the underlying infrastructure powering their mobile apps to deliver optimal levels of service.”

“Mobile apps are key to every business’s growth strategy. Mobile developers need an observability stack that combines the best of backend monitoring with a comprehensive view of the mobile user experience,” notes Kenny Johnston, VP Product at Instabug. “As a mobile-first company, Instabug’s expertise lies in helping developers understand, analyze, and enhance the app experience both quantitatively and qualitatively—whether that be crashes, app launch times, app ratings or bug reports. Our integration with Datadog creates a seamless view that enables teams to focus on what matters most to deliver an app that meets their users' increasingly high expectations.”

Instabug is now available for purchase in the Datadog marketplace.

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Instabug Joins Datadog Marketplace

Instabug announced a new integration with Datadog, now available in the Datadog marketplace.

Datadog consolidates metrics, traces, logs and more to help organizations scale their cloud and hybrid environments, troubleshoot potential issues and provide customers with excellent digital experiences. The Datadog Marketplace connects Datadog customers with unique technology integrations that allow for more customization and flexibility. The Marketplace is a part of the Datadog Partner Network, which features benefits including access to dedicated sales and marketing resources and premium Datadog product training materials.

Building this Datadog offering differentiates Instabug as a Datadog Partner Network (DPN) member that has demonstrated success integrating with Datadog’s products, helping Datadog customers evaluate and use their technology productively, at scale and varying levels of complexity.

The Instabug integration helps mobile teams deliver superior user experiences by giving Datadog users deep insights into the performance of their mobile apps while simultaneously streamlining the collection of user feedback.

Through the Instabug widget, Datadog teams can track an App Apdex score, a single performance metric indicating the mobile user’s perceived quality of the app. The widget also displays specific user feedback, including automatically captured details to help identify the root cause of a bug or crash. These mobile insights help teams understand user-impacting events and—when combined with Datadog’s log analytics and infrastructure monitoring—arm engineering teams with the information needed to prioritize and resolve critical issues quickly.

“Instabug’s integration enables our joint customers to monitor user experiences in their mobile applications,” said Alex Vetras, Senior Product Manager at Datadog. “In addition to the distilled Apdex score, Instabug provides a breakdown of user sessions by level of success and a stream of the most recently filed bug reports. Together with Datadog, customers can now tie Instabug’s user feedback with the underlying infrastructure powering their mobile apps to deliver optimal levels of service.”

“Mobile apps are key to every business’s growth strategy. Mobile developers need an observability stack that combines the best of backend monitoring with a comprehensive view of the mobile user experience,” notes Kenny Johnston, VP Product at Instabug. “As a mobile-first company, Instabug’s expertise lies in helping developers understand, analyze, and enhance the app experience both quantitatively and qualitatively—whether that be crashes, app launch times, app ratings or bug reports. Our integration with Datadog creates a seamless view that enables teams to focus on what matters most to deliver an app that meets their users' increasingly high expectations.”

Instabug is now available for purchase in the Datadog marketplace.

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Outages aren't new. What's new is how quickly they spread across systems, vendors, regions and customer workflows. The moment that performance degrades, expectations escalate fast. In today's always-on environment, an outage isn't just a technical event. It's a trust event ...

Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...