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Delphix Partners with AppDynamics

Delphix, the pioneer in programmable data infrastructure, announces the availability of an integrated solution aimed at driving application downtime to zero.

The integration combines production application data from Delphix with a customer’s use of application performance monitoring to accelerate service recovery.

“The most serious application issues are the hardest to reproduce and fix,” said Jedidiah Yueh, CEO of Delphix. “They often involve software, integrated applications, and data. Companies need to be able to automatically reproduce application states prior to, during, or after events occur to get services back online.”

Over the last decade, Delphix has built a data platform that collects data across all enterprise apps, from mainframes to cloud-native, and fuels data for cloud, CI/CD, and AI/ML, and other digital transformation programs. Delphix is building on this foundation by providing an integration between its programmable data infrastructure platform with the application performance monitoring insights from AppDynamics.

Once AppDynamics detects an application issue, the integration solution can trigger Delphix to automatically provision the right databases for the affected application from the right point in time. With this new integration solution, customers can leverage Delphix data provisioning within CI/CD and testing environments to help reproduce issues, perform root cause analysis, develop and test fixes, and drastically shorten the time to restore services.

“It is critical for developers and testers to have access to the right datasets within the right data sources in order to quickly reproduce application data and state-related issues,” said Renato Quedas, director of enterprise architecture and strategy, AppDynamics. “Delphix’s programmable data infrastructure makes it significantly faster for their customers to identify, reproduce, and recover from unexpected application issues.”

The integration delivers critical features to improve production operations and site reliability engineering workflows:

- Data Immutability: An immutable data time machine to recreate data in an application environment before, during, or after an event occurs.

- Automated Data for Environments: The ability to automatically provision data into production support environments, combined with APIs to refresh, clean up, bookmark, branch, and share data.

- Topology Based Provisioning and Event Data Analysis: Delphix receives application topology from AppDynamics to determine what data to provision and sends analytics and event data to AppDynamics for dashboarding and querying.

- Environments Deployed via Application Toolchains: When triggered by AppDynamics, Delphix can be proactively integrated with build and automation tools to quickly provide environments to reproduce and fix issues.

- Data Observability: Ability to identify, track, and resolve data-related application issues, such as data loss, data errors, and malicious changes to data, both within applications and across integrated systems.

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Delphix Partners with AppDynamics

Delphix, the pioneer in programmable data infrastructure, announces the availability of an integrated solution aimed at driving application downtime to zero.

The integration combines production application data from Delphix with a customer’s use of application performance monitoring to accelerate service recovery.

“The most serious application issues are the hardest to reproduce and fix,” said Jedidiah Yueh, CEO of Delphix. “They often involve software, integrated applications, and data. Companies need to be able to automatically reproduce application states prior to, during, or after events occur to get services back online.”

Over the last decade, Delphix has built a data platform that collects data across all enterprise apps, from mainframes to cloud-native, and fuels data for cloud, CI/CD, and AI/ML, and other digital transformation programs. Delphix is building on this foundation by providing an integration between its programmable data infrastructure platform with the application performance monitoring insights from AppDynamics.

Once AppDynamics detects an application issue, the integration solution can trigger Delphix to automatically provision the right databases for the affected application from the right point in time. With this new integration solution, customers can leverage Delphix data provisioning within CI/CD and testing environments to help reproduce issues, perform root cause analysis, develop and test fixes, and drastically shorten the time to restore services.

“It is critical for developers and testers to have access to the right datasets within the right data sources in order to quickly reproduce application data and state-related issues,” said Renato Quedas, director of enterprise architecture and strategy, AppDynamics. “Delphix’s programmable data infrastructure makes it significantly faster for their customers to identify, reproduce, and recover from unexpected application issues.”

The integration delivers critical features to improve production operations and site reliability engineering workflows:

- Data Immutability: An immutable data time machine to recreate data in an application environment before, during, or after an event occurs.

- Automated Data for Environments: The ability to automatically provision data into production support environments, combined with APIs to refresh, clean up, bookmark, branch, and share data.

- Topology Based Provisioning and Event Data Analysis: Delphix receives application topology from AppDynamics to determine what data to provision and sends analytics and event data to AppDynamics for dashboarding and querying.

- Environments Deployed via Application Toolchains: When triggered by AppDynamics, Delphix can be proactively integrated with build and automation tools to quickly provide environments to reproduce and fix issues.

- Data Observability: Ability to identify, track, and resolve data-related application issues, such as data loss, data errors, and malicious changes to data, both within applications and across integrated systems.

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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 ...

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