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Blue Medora Adds 24 New Endpoint Integrations for BindPlane

Blue Medora announced 24 new endpoint integrations for BindPlane. BindPlane addresses the common challenge most data center operations teams experience – gaining a comprehensive view of what’s going on across their IT ecosystem. BindPlane dramatically expands observability for large enterprises monitoring microservices, Microsoft Azure cloud environments and next-generation infrastructures. Since its introduction in February, the catalog of BindPlane endpoint integrations has grown more than 25%. BindPlane automatically discovers external relationship metadata, seeing any new relationship information instantaneously and creating a full-stack relationship map. When shared with the analytics platform through the Dimensional Data stream, this map helps the platform and its users sound the alarm more accurately. BindPlane creates new or additional relationships and discovers dependencies as more endpoints are added to the full IT stack across heterogeneous enterprise data centers and cloud stacks on demand. Specific integrations used for distributed containerized environments released during this period include: Kubernetes, Docker Swarm, Kafka, Mesos, Pure Storage, Isilon, NetApp Solidfire, NetApp Hyper-Converged Infrastructure, and Palo Alto Networks. “We believe a strategy of high-velocity innovation is required to solve the challenges of managing hybrid cloud environments,” explains Christian Fernando, vice president of product, Blue Medora. “A critical element is decoupling data collection from specific analytics platforms. This unlocks new levels of visibility into better metrics, which in turn frees platform providers to build a better platform. Performance metrics must include their relationship to other components in the IT stack to truly provide insights, so completing these multiple endpoint integrations is key.” BindPlane eliminates silos for customers adopting Azure and AWS infrastructure services. It standardizes metrics between clouds and allows organizations to analyze them using third-party performance monitoring or analytics software to better understand the true cost of cloud services and to identify the best cloud for specific applications. BindPlane translates all metrics from a given endpoint into Blue Medora’s proprietary ExUno universal data language, making it compatible with any monitoring platform and every use case (alerts, dashboards, reports, etc.). The result is a standard integration layer that delivers universally accessible insights from any cloud to every analytics platform within the organization. Specific integrations used for Azure cloud monitoring released during this period include: Azure Storage, Azure Table Storage, Azure Blob Storage, Azure File Storage, Azure Queue Services, Azure Search, Azure Batch, Azure Load Balancer, Azure Functions, Azure Web Apps, Azure Resource Groups, Azure Database for MySQL, Azure Database for PostgreSQL, Azure Cost Management, Azure Redis Cache and Azure Event Hub.

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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 ...

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Blue Medora Adds 24 New Endpoint Integrations for BindPlane

Blue Medora announced 24 new endpoint integrations for BindPlane. BindPlane addresses the common challenge most data center operations teams experience – gaining a comprehensive view of what’s going on across their IT ecosystem. BindPlane dramatically expands observability for large enterprises monitoring microservices, Microsoft Azure cloud environments and next-generation infrastructures. Since its introduction in February, the catalog of BindPlane endpoint integrations has grown more than 25%. BindPlane automatically discovers external relationship metadata, seeing any new relationship information instantaneously and creating a full-stack relationship map. When shared with the analytics platform through the Dimensional Data stream, this map helps the platform and its users sound the alarm more accurately. BindPlane creates new or additional relationships and discovers dependencies as more endpoints are added to the full IT stack across heterogeneous enterprise data centers and cloud stacks on demand. Specific integrations used for distributed containerized environments released during this period include: Kubernetes, Docker Swarm, Kafka, Mesos, Pure Storage, Isilon, NetApp Solidfire, NetApp Hyper-Converged Infrastructure, and Palo Alto Networks. “We believe a strategy of high-velocity innovation is required to solve the challenges of managing hybrid cloud environments,” explains Christian Fernando, vice president of product, Blue Medora. “A critical element is decoupling data collection from specific analytics platforms. This unlocks new levels of visibility into better metrics, which in turn frees platform providers to build a better platform. Performance metrics must include their relationship to other components in the IT stack to truly provide insights, so completing these multiple endpoint integrations is key.” BindPlane eliminates silos for customers adopting Azure and AWS infrastructure services. It standardizes metrics between clouds and allows organizations to analyze them using third-party performance monitoring or analytics software to better understand the true cost of cloud services and to identify the best cloud for specific applications. BindPlane translates all metrics from a given endpoint into Blue Medora’s proprietary ExUno universal data language, making it compatible with any monitoring platform and every use case (alerts, dashboards, reports, etc.). The result is a standard integration layer that delivers universally accessible insights from any cloud to every analytics platform within the organization. Specific integrations used for Azure cloud monitoring released during this period include: Azure Storage, Azure Table Storage, Azure Blob Storage, Azure File Storage, Azure Queue Services, Azure Search, Azure Batch, Azure Load Balancer, Azure Functions, Azure Web Apps, Azure Resource Groups, Azure Database for MySQL, Azure Database for PostgreSQL, Azure Cost Management, Azure Redis Cache and Azure Event Hub.

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 ...