Network Instruments, a business unit of JDSU, announced the latest edition of its Observer Performance Management Platform.
Observer Platform 17 provides network managers and engineers a comprehensive, intuitive approach to:
- Proactively pinpoint performance problems and optimize services.
- Integrate monitoring into the deployment of IT initiatives, including cloud, service orchestration and security.
- Easily manage access and share performance data with IT teams and business units.
- Quickly assess and optimize user experience with web services.
This performance management solution also features redesigned, easy-to-use interfaces and workflows, expanded web user visibility, increased transactional intelligence, and enhanced integration with third-party tools and applications.
“The Observer 17 release uniquely positions the Platform for the future of IT and the network manager’s evolving role as a primary enabler of technology adoption throughout the enterprise and as a key troubleshooter,” said Charles Thompson, CTO for Network Instruments. “Other IT teams are looking to the network team for greater application troubleshooting and support. Utilizing the newest features in Observer, they are well prepared for their constantly changing role by achieving quicker root-cause analysis, understanding applications in-depth, and easily sharing performance data with non-network teams.”
Key enhancements include:
- Intuitive, drag-and-drop interface and streamlined workflows transform Network Performance Management from an ad hoc practice to a proactive, collaborative process. IT can now manage, monitor, and assess performance in two clicks.
- Third-party system integration via Representational State Transfer (RESTful) APIs facilitate easier sharing of performance intelligence with other groups, as well as integration of monitoring technologies for successful service orchestration for cloud, Software-Defined Networking (SDN) and virtual deployments.
- Enhanced Web Services Analytics provide greater insight into how end users are experiencing web services through expanded client-based and comparative details.
- Deeper transaction-level intelligence and correlative analysis allow for quicker and more effective application troubleshooting. With access to greater granularity, network teams are able to more easily assess relationships between transaction details and other performance variables for a higher degree of actionable insights.
The new Observer Platform features allow network professionals a more productive tool to stay on top of key IT trends and challenges such as:
- IT Automation—As businesses increasingly transition to automated, self-service IT models involving the deployment of cloud, SDN and virtualized environments, these dynamic services are often being implemented without adequate monitoring. To minimize the ‘black holes’ created when users roll out or move IT services and resources without the network team’s knowledge, the new Observer Platform ties together the provisioning of IT resources with the automatic deployment of monitoring tools via RESTful API for complete visibility.
- IT Alignment Across the Business—In delivering Unified Communications and Big Data initiatives, application teams now turn to network teams to lead the charge for metrics, intelligence and app problem solving, and troubleshooting. RESTful APIs and improvements in user management make it easier to integrate Observer 17 into external workflows and processes to help share network performance data with non-network teams.
- Monitoring Mobile Experience—With movements to the cloud and increased access to web services by end users on mobile devices, Observer 17 brings a higher level of visibility and insight into how they are experiencing web services, regardless of the device. Observer now provides comparative visibility by browser type and operating system, alongside performance metrics, to determine if the user experience is the same via a desktop or mobile device.
Observer Platform 17 is currently available and includes Observer Apex (previously called Observer Reporting Server), Observer Management Server (formerly called Network Instruments Management Server), Observer GigaStor, Observer Analyzer, and Observer Infrastructure products.
The Latest
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 ...
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 ...