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Circonus Announces Availability of Spring 2020 Release

Circonus announced its Spring 2020 release. The highlight of the release is a Kubernetes monitoring solution that provides health-based alerting and horizontal pod auto-scaling. Additional enhancements include cloud monitoring, GCP Marketplace availability, performance improvements, and a more comprehensive Terraform integration. With these latest enhancements, Circonus becomes the only solution that can collect and analyze IT infrastructure, application, and container data at extreme scale across cloud, on-prem, and hybrid deployments — all in one platform. The Circonus Kubernetes monitoring solution lets enterprises monitor one or more Kubernetes clusters. It provides turnkey dashboards and alerting for increased visibility into cluster performance and health, and drives dynamic Kubernetes horizontal pod auto-scaling strategies that can be custom-tuned to the unique needs of an organization. Features include: - Easy-to-install agent - Immediate, real-time operational and health dashboards - Turnkey alerting for Kubernetes clusters to ensure Kubernetes remains healthy - Health-check insights such as crash loops, disk and memory pressure, job and volume failures, errors, pod pending delays, and deployment glitches - Native StatsD collection support - Horizontal pod auto-scaling What makes auto-scaling with Circonus unique is the ability to drive auto-scaling based on rich historical data analysis that customers have stored within Circonus — driving efficient, novel auto-scaling in a way that no other solution currently can. As a result, organizations can create dynamic auto-scaling strategies that will ensure optimal performance, reduce costs, and save time. Circonus’s cloud monitoring solution includes a cloud agent that provides a lightweight binary through which to easily collect metrics from Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP), as well as in-application dashboards. Customers can instantly move all of their metrics from multiple clouds into a single platform, enabling them to run queries, set alerts, and compare data from a single place. The Spring release also includes: - Performance improvements: Customers can now run analytic queries upon thousands of application metrics in near real time for unprecedented visibility into application performance - Comprehensive Terraform integration: Extension, documentation, and other improvements have been made to Circonus’s native Terraform provider - High availability metric ingestion: The Circonus cluster broker is designed to share the load of metric ingestion across multiple brokers, creating a fail-safe if one goes down - UI refresh: The UI has experienced a refresh with the addition of dark mode as well as responsive behavior across mobile devices “Unlike traditional monitoring tools, the Circonus machine data intelligence platform was purpose-built to offer unlimited scalability,” said Bob Moul, CEO, Circonus. “It can ingest, store, and analyze trillions of measurements a second in real-time across billions of individual metric streams. This allows today’s enterprises to gain levels of valuable insights that were previously untapped, enabling them to improve the performance of their IT infrastructure, prevent issues before they arise, optimize processes, and make better business decisions.”

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Circonus Announces Availability of Spring 2020 Release

Circonus announced its Spring 2020 release. The highlight of the release is a Kubernetes monitoring solution that provides health-based alerting and horizontal pod auto-scaling. Additional enhancements include cloud monitoring, GCP Marketplace availability, performance improvements, and a more comprehensive Terraform integration. With these latest enhancements, Circonus becomes the only solution that can collect and analyze IT infrastructure, application, and container data at extreme scale across cloud, on-prem, and hybrid deployments — all in one platform. The Circonus Kubernetes monitoring solution lets enterprises monitor one or more Kubernetes clusters. It provides turnkey dashboards and alerting for increased visibility into cluster performance and health, and drives dynamic Kubernetes horizontal pod auto-scaling strategies that can be custom-tuned to the unique needs of an organization. Features include: - Easy-to-install agent - Immediate, real-time operational and health dashboards - Turnkey alerting for Kubernetes clusters to ensure Kubernetes remains healthy - Health-check insights such as crash loops, disk and memory pressure, job and volume failures, errors, pod pending delays, and deployment glitches - Native StatsD collection support - Horizontal pod auto-scaling What makes auto-scaling with Circonus unique is the ability to drive auto-scaling based on rich historical data analysis that customers have stored within Circonus — driving efficient, novel auto-scaling in a way that no other solution currently can. As a result, organizations can create dynamic auto-scaling strategies that will ensure optimal performance, reduce costs, and save time. Circonus’s cloud monitoring solution includes a cloud agent that provides a lightweight binary through which to easily collect metrics from Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP), as well as in-application dashboards. Customers can instantly move all of their metrics from multiple clouds into a single platform, enabling them to run queries, set alerts, and compare data from a single place. The Spring release also includes: - Performance improvements: Customers can now run analytic queries upon thousands of application metrics in near real time for unprecedented visibility into application performance - Comprehensive Terraform integration: Extension, documentation, and other improvements have been made to Circonus’s native Terraform provider - High availability metric ingestion: The Circonus cluster broker is designed to share the load of metric ingestion across multiple brokers, creating a fail-safe if one goes down - UI refresh: The UI has experienced a refresh with the addition of dark mode as well as responsive behavior across mobile devices “Unlike traditional monitoring tools, the Circonus machine data intelligence platform was purpose-built to offer unlimited scalability,” said Bob Moul, CEO, Circonus. “It can ingest, store, and analyze trillions of measurements a second in real-time across billions of individual metric streams. This allows today’s enterprises to gain levels of valuable insights that were previously untapped, enabling them to improve the performance of their IT infrastructure, prevent issues before they arise, optimize processes, and make better business decisions.”

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IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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