This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary". The cookie is used to store the user consent for the cookies in the category "Other. The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". The cookie is used to store the user consent for the cookies in the category "Analytics". These cookies ensure basic functionalities and security features of the website, anonymously. Established providers in this space, according to G2, include Splunk Enterprise, Datadog, Sumo Logic, Logz.io, Dynatrace, LogDNA, New Relic One, Graylog, Progress WhatsUp Gold and LogMonitor.Necessary cookies are absolutely essential for the website to function properly. Explorer is now available in preview for current customers. “Access to full-fidelity logs is a must in dynamic container environments to deliver a flawless application experience,” Ravulur said.ĭataset Kubernetes Explorer came into the market just months after SentinelOne launched its live enterprise platform. He said that they don’t work for modern environments because they are too slow to detect and respond in real time, too siloed for useful insights, too expensive to scale, and too complex to operate. Traditional data platforms were designed decades ago in the pre-cloud era.
“As organizations shift to Kubernetes, the ability to cost-effectively analyze events across the entire cloud stack including applications, container platforms and infrastructure will become the norm, not the exception.” “Dynamic containerized platforms generate a large volume of fast-moving data,” Paul Nashawaty, senior analyst at Enterprise Strategy Group, said in a media advisory. According to KBV Research, the global log management market will grow to $3.3 billion by 2025, rising at an 11% compound annual growth rate (CAGR). Log monitoring, also known as log management, is becoming a crucial component in building next-generation IT infrastructure. “This definitely fits into the ‘observability’ category, in terms of being able to actually find anomalies and identify root-cause issues in order to go in and fix anomalies as they occur.” “Users will be able to very intuitively allow devops and SRE (site reliability engineering) teams to be able to troubleshoot any errors that may be occurring as well,” Ravulur said. Not having overall observability into such complex systems of Kubernetes clusters, containers, data stores and microservices can cost administrators time – and companies money on the bottom line. Dataset Explorer provides an at-a-glance view into all Kubernetes clusters with the flexibility for users to drill down into a particular cluster, namespace, nodes, pods, containers, or deployed workloads in seconds, Ravulur said. Using this visual tool, Kubernetes teams can more easily see and understand the interdependencies of Kubernetes components, detect performance issues, uncover root causes and resolve them, Ravulur said.
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