Expanding its range of observability pipeline solutions, observIQ announces BindPlane OP Cloud BindPlane OP dramatically reduces observability costs and simplifies the management of telemetry agents at scale while avoiding vendor lock-in. It recognizes the explosive growth in telemetry data from multiple sources and vendors in cloud and legacy environments and the need for a standardized, unified telemetry layer.
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BindPlane OP is based on the OpenTelemetry standard, to which observIQ is a top contributor. The cloud version simplifies the setup and maintenance process, making it a fast and easy way to deploy an observability pipeline.
BindPlane OP reduces telemetry data volume, filtering and deduplicating data for greater manageability and lowering the cost of data analytics. It also provides a single control plane with an intuitive interface for managing thousands of agents and the ability to quickly deploy new agents, manage their configurations, and monitor their health in real-time.
observIQ now offers three versions of BindPlane OP:
- BindPlane OP – For those organizations looking to test OpenTelemtery-based observability pipelines. It’s a free open source observability pipeline.
- BindPlane OP Enterprise – A solution for those organizations with high regulatory or security requirements which prevent cloud-based options. It includes roles-based access control, Active Directory and LDAP authentication support, premium processors for reduced observability costs and 24/7 support.
- BindPlane OP Cloud – For those customers wishing to deploy a cloud version with simple setup and deployment as part of their overall cloud framework.
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Quote from Mike Kelly, CEO of observIQ
“As we work with major organizations grappling with massive amounts of telemetry data, we know some require the control of an on prem solution while others prefer the ease-of-deployment of a hosted system. Our goal is to meet the customer where the problem is, so offering these options provides a degree of flexibility and a vendor-neutral solution to rapidly reduce their data costs.”
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