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Panzura Delivers High Performance Log Analytics Service with up to 75% Cost Savings

The Only Multi-Cloud Log Analytics Platform Delivering Always-On Availability, One-Click Deployment and Flexible Scale at a Fraction of the Cost of Splunk

Panzura, the leader in multi-cloud data services, announced the immediate availability of its Log Analytics Service (LAS) within the platform. Based on the unique Block Object Storage technology (VBOS), Log Analytics Service solves the growing IT challenge of ingesting, storing, analyzing and managing rapidly expanding log data sets across the organization.  LAS is available on, a powerful multi-cloud data services platform delivering data search, analytics and insights at an affordable price.

“AppBrilliance’s disruptive financial transactions platform needed a log analytics service that could scale to support hundreds of millions of transactions per day,” said Eric Smith AppBrilliance CEO.  “We chose because of its simplicity, scalability and security. We simply consume it as an API and automatically scales while keeping our log data hot and immediately searchable for as long as needed. Plus it uses open-source Elasticsearch which our developers love.”

Digital transformation has driven explosive growth in users, apps and logs. IT Operations need to constantly manage terabytes of logs generated across the company. Elasticsearch enables rapid data ingestion, indexing and visualization; however, scaling to enterprise use cases is costly due to support, performance and security issues.

Traditional log analytics platform such as Splunk’s typically rely on proprietary technologies and require hands-on management. Customers need to create server clusters, index nodes, dedicate storage pools for the aggregated log size, assign tiering of data and more.

Read More: JRNI Closes $6 Million Series C Extension, Bringing Total Series C Funding to $19.4 Million is the only platform that allows users to leverage the power of Elasticsearch while freeing IT staff from managing nodes, shards, replicas, tiering and other deployment details by abstracting the infrastructure layer. ensures long-tail, always-on data access and delivers peace of mind to IT teams. Customers do not have to make the trade-off between keeping the logs they want or keeping only what they can afford, compromising data compliance and security requirements. empowers IT operations to address log retention and compliance needs while lowering costs up to 75 percent.

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Key differentiators of include:

  • Five minute visualization – Visualize your data in less than five minutes and customize your alerts
  • Never delete data – Never delete or take your data offline so it is always available for search, analytics and machine learning
  • Flexible deployment – Choose your managed service option of private or public cloud based on security, compliance and big data requirements with one-click deployment of Elasticsearch/ELK and apps, dashboards and connectors

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“The core advantage of our Log Analytics Service is the block object storage,” said Geoff Tudor, VP and GM, at Panzura. “This allows enterprises to save logs for a longer period of time without becoming too costly. Data is kept hot and searchable but is stored on low-cost object storage which is typically 10x cheaper than machine data stored on flash. This not only adds value to the enterprise, but it also reduces the cost of storage and allows for larger, searchable data sets.”

Customers leverage the platform for use cases such as system health monitoring, application performance monitoring, real-time incident response, security information and event management (SIEM), IoT and more. Building on the successful launch of File Search Service and for Elasticsearch, the launch of Log Analytics Service further delivers customer value by solving a critical customer need for log management. is now available in AWS, through Panzura’s CSP partner phoenixNAP and as a privately managed version for highly compliant data sets. leverages AWS Open Distribution for Elasticsearch to provide full ELK stack compatibility.

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