Near Real-time Log Analytics

Create a cloud-native log analytics solution

Challenges

  • High cost: expensive volume-based pricing model, not for historical data or long-term data storage 
  • Slow time-to-analytics: hire and train highly-skilled technical resources to implement and maintain a complex technology stack 
  • Lack of cloud-nativeness: insufficient scalability and elasticity requires excessive maintenance and IT overhead
  • Vendor lock-in: unable to easily choose or change preferred tools to work with and lack of SQL processing capabilities
  • Preparatory data format: processing is limited to vendor specific offerings, sharing data with other services is nearly impossible

Solutions

  • Cost reduction by minimizing log data across batch and streaming by storing long-term data on Amazon S3, filtering, aggregating and transforming data before being indexing without any adding developers
  • Fast time-to-analytics by using a visual, SQL based interface directly stream data from cloud sources without complex architectures or hiring additional staff
  • Seamless integration with other cloud services to iterate quickly when adding new features and capabilities to achieve continuous delivery
  • Open Cloud Lakehouse engine provides users with a centralized cost-effective storage with access to any processing engines
  • Centralized cloud object storage supports any file format that allows sharing with any non-vendor specific services

Leveraging Upsolver

Reduce cost with Cloud object storage

Stream and transform tens of thousands of events per second on cloud in real-time. Only load hot data to log analytics applications to minimize cost. Use Cloud object storage to store the entire log history and replay data as needed.

Accelerate time-to-analytics with a visual, SQL-based interface

Plug-n-play solution that utilizes a visual, SQL-based interface to get up and running within hours without having to hire additional developers. Onboarding new and complex data structures, parse schema on read at the push of a button.

Integrate with any analytics solutions

Could-native open lakehouse engine integrates and scales seamlessly with any log analytics, SQL or Machine Learning solutions.

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