Economical Observability Starts with Smarter Data Management

Eliminate noisy data and reduce costs with
Logz.io’s Data Optimization Manager.

Introducing Logz.io’s Data Optimization Manager

Learn how Dish Network removed 62% of their observability data by filtering out noisy data.

Introducing Logz.io’s Data Optimization Manager

Most telemetry data collected with monitoring and observability tools today is never actually used – creating noisy observability environments and needlessly high ingestion and storage costs.

That’s why we built Data Optimization Manager – a set of capabilities designed to eliminate the noise and focus on the data that matters most, including:

  • Self-service tools – to identify and filter out unneeded data yourself.
  • Hands-on expertise – to help you better understand which data is valuable, and what can be removed.
  • Data storage optimization – to reduce storage costs.
Self-service tools to identify and remove noisy data on the fly
Self-service tools to identify and remove noisy data on the fly

Within the Logz.io platform, take data removal into your own hands with tools designed to quickly find and remove unneeded data:

  • Pattern recognition: turn millions of log lines into tens by clustering similar logs into groups – making it easy to spot duplicated logs or noisy data that doesn’t contain useful information.
  • Easy-to-use data filters: easily remove unneeded data with dynamic data filters that can be turned on and off with a click – all in one place.
  • Data volume monitoring and caps: gain visibility and control over your data volumes by monitoring data usage and capping specific data sets.
Hands-on expertise from Logz.io engineers to eliminate noisy data
Hands-on expertise from Logz.io engineers to eliminate noisy data

Logz.io engineers are always available to provide direct support to customers seeking to remove or declutter noisy data, including:

  • Data review: get a second eye from experienced Logz.io engineers to help you understand which data is valuable, and what can be discarded.
  • Dashboards filtering: why pay for metrics data you don’t monitor? We can filter out all your metrics that aren’t being monitored on specific dashboards.
  • Sampling advice: unsure of what trace sampling to implement? We’ll help you decide the best sampling method for your use case.
The support team is a partner that helps us analyze what we send to become more efficient, especially during our bursty periods.
Amit Zohar
Chief Architect at Blue Dot
Smarter data management to optimize storage costs
Smarter data management to optimize storage costs

Distribute data across multiple Logz.io storage tiers depending on your organization’s specific search performance and cost preferences:

  • Real-time Tier: High-availability and high-performance log storage for your recent logs.
  • Smart Tier: As logs age, move them to the more cost efficient Smart Tier – without any impact on search performance.
  • Historical Tier: Use cheap cloud storage (S3 or Blob) to archive logs for long periods — reingest them back into Logz.io at any time.
2022 Gartner® Magic Quadrant for Application Performance Monitoring and Observability
Forrester Observability Snapshot.