Fast Time to Insights

From raw data to actionable insights, automatically, to speed time-to-pane for your business data.

The business data generated by applications, services, users, and tools is the lifeblood of business, containing important statistics, correlation, and event details. More of that data is being sent to cloud storage like Amazon S3 or GCP every minute of every hour of every day. To support analysis and insights, it must be indexed quickly, efficiently, and with as little cost and overhead as possible.

The Old Way

Most traditional solutions require work and resources to select, clean, and prepare that diverse data for analysis, transforming it into an analytics-friendly format, then load it into the analytics platform—this is the ETL process. ETL is time-consuming, sometimes taking up to 80% of the time to perform data analytics. It introduces complexity, and increases compute and storage costs, including unexpected costs from training to licensing. It can also create data privacy and compliance gaps, delay insights, and ultimately, limit the value of your data.

The ChaosSearch Way

The core principles of the ChaosSearch “transformational architecture” are aggregation, automation, and activation, emphasizing live data ingestion, where schema detection and indexing is automatic and fully self-governed, removing labor-intensive ETL pipelines, and activating value-driven analytics.

ChaosSearch has two methods for adapting schema and bypassing the ETL tax and data movement needed by other solutions:

  • Easy controls (specified in object groups) for filtering the raw data to ingest, the fields to include for analysis, and automated data typing for fields prior to indexing the data.
  • Post indexing, ChaosSearch transformations and materializations within the lens of a view can virtually tailor the indexed data for specific analysis needs and behaviors needed by the end-user analysts.

Chaos Refinery

Views are defined as part of the Chaos Refinery®, which is comprised of the following components:

  • Abstract lenses (views) for filtering data so that users can focus on specific datasets, across one or more datasets (object groups)
  • Schema-on-write controls to materialize and transform fields within the indexed data to view columns that users want for filtering and analysis, without requiring physical ETL-ing
  • Multi-Model Access where one logical representation (view) provides Search, SQL, and Conversational AI without the time, cost, and complexity of multiple databases

ChaosSearch indexed data is fully searchable and highly performant, able to deliver answers more quickly to analytics queries and summary visualizations.

The ChaosSearch console includes embedded analytics applications such as OpenSearch Dashboards and Apache Superset to provide familiar tools that users can leverage to quickly search, query, and visualize their data. ChaosSearch also supports numerous integrations with existing observability and analysis tools to extend their analytic reach with our longer data history and flexible ChaosSearch analysis capabilities. OpenSearch Dashboards also has alerting support to send notifications when defined conditions are observed in the indexed data. Those alerts can be managed within ChaosSearch and forwarded to some popular alert management systems via supported aggregations.

What’s Next

Read about the benefits of the Chaos Index data design