Independent Research Firm Names Elastic a Strong Performer in Artificial Intelligence for IT Operations (AIOps)

Strengths include the ability to consume and process large datasets across a broad array of data types

Elastic (“Elastic”), the company behind Elasticsearch, announced that it has been named a Strong Performer by Forrester Research in The Forrester Wave: Artificial Intelligence For IT Operations, Q4 2022.

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The report evaluates 11 vendors based on 35 criteria grouped into three categories: current offering, strategy, and market presence. Elastic received the highest scores possible in 13 evaluation criteria, including data sources and ingestion, data collection and automation, data retention/tiering/rehydration, mapping – general, distributed tracing, application diagnostics, container monitoring, quantification and validation, discovery and enrichment, prediction and probability, dashboard and reporting capabilities, deployment options, partner ecosystem.

According to Forrester’s evaluation, “Its search-powered solution is enabled by its ability to consume and process large datasets, with extensive native support for a broad array of data types. This strength positions Elastic well in an environment where telemetry data, sources, and cardinality continue to exponentially increase.”

The report also cites that, “Elastic pushes the limits of data management capabilities. Capabilities such as anomaly detection, data correlation, and interactive modeling of large datasets are core to Elastic implementations. Its monitoring support for containers and orchestrators is comprehensive.”

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“Given the expansive nature of today’s observability across complex hybrid and multi-cloud environments, the implementation of AIOps has become crucial for a growing number of IT teams to digest their petabyte-scale telemetry,” said Sajai Krishnan, General Manager, Observability, Elastic. “We believe our recognition in this report, in our first year of consideration, further validates our approach to providing an open, unified solution that offers our customers deep, end-to-end visibility into even their most complex environments so they can detect, investigate, and remediate issues and incidents faster. Our machine learning capabilities and the flexibility for customers to bring their own models to apply across logs, traces, and metrics in an integrated manner sets us up strongly for further advancing AIOps value for our customers.”

Elastic Observability collects, centralizes, and analyzes observability data at scale, delivering full-stack visibility into some of the most complex, cloud-native environments. Users can automate problem resolution and streamline operations with integrated domain-specific machine learning and anomaly detection to reduce time-consuming troubleshooting. Elastic’s out-of-box machine learning underpins observability workflows across log, APM, and metrics data to provide rich context, identify anomalies, and accelerate problem resolution.

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