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Elastic Delivers Cloud-Connected AutoOps for Self-Managed Elasticsearch Users

Elastic announced that AutoOps is now available for the first time for self-managed enterprise users—at no additional cost.

By offloading the heavy lifting to Elastic Cloud, self-managed users gain powerful diagnostic benefits without the overhead of associated infrastructure, also gaining operational insights that improve resource efficiency and lower hardware costs.

“We are always looking to simplify Elasticsearch management to allow developers to focus on building new features instead of troubleshooting issues,” said Ajay Nair, general manager, Platform, at Elastic. “Teams working in self-managed environments can now access the same benefits of AutoOps experienced by Elastic Cloud users.”

AutoOps simplifies cluster management with zero additional overhead. The first in a roadmap of Elastic Cloud connected services for self-managed environments, it runs through a lightweight integration that securely streams operational metadata, such as shard allocations, query latencies, and node utilization to Elastic Cloud. The cloud-powered service processes this telemetry to deliver real-time issue detection and resolution, while the underlying customer data never leaves the self-managed deployment.

Key features for AutoOps include:

  • Simplified cluster management: Delivers real-time cluster insights and automatic detection of ingestion bottlenecks, shard imbalance, and mapping errors so teams can resolve problems before they impact performance.
  • Reduced operational overhead: Eliminates the need to provision and manage a dedicated monitoring cluster. AutoOps data is stored in Elastic's infrastructure and managed by Elastic, freeing teams from additional infrastructure costs and administrative tasks.
  • Cost and resource optimization: Highlights underutilized nodes and inefficient indices, providing clear methods to improve resource utilization and reduce hardware costs.
  • Better support: Elastic Support engineers’ read-only access to AutoOps diagnostics makes support responses faster, as well as more precise resolutions to support tickets.

AutoOps users get the data sovereignty of a self-managed deployment, combined with simplified, proactive operational insights. The platform securely streams operational metadata about cluster workloads to Elastic Cloud, leaving underlying business data within the indices.

“Before using AutoOps, we were spending a significant amount of time manually analyzing nodes, charts, and indices to understand the root cause and determine a solution for issue diagnosis," said Oz Levy, data operations manager at Tipalti. “When we started using AutoOps, it provided actionable intelligence that changed the game; we no longer have to hunt for answers, they get delivered to us right away, along with the solutions to address them.”

AutoOps is available at no additional cost for Enterprise subscription users. Support for AutoOps for self-managed customers is available now. Sign up for an Elastic Cloud Account to get started.

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Elastic Delivers Cloud-Connected AutoOps for Self-Managed Elasticsearch Users

Elastic announced that AutoOps is now available for the first time for self-managed enterprise users—at no additional cost.

By offloading the heavy lifting to Elastic Cloud, self-managed users gain powerful diagnostic benefits without the overhead of associated infrastructure, also gaining operational insights that improve resource efficiency and lower hardware costs.

“We are always looking to simplify Elasticsearch management to allow developers to focus on building new features instead of troubleshooting issues,” said Ajay Nair, general manager, Platform, at Elastic. “Teams working in self-managed environments can now access the same benefits of AutoOps experienced by Elastic Cloud users.”

AutoOps simplifies cluster management with zero additional overhead. The first in a roadmap of Elastic Cloud connected services for self-managed environments, it runs through a lightweight integration that securely streams operational metadata, such as shard allocations, query latencies, and node utilization to Elastic Cloud. The cloud-powered service processes this telemetry to deliver real-time issue detection and resolution, while the underlying customer data never leaves the self-managed deployment.

Key features for AutoOps include:

  • Simplified cluster management: Delivers real-time cluster insights and automatic detection of ingestion bottlenecks, shard imbalance, and mapping errors so teams can resolve problems before they impact performance.
  • Reduced operational overhead: Eliminates the need to provision and manage a dedicated monitoring cluster. AutoOps data is stored in Elastic's infrastructure and managed by Elastic, freeing teams from additional infrastructure costs and administrative tasks.
  • Cost and resource optimization: Highlights underutilized nodes and inefficient indices, providing clear methods to improve resource utilization and reduce hardware costs.
  • Better support: Elastic Support engineers’ read-only access to AutoOps diagnostics makes support responses faster, as well as more precise resolutions to support tickets.

AutoOps users get the data sovereignty of a self-managed deployment, combined with simplified, proactive operational insights. The platform securely streams operational metadata about cluster workloads to Elastic Cloud, leaving underlying business data within the indices.

“Before using AutoOps, we were spending a significant amount of time manually analyzing nodes, charts, and indices to understand the root cause and determine a solution for issue diagnosis," said Oz Levy, data operations manager at Tipalti. “When we started using AutoOps, it provided actionable intelligence that changed the game; we no longer have to hunt for answers, they get delivered to us right away, along with the solutions to address them.”

AutoOps is available at no additional cost for Enterprise subscription users. Support for AutoOps for self-managed customers is available now. Sign up for an Elastic Cloud Account to get started.

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Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...

In a 2026 survey conducted by Liquibase, the research found that 96.5% of organizations reported at least one AI or LLM interaction with their production databases, often through analytics and reporting, training pipelines, internal copilots, and AI generated SQL. Only a small fraction reported no interaction at all. That means the database is no longer a downstream system that AI "might" reach later. AI is already there ...

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UK IT leaders are reaching a critical inflection point in how they manage observability, according to research from LogicMonitor. As infrastructure complexity grows and AI adoption accelerates, fragmented monitoring environments are driving organizations to rethink their operational strategies and consolidate tools ...

For years, many infrastructure teams treated the edge as a deployment variation. It was seen as the same cloud model, only stretched outward: more devices, more gateways, more locations and a little more latency. That assumption is proving costly. The edge is not just another place to run workloads. It is a fundamentally different operating condition ...

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