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Elastic Announces General Availability of Elastic Cloud Serverless on Microsoft Azure

Fast to start and easy to scale, Elastic Cloud Serverless brings security, observability, and search with decoupled storage, fast, low-latency querying, and zero infrastructure hassle

Elastic announced the general availability of Elastic Cloud Serverless on Microsoft Azure. 

This release expands the reach of Elastic Cloud Serverless, giving developers more flexibility to deploy powerful generative AI, search, security, and observability workloads in the environments they already use.

Built on Elastic’s industry-first Search AI Lake architecture and leveraging Azure Blob Storage and Azure Kubernetes Service (AKS), Elastic Cloud Serverless combines vast storage, separate storage and compute, low-latency querying, and advanced AI capabilities to deliver uncompromising speed and scale.

“Elastic Cloud Serverless utilizes Azure Kubernetes Service (AKS) for its underlying platform,” said Qi Ke, corporate vice president at Microsoft Azure. “AKS reduces operational overhead and provides vast autoscaling capabilities to allow developers to tackle GenAI use cases with greater ease and speed to market. We’re delighted to partner with Elastic in support of our joint customers.”

“With our fully managed Elastic Cloud Serverless on Azure, customers can unlock the full value of their data without the burden of managing infrastructure,” said Ken Exner, chief product officer at Elastic. “Native integration with services like Azure Blob Storage, Event Hubs, and Azure Active Directory gives users streamlined data workflows with the low-latency querying and powerful search and AI relevance capabilities of Elasticsearch.”

Key benefits of Elastic Cloud Serverless on Azure include:

  • Decoupled storage and compute: Scale workloads independently with a design that balances cost and performance in high-demand scenarios.
  • Separation of search and indexing: Optimize for diverse use cases by independently scaling index and search tiers with optimized hardware for each use case.
  • Low-latency even on object stores: Low-latency search on vast datasets using segment-level query parallelization and intelligent caching.
  • Fully managed experience: Users are freed from operational tasks with the elimination of cluster management, capacity planning, and upgrades.
  • Usage-based pricing: Customers pay only for what they use — whether ingesting and retaining data in Elastic Security and Observability or using compute in Elasticsearch.

Support for Elastic Cloud Serverless on Microsoft Azure is available now in the East US region. Elastic plans to expand serverless availability to more Azure regions and introduce new features that further enhance performance and usability. 

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Elastic Announces General Availability of Elastic Cloud Serverless on Microsoft Azure

Fast to start and easy to scale, Elastic Cloud Serverless brings security, observability, and search with decoupled storage, fast, low-latency querying, and zero infrastructure hassle

Elastic announced the general availability of Elastic Cloud Serverless on Microsoft Azure. 

This release expands the reach of Elastic Cloud Serverless, giving developers more flexibility to deploy powerful generative AI, search, security, and observability workloads in the environments they already use.

Built on Elastic’s industry-first Search AI Lake architecture and leveraging Azure Blob Storage and Azure Kubernetes Service (AKS), Elastic Cloud Serverless combines vast storage, separate storage and compute, low-latency querying, and advanced AI capabilities to deliver uncompromising speed and scale.

“Elastic Cloud Serverless utilizes Azure Kubernetes Service (AKS) for its underlying platform,” said Qi Ke, corporate vice president at Microsoft Azure. “AKS reduces operational overhead and provides vast autoscaling capabilities to allow developers to tackle GenAI use cases with greater ease and speed to market. We’re delighted to partner with Elastic in support of our joint customers.”

“With our fully managed Elastic Cloud Serverless on Azure, customers can unlock the full value of their data without the burden of managing infrastructure,” said Ken Exner, chief product officer at Elastic. “Native integration with services like Azure Blob Storage, Event Hubs, and Azure Active Directory gives users streamlined data workflows with the low-latency querying and powerful search and AI relevance capabilities of Elasticsearch.”

Key benefits of Elastic Cloud Serverless on Azure include:

  • Decoupled storage and compute: Scale workloads independently with a design that balances cost and performance in high-demand scenarios.
  • Separation of search and indexing: Optimize for diverse use cases by independently scaling index and search tiers with optimized hardware for each use case.
  • Low-latency even on object stores: Low-latency search on vast datasets using segment-level query parallelization and intelligent caching.
  • Fully managed experience: Users are freed from operational tasks with the elimination of cluster management, capacity planning, and upgrades.
  • Usage-based pricing: Customers pay only for what they use — whether ingesting and retaining data in Elastic Security and Observability or using compute in Elasticsearch.

Support for Elastic Cloud Serverless on Microsoft Azure is available now in the East US region. Elastic plans to expand serverless availability to more Azure regions and introduce new features that further enhance performance and usability. 

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As artificial intelligence (AI) adoption gains momentum, network readiness is emerging as a critical success factor. AI workloads generate unpredictable bursts of traffic, demanding high-speed connectivity that is low latency and lossless. AI adoption will require upgrades and optimizations in data center networks and wide-area networks (WANs). This is prompting enterprise IT teams to rethink, re-architect, and upgrade their data center and WANs to support AI-driven operations ...

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...

In MEAN TIME TO INSIGHT Episode 15, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Do-It-Yourself Network Automation ... 

Zero-day vulnerabilities — security flaws that are exploited before developers even know they exist — pose one of the greatest risks to modern organizations. Recently, such vulnerabilities have been discovered in well-known VPN systems like Ivanti and Fortinet, highlighting just how outdated these legacy technologies have become in defending against fast-evolving cyber threats ... To protect digital assets and remote workers in today's environment, companies need more than patchwork solutions. They need architecture that is secure by design ...