Operations | Monitoring | ITSM | DevOps | Cloud

Elastic at AWS re:Invent: Concluding a year of partnership in agentic AI innovation

Highlights of another laudable year of customer-centric collaboration The integration of Elastic’s capabilities, including vector databases and context engineering, with AWS services helps customers build intelligent, scalable, and secure applications faster and with greater flexibility. Our ongoing collaboration has resulted in another year of notable innovation with AWS. This blog highlights our continued collaboration with AWS throughout 2025 to help you capitalize on the power of AI.

Elastic and Microsoft partnership achievements in 2025

Highlights of another successful year of customer-centric collaboration Once again, our partnership delivered an impressive year of innovation with Microsoft Azure, Azure AI Foundry, and Azure OpenAI. This blog highlights our continued collaboration with Microsoft to better serve customers throughout 2025 and our key moments at Microsoft Ignite.

Observability trends for 2026: Maturity, cost control, and driving business value

The observability landscape has undergone a fundamental transformation over the past several years. In a recent report, The Landscape of Observability in 2026: Balancing Cost and Innovation conducted by Dimensional Research and sponsored by Elastic, over 500 IT decision-makers were surveyed. It revealed that observability has definitively transitioned from an optional capability to a mission-critical business function.

Elastic's move to free on-demand training

Students can now learn what they need within the Elastic stack anytime. The Elastic Training team has shifted its on-demand training strategy from paid to free! Yes, you heard that right — complimentary on-demand training is now readily available to everyone. The Elastic Training team is continuously developing and releasing bite-sized training modules designed to align with Elastic solutions and highlight key features.

Elasticsearch: The context engine for grounding and orchestration in Microsoft Azure AI Foundry Agent Service

The rise of large language models (LLMs) and agentic applications promises to transform enterprise workflows. Yet, the core challenge remains: How do we ensure these powerful agents generate accurate, relevant, and trustworthy responses based on proprietary enterprise data rather than relying solely on their generic training knowledge? The answer lies in grounding — connecting the LLM to verified, trusted, and up-to-date information.

Elastic named a Leader in the IDC MarketScape: Worldwide Observability Platforms 2025 Vendor Assessment

We're proud to share that Elastic has been named a Leader in the IDC MarketScape: Worldwide Observability Platforms 2025 Vendor Assessment (doc, November 2025). We believe this recognition validates our ongoing mission: to deliver an observability platform that is open, extensible, and AI-driven to power full-stack observability that unifies operational and business data at scale, allowing SRE teams to move from detect and resolve problems faster.

Elastic recognized as a finalist for Innovation in Customer Portals in 2025 TSIA STAR Awards

We are proud to announce that Elastic has been named a finalist by the Technology & Service Industry Association (TSIA) in the 2025 STAR Awards program for Innovation in Customer Portals that Improve Digital Customer Experience. This award recognizes Elastic’s ability to embrace AI innovations to enhance our digital customer experience.

Bridging partners in pursuit of agentic AI - Part 2: How leaders can position themselves for the future

From ecosystem foundations to future advantage In Part 1: Why partnerships matter for enterprise intelligence, we explored how enterprises are moving from experimentation to scalable impact with agentic AI and how ecosystems make that possible. But naturally, the next question is: Where do we go from here?

Bridging partners in pursuit of agentic AI - Part 1: Why partnerships matter for enterprise intelligence

The pace of change in AI development has been dizzying. In just a few years, we’ve moved from experimenting with AI, machine learning (ML), retrieval augmented generation (RAG), and agents to asking how these innovations can solve real business problems. Enterprises are no longer impressed by the novelty and possibilities; instead, they expect outcomes.