February 2026 Summaries

Version 8.19.12 of the Elastic Stack has been released, and users are encouraged to upgrade from the previous version, 8.19.11, due to important security vulnerability fixes included in this update. The release notes provide a comprehensive list of changes and issue resolutions for each product within this version. Users are advised to refer to the security advisory for detailed information about the addressed vulnerabilities.

Version 9.2.6 of the Elastic Stack was released, featuring important fixes for potential security vulnerabilities, making it a recommended upgrade over version 9.2.5. Users are advised to consult the security advisory for detailed information on the vulnerabilities addressed and to refer to the release notes for a comprehensive list of changes and issues resolved in this latest version.

Colsubsidio, a prominent family compensation fund in Colombia, successfully transformed its business process monitoring by implementing Elastic Observability, addressing the challenges of isolated monitoring systems and limited technical visibility. This integration allowed the organization to unify logs, metrics, traces, and business events across more than 40 critical processes, leading to a 30% reduction in mean time to recovery (MTTR) and a 95% decrease in critical incidents. With centralized telemetry and end-to-end traceability, Colsubsidio improved API response times by 30% and reduced integration errors by 25%, resulting in enhanced service stability and availability for over one million users. The adoption of Elastic as the official enterprise observability platform not only improved operational efficiency and business continuity but also accelerated Colsubsidio's digital transformation and bolstered its reputation as a leader in technological innovation in Colombia.

Version 9.3.1 of the Elastic Stack was released on February 26, 2026, and is recommended over the previous version 9.3.0 due to fixes for potential security vulnerabilities. Users are encouraged to upgrade to this latest version to benefit from these security enhancements. Detailed information about the fixed issues and a comprehensive list of changes for each product in this release can be found in the release notes.

Elastic AutoOps is now available for free to all Elasticsearch users, offering automated root cause analysis and performance insights to enhance the management of Elasticsearch environments. This tool provides real-time diagnostics and operational insights without the need for additional infrastructure, allowing users to optimize resource utilization and reduce mean time to resolution (MTTR) by quickly identifying and addressing performance issues. Elastic AutoOps connects to Elastic Cloud via Cloud Connect and operates by transforming operational metadata into actionable intelligence, ensuring business data remains secure within user environments. It simplifies setup with a lightweight agent, enabling a centralized view of multiple clusters and providing customizable alerts without the need for separate monitoring infrastructure. The tool is beneficial for a wide range of users, from developers to team leads, by offering insights that help prevent outages, optimize resources, and support decision-making in dynamic, high-stakes environments. An example of its effectiveness is demonstrated by Tipalti, a global payables automation leader, which achieved a 10% annual cost saving by using AutoOps to optimize resources and prevent outages.

Elastic has announced the availability of new CPU Optimized and Storage Optimized ARM hardware profiles powered by AWS Graviton4 processors on Elastic Cloud Hosted, which offer improved price-performance for Elastic Cloud workloads. The CPU Optimized profile provides up to 15% better price-performance for CPU-bound tasks, while the Storage Optimized profile offers up to 40% gains for data-intensive workloads, enhancing compute efficiency and data processing without requiring changes to existing operations. These profiles are designed for users running observability, security, and search workloads, and are available in select AWS regions. Users can create new deployments or migrate existing ones to these ARM profiles via the Elastic Cloud console, with detailed guidance available in Elastic's documentation.

Elastic Cloud Serverless has expanded its availability on Microsoft Azure, doubling its presence to eight regions globally, including new locations in East US 2, Southeast Asia, Spain Central, and Germany West Central. This fully managed, stateless architecture offers users the power of Elasticsearch without the need for infrastructure management, allowing for quick scaling and access to advanced features like retrieval augmented generation and threat hunting. The platform's dynamic auto-scaling capability accommodates large data volumes and complex queries, while its usage-based pricing model ensures cost efficiency. Elastic Cloud Serverless, built on Azure Blob Storage, boasts a 99.95% monthly uptime SLA and emphasizes reliability and flexibility, enabling users to focus on applications with confidence. As part of its ongoing commitment to innovation, Elastic continues to enhance its serverless solutions on Azure, inviting users to experience the future of search, security, and observability.

The Elastic Support Hub has introduced a self-service feature that allows users to instantly check the impact of third-party Common Vulnerabilities and Exposures (CVEs) on their Elastic deployments, enhancing their ability to filter out unnecessary alerts from security scanners and confirm Elastic’s official assessments. This feature, built on Elastic’s vulnerability management program, provides users with direct access to a comprehensive database of security statements, enabling them to perform primary reviews without needing to file support tickets. Users can search for CVE impact statements using the Native Search bar or the Elastic Support Assistant, which employs retrieval augmented generation to efficiently retrieve relevant data. While the Support Assistant is optimized for bulk CVE checks, it is recommended to break down larger lists to fit the system's capacity. The Elastic Support Hub aims to streamline the process of assessing security vulnerabilities by bridging the gap between Elastic's security researchers and users, ensuring that the information available is both accurate and actionable.

Elastic has introduced Elastic Serverless Plus, an add-on to Elastic Cloud Serverless, which enhances connectivity, security, and control for critical regulated workloads. The key feature of this add-on is the integration with AWS PrivateLink, allowing enterprises to maintain strict network isolation and secure data transmission within a virtual private cloud, which is crucial for sectors like finance, healthcare, and government. This feature supports a Zero Trust Architecture, ensuring data remains on the AWS backbone without traversing the public internet, thereby simplifying compliance with standards such as SOC 2, HIPAA, and PCI-DSS. The add-on also offers operational benefits, including reduced data transfer costs and consistent latency, by routing traffic through AWS PrivateLink, treating Elastic deployments as local VPC resources. Currently available in the Observability Complete and Security Analytics Complete tiers with no additional charge during the promotional period, the add-on will later incur a 10% upcharge based on consumption. Elastic plans future enhancements, including multicloud network security and encryption at rest with customer-managed keys, with features subject to Elastic's discretion regarding release timing and availability.

Elastic{ON} London 2026, scheduled for February 26, aims to address challenges faced by UK business leaders, such as rapid AI innovation, increasing security expectations, and fragmented data, by emphasizing the role of developers, engineers, analysts, and architects in solving these issues. The event will focus on the transition from passive AI to agentic AI, highlighting the importance of context engineering, which involves providing AI with relevant, real-time data for accurate actions. Pre-event workshops and networking opportunities on February 25 will offer attendees deep dives into the Elastic Stack, AI-driven security, and generative AI applications. Key tracks and sessions during the event will cover the latest trends in search, observability, and security, translating technical capabilities into business growth, and leveraging Elastic for secure, scalable data insights in the public sector. Attendees are encouraged to set clear objectives, engage with Elastic engineers and partners, and prioritize comfort for a productive day of learning and networking.

Full-stack observability is increasingly recognized as a strategic tool for IT leaders in the Gulf Cooperation Council (GCC) to achieve operational resilience, faster return on investment (ROI), and digital maturity amidst the complexities of hybrid IT environments. The integration of AI-powered insights and automation within observability tools addresses challenges such as visibility gaps and data silos, which are prevalent in regions like Saudi Arabia and the UAE due to rapid digital transformation and diverse technology ecosystems. By providing comprehensive visibility across infrastructure, applications, and data layers, observability facilitates proactive management, aligns IT performance with business objectives, and supports compliance with regional governance requirements. This capability is crucial for Gulf organizations striving to maintain a competitive edge in a fast-evolving market. Observability also enhances service delivery through improved incident resolution and reduced downtime, while enabling IT leaders to demonstrate the financial impact of technical initiatives by linking them directly to business outcomes. Overcoming deployment challenges such as cost overruns and overwhelming data generation is essential for maximizing the potential of observability, ensuring that it remains a cornerstone of digital transformation efforts in the region.

AI-driven observability is emerging as a critical component of mission resilience in the public sector, addressing the challenges posed by complex IT environments, data governance, and the need for continuous monitoring across diverse systems. Downtime, with its potential to erode public trust, necessitates a shift from traditional monitoring to a more resilient model that includes AI and data mesh architecture. This approach ensures compliance, data sovereignty, and cost efficiency while providing real-time insights into system performance and security. AI enhances observability by automating anomaly detection and correlating signals, thereby enabling faster diagnostics and response to issues before they impact citizens. Open standards like OpenTelemetry foster interoperability and transparency, reducing technical friction and enhancing collaboration. By aligning observability with mission outcomes, public sector IT can evolve from a support function to a strategic partner, ensuring uptime and trust in government services.

The February 2026 Elastic DevRel newsletter highlights the release of version 9.3 of Elasticsearch and the Elastic Stack, showcasing several advancements including the general availability of the Elastic Agent Builder for AI agent development, pattern-based log compression, and expanded model availability in the Elastic Inference Service. The update introduces enhancements in vector storage, GPU acceleration, and analytics performance, while Elastic Workflows, an automation engine in Kibana, is featured for building automation with defined triggers and steps. Additionally, Elasticsearch 9.3 supports bfloat16 vector storage, offering reduced memory usage for high-dimensional embeddings, and expands GPU support for vector-heavy tasks. ES|QL receives improvements for time-series analytics, enhancing performance and stability for metrics queries. The newsletter also promotes various blogs, videos, and upcoming events, including an Agent Builder hackathon and the Elastic{ON} Tour conference series, emphasizing opportunities for community engagement and showcasing the latest developments and practical applications within the Elastic ecosystem.

Elastic has launched a Public Roadmap on GitHub to increase transparency and collaboration by providing developers with visibility into upcoming features, capabilities, and enhancements for their products. This initiative aims to prevent redundant development work by allowing users to see what the company is planning, thus helping them align their projects accordingly. The roadmap, rooted in Elastic's open-source ethos, offers a calendar view segmented by development stages and includes navigational aids such as key initiatives and solution-specific tabs. It also features a search function to explore specific releases or ongoing developments. Elastic encourages regular visits to the roadmap for updates, although the timing and delivery of new features remain at the company's discretion.

AI is advancing rapidly, reshaping how organizations build, defend, and operate systems, but this speed presents challenges, as operational, economic, and regulatory structures struggle to keep pace, creating pressures that demand resilient architectures. Organizations must invest in foundational systems that remain stable amid rapid innovation, as history shows that technology waves like nuclear power and the dot-com boom eventually stabilize around durable infrastructure. Elastic provides a solution by offering a stable, governed operational foundation that integrates seamlessly with AI innovations, ensuring organizations can manage change without unnecessary risk. Elastic's platform supports unified visibility, open AI integration, and resilient operations, allowing organizations to adapt quickly while maintaining stability, thus securing investments in an unpredictable environment.

OpenTelemetry (OTel) is increasingly recognized as the standard for observability, with major companies like AWS and Google transitioning from proprietary agents to OTel standards. The widespread adoption is hindered by challenges in execution, as many organizations mistakenly treat OTel as a simple tool replacement rather than a new operational model. A strategic blueprint for successful OTel adoption emphasizes the importance of context over mere vendor agnosticity, recommending a "Collector First" architecture that decouples data generation from destination and utilizes both automatic and manual application instrumentation. The approach involves a gradual migration using the strangler pattern, beginning with Kubernetes, to avoid disruptions in IT environments. Organizations are encouraged to operationalize OTel with clear ownership of schemas and pipelines, ensuring schema consistency and validation to maintain data usability and compliance. As OpenTelemetry becomes the default standard, it is crucial to adopt strategies that prioritize context, consistency, and gradual migration to future-proof observability architectures.

Matt Nowzari, a software engineer at Elastic based in North Carolina, focuses on integrating external data into Elasticsearch using tools like Open Crawler, Elastic connectors, and Agent Builder. Passionate about open-source development and community engagement, Matt believes innovation is driven by collaboration and encourages developers to actively participate in the open-source community. Outside of his professional endeavors, he is an avid car enthusiast, participating in autocross events and aspiring to become a certified track instructor. His work routine includes a balance of communication with European teammates in the morning and deep-focus work in the afternoon, supported by a well-organized workspace featuring a MacBook Pro, an ultrawide monitor, and a mechanical keyboard. Matt leverages tools like VS Code and AI integrations for code review and refinement, while music aids in maintaining a steady workflow. He is intrigued by the potential of Agent Builder in Kibana for transforming how users interact with data, and envisions creating a searchable knowledge base for older car repairs if given the opportunity.

Generative AI (GenAI) and OpenTelemetry (OTel) are increasingly crucial in reshaping the observability landscape, as evidenced by a report surveying over 500 IT decision-makers. GenAI adoption is projected to reach 98% within two years, driven by its ability to automate pattern recognition and query telemetry in plain language, although its current application faces challenges like security concerns and potential misinformation. Meanwhile, OpenTelemetry's adoption, while currently modest, is accelerating, with vendor compliance and OTel's integration becoming essential criteria for observability platforms. The convergence of GenAI and OTel is influencing vendor selection, with integrated capabilities, comprehensive support, and security measures becoming requirements, thus positioning vendors who invest in these technologies advantageously in the evolving observability market.

Elastic Workflows is a new automation engine integrated directly into Elasticsearch, designed to unify scripted automation and AI-driven processes while eliminating the need for external integrations. This system addresses the limitations of traditional automation, which often requires separate data management and lacks adaptability, by providing a seamless approach that combines reliable, predictable execution with AI's flexible reasoning capabilities. Elastic Workflows is defined in YAML, allowing for version control and real operational logic, and is event-driven, enabling it to respond to data changes, external events, or user actions. By natively integrating with Elastic Agent Builder, it empowers AI agents to take concrete actions within an organization's systems, enhancing decision-making and reducing the complexity of automation tasks. This integration benefits various roles, such as security analysts and operations teams, by providing structured processes with AI-supported insights, resulting in faster issue resolution while maintaining oversight and control. Currently available as a technical preview, Elastic Workflows aims to bring automation closer to operational data, ensuring reliability and flexibility while simplifying architecture and reducing the need for complex integrations.

Version 9.2.5 of the Elastic Stack was released, and users are encouraged to upgrade from the previous version, 9.2.4. For comprehensive information on the issues addressed and the complete list of changes across the products included in this release, users should consult the release notes.

Version 8.19.11 of the Elastic Stack has been released, and users are encouraged to upgrade from the previous version, 8.19.10. This latest release addresses various issues and includes a comprehensive list of changes across each product, as detailed in the release notes.

Elastic 9.3 introduces several new features and improvements to the Elasticsearch Platform, enhancing its capabilities in data transformation, AI, observability, and security. This release includes Elastic Workflows for integrating workflow automation, Elastic Agent Builder for developing custom AI agents, and GPU-accelerated vector indexing for improved data processing. It also brings AI-powered tools like the Jina AI models for faster multilingual embeddings and reranking. In observability, new integrations with Amazon Bedrock and enhancements to Elastic Streams facilitate AI-assisted log parsing and root cause analysis. Elastic Security sees upgrades with features like Entity AI Summary for risk assessment and improved detection and response automation. The Elasticsearch Platform continues to bridge enterprise data with AI experiences, offering advanced analytics and automation, while Elastic Cloud Serverless expands its global reach with performance boosts. Overall, Elastic 9.3 aims to provide developers and practitioners with a robust and scalable platform for enhanced data management and AI applications.