June 2025 Summaries

Airtel, a leading telecommunications provider, is enhancing its managed security services (MSS) by integrating Elastic's AI-driven analytics into its Security Operations Centre (SOC) to deliver advanced threat detection and response capabilities. This collaboration allows Airtel to offer world-class managed security services to its business customers by utilizing Elastic Security's features such as AI Assistant, Attack Discovery, and GenAI-powered analytics. These features enable faster threat detection, smarter incident response, and efficient data onboarding, while also reducing operational costs and improving collaboration between technical teams. Elastic's scalable architecture supports Airtel in managing large volumes of data, ensuring deep visibility and compliance, and automating routine tasks to enhance productivity. By centralizing logs and threat intelligence, Airtel helps enterprises across sectors stay ahead of evolving threats, solidifying its position as a pioneer in the Indian market and a global leader in Elastic-powered security services.

Generative AI is revolutionizing data integration and analytics for the UK Ministry of Defence (MOD) by drastically reducing the time required to convert raw data from the Navy, Army, and Air Force into actionable intelligence. Traditionally a time-consuming task, data integration now takes minutes instead of days, thanks to AI's ability to automate the preparation and integration of custom data sources. This advancement enhances operational decision-making speed and efficiency, enabling a more cohesive analytical ecosystem across military services. By employing a data mesh approach and standardizing datasets through the Elastic Common Schema, the MOD can support greater collaboration and interoperability, allowing for seamless information sharing and more agile analytics. With AI tools like Automatic Import and AI Assistant, the MOD can maintain security and data sovereignty while reducing complexity and improving workforce efficiency, ultimately supporting mission readiness and operational agility.

Elastic has announced the general availability of its Cloud Serverless platform on Microsoft Azure, specifically in the EastUS region, offering a fast and scalable solution for security, observability, and search without the need to manage infrastructure. Built on the Search AI Lake architecture that leverages Azure Blob Storage, this service allows for independent scaling of compute and storage, resulting in optimized performance and cost efficiency. The platform separates search and indexing workloads, enabling reliable scalability with low-latency query performance, even when handling large datasets from object storage. Users can benefit from hassle-free operations due to the elimination of cluster management and capacity planning, and the service operates on a flexible, usage-based pricing model. Elastic plans to extend its serverless offerings to more Azure regions and is working on additional features to enhance performance and usability.

Elastic has introduced its Verified Generative AI Partner certification to help businesses move beyond AI pilot projects to scalable, secure solutions that deliver real value, addressing challenges such as integrating multiple AI models and managing enterprise data. The certification equips partners with comprehensive training in Elastic's AI technologies, enabling them to offer expert guidance, innovative approaches, and strategic support throughout the implementation process. Partners like GIOS Technology, KPMG, Minsait, NTT Data, and Puur Data are now certified, providing tailored solutions and leveraging Elastic's vector database and extensive GenAI integrations with companies like NVIDIA and RedHat. These partners play a crucial role in Elastic’s global AI strategy by offering deep regional expertise and fostering strong customer relationships in Europe and the Middle East. Elastic emphasizes caution when using third-party AI tools, advising users to be aware of privacy practices and potential risks associated with personal data.

Elastic has transitioned its Elasticsearch platform to a serverless architecture with the launch of Elastic Cloud Serverless, aiming to meet changing customer demands for simplified infrastructure management and pay-per-use models. This transformation involved shifting from a stateful to a stateless system by leveraging cloud-native object stores for persistent storage, adopting Kubernetes for orchestration, and employing a cell-based architecture for resilience. The platform also implements custom autoscaling controllers to optimize resource allocation and has developed a flexible pricing model aligned with actual usage. Elastic's approach includes using Crossplane for infrastructure management, addressing networking challenges with Cilium, and ensuring high availability through proactive capacity planning. The company emphasizes a cultural shift towards continuous innovation and automation, positioning Elastic Cloud Serverless as a scalable, efficient, and customer-centric solution for running Elasticsearch, with plans for ongoing feature development to enhance customer experience in the evolving serverless landscape.

The US General Services Administration (GSA) and Elastic, a leading Search AI company, have announced a strategic agreement aimed at modernizing federal IT systems while driving cost savings and enhancing cybersecurity, observability, and AI capabilities across federal agencies. The agreement introduces government-wide pricing for Elastic’s solutions, offering significant volume discounts of up to 60%, thereby streamlining the procurement process and reducing inefficiencies associated with fragmented purchases. This collaboration aligns with broader federal initiatives to improve IT efficiency, emphasizing cost-effectiveness and innovation as outlined in recent executive orders and directives from the US Office of Management and Budget (OMB). Elastic's technology enables agencies to utilize open-source Search AI and a data mesh approach to transform siloed data into actionable insights, supporting initiatives like Zero Trust and GenAI applications. The partnership is expected to facilitate secure, scalable innovation in the public sector, allowing agencies to modernize, secure, and simplify operations without exceeding budget constraints.

Version 8.18.3 of the Elastic Stack has been released, and users are encouraged to upgrade from the previous version 8.18.2. This latest release includes fixes for potential security vulnerabilities, and users are advised to consult the release notes for comprehensive details on the changes and improvements made to each product within the stack. Further information on the security fixes can be found in the accompanying security advisory.

Elastic has been recognized as a Leader in The Forrester Wave™: Security Analytics Platforms, Q2 2025, highlighting its robust capabilities in managing and analyzing data for security and observability. Elastic Security offers a comprehensive platform that includes SIEM, extended detection and response (XDR), cloud monitoring, and more, all powered by the speed and flexibility of Elasticsearch. Notable features include AI-driven analytics, open and community-driven detection engineering, and a flexible economic model that supports hybrid deployments without paywalls. Elastic's platform enables security teams to reduce complexity and improve operational efficiency, offering tools such as federated search, timeline views, and open detection rules tailored to security analysts. The company stresses transparency, with open-source detection rules and traceable AI suggestions, and has entered strategic collaborations, such as with AWS, to enhance its offerings. Elastic's innovations aim to accelerate security and AI advancements, providing security teams with the tools needed for modern challenges, ultimately delivering improved outcomes such as reduced mean time to resolution (MTTR) and better visibility across environments.

Version 8.17.8 of the Elastic Stack was released on June 24, 2025, and users are encouraged to upgrade to this latest version over previous ones, such as 8.17.7. The release includes fixes for potential security vulnerabilities, and details about the issues resolved and changes made for each product in this version can be found in the release notes. Users are advised to consult the security advisory for more comprehensive information on the security updates included in this release.

Elastic Stack version 7.17.29, released on June 24, 2025, by Alina Băcălete, is recommended over its predecessor, version 7.17.28, due to its enhancements and fixes. This latest release addresses potential security vulnerabilities, and users are encouraged to review the release notes and security advisory for comprehensive details on the changes and improvements made to each product within the Elastic Stack.

Version 9.0.3 of the Elastic Stack has been released as of June 24, 2025, and is recommended over the previous version, 9.0.2, due to its inclusion of fixes for potential security vulnerabilities. Users are encouraged to upgrade to this latest version and consult the release notes for a comprehensive list of changes and resolved issues. For more information on security improvements, the security advisory provides further details.

Elastic has integrated generative AI capabilities into its Elastic Cloud platform, enabling features in Elastic Security, Observability, and Search by default, which facilitates seamless access without additional setup or third-party contracts. The Elastic Managed LLM offers automatic threat detection, investigation, and response in security, while in observability, it accelerates root cause analysis and incident response. Developers can rapidly prototype and test GenAI capabilities using Elastic's low-code interface, AI Playground, and Search AI Assistant. Elastic's AI is uniquely integrated with its platform, leveraging retrieval augmented generation (RAG) to enhance responses by sourcing relevant context from organizational knowledge bases, such as runbooks and documentation. With over 400 integrations, Elastic's AI insights are enriched with logs, metrics, and traces, ensuring accurate and actionable results. The platform supports connections to public LLMs for those needing more customization, offering flexibility while maintaining a unified data access approach. Elastic's approach emphasizes speed, control, and customization, providing a production-ready AI stack that aligns with modern team workflows, and emphasizes security and compliance within its ecosystem.

Elastic Extended Security, developed through the acquisition of Endgame, enhances Elastic's Search AI Platform by integrating advanced EDR capabilities to deliver true XDR, correlating data from endpoints, networks, users, and cloud sources at search speed within a unified platform. Elastic's approach eliminates traditional EDR limitations by providing a vendor-agnostic platform that seamlessly integrates third-party tools and offers unlimited agent deployment without hidden costs. The platform includes comprehensive defenses against advanced threats like malware, ransomware, and fileless attacks, utilizing AI-driven features for enhanced detection and response. Elastic ensures transparency by sharing its detection logic and engaging in open research through Elastic Security Labs, which continuously updates protection measures. The solution is recognized for its robust security capabilities, validated by independent testing, and offers a flexible, scalable defense strategy against modern cyber threats without compromising on performance.

Security analysts at the UK Ministry of Defence (MOD) face the challenge of managing an overwhelming number of daily alerts, which often leads to burnout and inefficiencies. The MOD's AI strategy aims to address these issues by leveraging AI to automate and enhance data analysis, thereby improving productivity and reducing the workload on analysts. AI tools like AI Assistant and Attack Discovery help distill thousands of alerts into actionable intelligence, allowing analysts to focus on critical threats. This integration of AI aims to streamline security operations, reduce costs, and support the MOD's goal of implementing a Zero Trust Architecture by 2026. By unifying data from various sources, the MOD seeks to create a comprehensive view of security threats and enhance decision-making capabilities, ultimately transforming how security teams operate and respond to threats.

The Ministry of Defence's (MOD) Defence Data Management Strategy, introduced in 2020, aims to treat data as a strategic asset, prioritizing its integration and usability alongside developing skilled personnel and positioning Defence as data leaders. As the 2025 target approaches, efforts continue to overcome challenges such as siloed systems and the complexities of AI accessing sensitive data, necessitating robust accountability and visibility measures. The strategy includes six data management rules focusing on data sovereignty, standardization, exploitation, security, curation, and retention, all of which aim to enhance operational efficiency and decision-making. Elastic's solutions are highlighted as instrumental in achieving these goals by providing comprehensive visibility, auditability, and protection across data lifecycles, enabling Defence to manage data effectively while maintaining compliance and fostering innovation through collaboration with partners and allies.

In 2025, generative AI is becoming a key player in transforming enterprise search capabilities, transitioning from mere proof of concept to practical application. Accenture and Elastic have formed a strategic partnership to leverage AI-powered search tools that unify structured and unstructured data, thereby enhancing decision-making and reducing manual research efforts. This collaboration aims to optimize search relevance and retrieval quality through multistage approaches and advanced AI models, ultimately increasing the return on corporate data. The partnership emphasizes the importance of a vectorized and optimized data foundation and highlights the significance of integrating Elastic's scalable search technology with Accenture's industry expertise. As generative AI continues to evolve, the focus is on creating agentic frameworks that automate and enhance decision-making processes, positioning organizations for long-term value and competitiveness.

Elastic Cloud Serverless has been launched on Google Cloud in the new regions of Belgium and Mumbai, offering a rapid and scalable solution for observability, security, and search without the need for infrastructure management. Built on the Search AI Lake architecture, it leverages Google Cloud Storage to provide vast storage, separate storage and compute, low-latency querying, and advanced AI capabilities. Users can quickly initiate projects via the Elastic Cloud console, choosing between Belgium or Mumbai, and can also manage their subscriptions through the Google Cloud Marketplace, with costs tied to usage. Elastic plans to expand to more regions and introduce new features, emphasizing its commitment to delivering speed, scale, and cost-efficiency without compromise.

Integrating artificial intelligence (AI) and machine learning (ML) into national security mission systems is becoming increasingly essential to enhance monitoring and IT resilience, yet significant data challenges such as silos, security gaps, and outdated IT infrastructure must first be addressed. A strategic collaboration between AWS, Anthropic, and Elastic aims to overcome these challenges by providing advanced AI capabilities for observability, anomaly detection, and root cause analysis, which are crucial for ensuring operational resilience and security risk mitigation. By automating routine tasks and optimizing data management, this partnership enables site reliability engineers to focus on strategic priorities, thereby boosting productivity and enhancing the efficiency of defense and intelligence operations. Elastic's Search AI Platform plays a pivotal role by offering AI-driven automation, efficient data tiering, and comprehensive observability, which improves user satisfaction and developer productivity. Additionally, the collaboration provides robust infrastructure support from AWS, state-of-the-art AI/ML models from Anthropic, and intelligent data management from Elastic, ensuring that national security operations remain agile and responsive to emerging threats.

Modern defense networks face challenges in overcoming data silos, as critical data is dispersed across various domains, including land, sea, air, space, and cyber environments, making seamless collaboration difficult. Traditionally, centralizing data has been a complex and risky task, often leading to inefficiencies and security vulnerabilities. A new approach using a data mesh architecture allows interoperability without the need for costly data migrations, enabling secure data sharing and analysis across diverse systems while maintaining data sovereignty. This method enhances operational efficiency by allowing analysts to perform cross-cluster searches, retrieving unified results from multiple sources without moving the data itself, significantly reducing response times and bandwidth requirements. Elastic's Search AI Platform is highlighted as a solution that facilitates this interoperability, helping defense organizations transform operational data into actionable intelligence quickly, thereby providing a strategic advantage in rapidly evolving digital battlefields.

Elastic Security achieved a perfect score of 100% in the AV-Comparatives Business Security Test, excelling in both the Real-World Protection Test and the Malware Protection Test, which underscores its effectiveness in protecting businesses against modern cyber threats. The AV-Comparatives tests are rigorous, simulating 220 complex attack scenarios and using a dataset of 1,018 unique malware samples to evaluate security solutions beyond basic malware detection. Elastic Security's superior performance demonstrates its advanced capabilities in threat detection and prevention, highlighting its commitment to providing robust cybersecurity without compromising system performance. The solution incorporates extended detection and response (XDR) technology, offering a comprehensive view of security across endpoints, networks, and cloud environments, which helps organizations improve detection rates and reduce response times. Elastic Security's platform is designed to optimize performance and provide seamless integration with daily operations, ensuring efficient and effective protection against increasingly sophisticated threats.

Defence organizations, including the UK Ministry of Defence (MoD), face challenges from disjointed security tools and siloed data that lead to inefficiencies and increased costs, while also managing threats from cyber attacks. Elastic Security offers a unified platform using AI-driven Security Information and Event Management (SIEM) to streamline threat detection, reduce false positives, and cut incident response times, resulting in significant cost savings. The data mesh approach by Elastic helps break down data silos without compromising security, enhancing interoperability and maintaining necessary access controls. This strategy supports the MoD's Defence Data Strategy by enabling cross-domain investigations and reducing storage costs, ultimately improving operational resilience. Elastic's technology facilitates integrating multiple cloud environments securely, allowing defence agencies to optimize costs while maintaining strict security standards. Additionally, the platform's AI capabilities reduce administrative burdens by automating compliance processes, supporting the Digital MOD.UK's mission to unify security standards. Overall, Elastic's solutions promise a reduction in the total cost of ownership and improved efficiency, which are critical for modernizing and securing defence operations.

Adhish Thite, a lead AI engineer at Elastic, has a career that spans from India to Silicon Valley and North Carolina, ultimately returning to Pune, India. Known for his childhood curiosity about technology, which earned him the nickname "Tech-nificent Adhish," he has developed a methodical approach to work, relying on a meticulously arranged workspace featuring a MacBook Pro and Apple Studio Display. Adhish employs techniques like the Pomodoro Technique for productivity and maintains a balance between work and personal growth by journaling daily achievements. His role at Elastic involves leading the development of ElasticGPT, a generative AI solution aimed at enhancing internal workflows, which has received positive feedback from users. Adhish is also active in the developer community, engaging with peers through platforms like GitHub and LinkedIn, and embracing the "build in public" movement to refine his projects. Despite his accomplishments, Adhish continues to nurture his curiosity and creativity, believing in the potential of technologies like Elasticsearch to transform data into actionable insights.

Assigning custom data view IDs in Kibana is advocated as a best practice to avoid chaos in collaborative environments, where multiple users might create similar data views with random, auto-generated IDs. By using intuitive and consistent custom IDs, such as those that reflect the dataset or environment, teams can prevent the fragmentation that occurs when visualizations become tied to unique and easily forgotten random IDs. This approach facilitates easier recovery of visualizations if a data view is deleted, as recreating the data view with the same custom ID restores the associated visualizations. Through an example using data from "Young Sheldon," the importance of this practice is highlighted, illustrating how custom IDs reduce complexity and improve workflow efficiency in larger teams, helping to maintain order and avoid the breakdown of dashboards caused by the deletion of data views with arbitrary IDs.

Elastic has achieved the AWS Education ISV Partner Competency, reinforcing its reputation as a provider of high-quality solutions for education institutions, with a focus on digital transformation through Search AI and cloud innovation. This recognition highlights Elastic's capabilities in delivering secure and scalable solutions that enhance student outcomes, operational resilience, and security operations for both K–12 and higher education institutions. Elastic's Search AI Platform leverages generative AI and an AI-optimized architecture to empower educational organizations to extract insights from vast data troves while maintaining flexibility and security. The competency also attests to Elastic's success in aiding educational institutions with AI, machine learning, and data analytics technologies, enabling them to innovate and address complex IT challenges. The company's expanding suite of AWS competencies demonstrates its commitment to advancing digital transformation across various sectors, including government, financial services, and security.

Version 8.17.7 of the Elastic Stack has been released, as announced by Panagiotis Sfendourakis on June 3, 2025. Users are encouraged to upgrade to this latest version, which is preferred over the previous 8.17.6 release. For a comprehensive list of changes and issues addressed in this update, users are advised to consult the release notes.

Version 9.0.2 of the Elastic Stack has been released, and users are encouraged to upgrade to this latest version over the previous 9.0.1 release. For comprehensive details on the issues addressed and a complete list of changes for each product in this version, users are directed to consult the release notes.