# opensearch Published articles for opensearch. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Linux Foundation Newsletter: September 2026 DevFeed: [Linux Foundation Newsletter: September 2026]() Original publisher: [Read original article]() Author: andrewb@proximabiz.com (The Linux Foundation) Published: 2026-09-17T14:49:43Z Content type: news Language: en Sources: [Linux Foundation - Blog]() Topics: [linux foundation](), [MCP](), [Artificial Intelligence](), [Open Source](), [Xen](), [opensearch](), [Cybersecurity]() Tags: [2026](), [blog](), [careers](), [cybersecurity](), [education](), [lf-europe](), [lf-events](), [lf-research](), [linux](), [linux-blog](), [linux-foundation](), [mcp](), [newsletter](), [open-source](), [open-source-summit](), [opensearch](), [project-news](), [projects](), [september-2026](), [tech-talent]() ### AI overview The September 2026 Linux Foundation Newsletter highlights upcoming AGNTCon and MCPCon North America, developments in agentic AI and AI-agent infrastructure, Xen safety and security work, OpenSearch recognition, and LF Energy research, projects, and community updates. ### Source excerpt Welcome to the September 2026 edition of the Linux Foundation Newsletter The open agentic AI community is coming together in San Jose for AGNTCon + MCPCon North America, October 22-23. More than 3,500 developers, researchers, maintainers and technical leaders will gather for 150 sessions across 11 tracks focused on MCP, agent infrastructure, security, interoperability and production agent systems. Register by October 8 to save. Beyond the event, six developments stand out this month. TheAgentic AI Foundation welcomed the Gates Foundation as its first philanthropic member, bringing the perspectives of underserved communities into the development of agentic AI and supporting broader participation in the firstMCP Dev Summit Nairobi. The Linux Foundation welcomed TRACE, an open specification developed with AMD, Anthropic, Intel, Microsoft, NVIDIA, OPAQUE and TII to provide portable, verifiable runtime and compliance evidence for AI agents and confidential workloads. TheXen Project launched the Xen Safety Committee to develop shared engineering artifacts for functional safety certification and extended security coverage for Xen releases to five years.OpenSearch won the Analytics & Data Intelligence Solutions category in SiliconANGLE's2026 TechForward Awards as the project celebrates five years of community growth. NewLF Energy research found that open source software can deliver two to five times greater net value for grid operators and introduced a standardized framework for evaluating those investments. LF Energy also welcomed three new members and three new projects, advanced Power Grid Model to Early Adoption after more than 10 million downloads, and documented how TenneT achieved a tenfold improvement in grid security analysis performance with PowSyBl. You'll also find new Linux Foundation research, training and certification opportunities, registration for upcoming events, and project news spanning cloud native, AI, energy, cybersecurity, automotive, telecommunicat ## FIPS 140-3 support in OpenSearch DevFeed: [FIPS 140-3 support in OpenSearch]() Original publisher: [Read original article]() Author: Karsten Schnitter Published: 2026-09-16T19:12:14Z Content type: article Language: en Sources: [OpenSearch]() Topics: [fips 140-3](), [opensearch](), [Cryptography](), [Encryption](), [Security]() Tags: [aws](), [blog](), [compliance](), [cryptography](), [encryption](), [fips](), [fips-140-3](), [opensearch](), [security](), [technical]() ### AI overview This post explains OpenSearch support for a FIPS 140-3-compliant mode starting with version 3.6. It describes the validated cryptographic modules used for security-relevant operations, the collaboration involving SAP, SAS, and AWS, and how native FIPS mode differs from using a FIPS-validated TLS-terminating proxy. ### Source excerpt OpenSearch now supports running in a mode compliant with FIPS 140-3, contributed through a multi-year collaboration between SAP, SAS, and AWS. The post FIPS 140-3 support in OpenSearch appeared first on OpenSearch. ## And the winners are: Announcing the results of the OpenSearch Agent Skills Hackathon DevFeed: [And the winners are: Announcing the results of the OpenSearch Agent Skills Hackathon]() Original publisher: [Read original article]() Author: James McIntyre Published: 2026-09-14T23:00:09Z Content type: article Language: en Sources: [OpenSearch]() Topics: [Agent Skills](), [Hackathon](), [Code]() Tags: [agent-skills](), [audit](), [blog](), [github](), [hackathon](), [latency](), [opensearch](), [root-cause-analysis](), [technical]() ### AI overview This OpenSearch article announces the winners of the OpenSearch Agent Skills Hackathon. It describes the competition requirements and judging criteria, then highlights the first-place Unclosed skill, which performs auditable log root-cause analysis through premise audits, hypothesis trees, and closure checks. ### Source excerpt Meet the three winners of the OpenSearch Agent Skills Hackathon. Their skills tackle log root-cause analysis, GDPR compliance, and slow-query diagnostics, all built read-only, fully auditable, and shipped with real evaluation. The post And the winners are: Announcing the results of the OpenSearch Agent Skills Hackathon appeared first on OpenSearch. ## OpenSearch Wins Analytics & Data Intelligence Solutions Category in the SiliconANGLE TechForward Awards DevFeed: [OpenSearch Wins Analytics & Data Intelligence Solutions Category in the SiliconANGLE TechForward Awards]() Original publisher: [Read original article]() Author: Kristi Piechnik Published: 2026-09-14T12:00:14Z Content type: news Language: en Sources: [OpenSearch]() Topics: [Open Source](), [AI Infrastructure](), [observability](), [AI search](), [Security](), [Retrieval Augmented Generation (RAG)](), [Databases](), [real-time]() Tags: [2026](), [agentic-ai](), [ai-agents](), [ai-infrastructure](), [announcements](), [awards](), [data](), [enterprise](), [observability](), [open-source](), [opensearch](), [real-time](), [recognition](), [retrieval](), [retrieval-augmented-generation-rag](), [search](), [security]() ### AI overview OpenSearch won the Analytics & Data Intelligence Solutions category in SiliconANGLE Media's 2026 TechForward Awards. The recognition highlights its open source, vendor-neutral platform for enterprise search, observability, security analytics, vector databases, and agentic AI workloads. ### Source excerpt Recognition validates open source momentum, architectural consolidation, and enterprise scale as the project marks five years of community growth The post OpenSearch Wins Analytics & Data Intelligence Solutions Category in the SiliconANGLE TechForward Awards appeared first on OpenSearch. ## A visual guide to troubleshooting search performance using Query Insights dashboards DevFeed: [A visual guide to troubleshooting search performance using Query Insights dashboards]() Original publisher: [Read original article]() Author: Chenyang Ji Published: 2026-09-04T20:11:52Z Content type: tutorial Language: en Sources: [OpenSearch]() Topics: [Amazon OpenSearch Service](), [dashboards](), [Monitoring](), [Latency](), [cpu]() Tags: [blog](), [configuration](), [cpu](), [dashboards](), [distribution](), [how-to](), [index](), [latency](), [memory](), [monitoring](), [navigation](), [opensearch](), [performance](), [real-time](), [technical](), [troubleshooting](), [view](), [visualization]() ### AI overview A visual guide to using OpenSearch Query Insights dashboards to investigate slow searches and unexpected resource usage. It covers the Live Queries and Top N Queries views, interactive visualizations, configuration, and metrics such as latency, CPU, and memory. ### Source excerpt OpenSearch Query Insights dashboards provide interactive visualizations for monitoring live queries, analyzing top N query performance, and viewing individual query details. This post explores each visualization and shows how to use visualizations to troubleshoot search performance issues. The post A visual guide to troubleshooting search performance using Query Insights dashboards appeared first on OpenSearch. ## Online index migration and shard scaling in OpenSearch with the AOSC plugin DevFeed: [Online index migration and shard scaling in OpenSearch with the AOSC plugin]() Original publisher: [Read original article]() Author: Arpit Singla Published: 2026-08-18T21:56:28Z Content type: article Language: en Sources: [OpenSearch]() Topics: [Amazon OpenSearch Service](), [migration](), [Open Source](), [Routing (disambiguation)]() Tags: [blog](), [mapping](), [migration](), [open-source](), [opensearch](), [pipeline](), [plugin](), [production](), [reconciliation](), [routing](), [schema](), [technical](), [workflow]() ### AI overview This article introduces Automatic Online Schema Change (AOSC), an open-source OpenSearch plugin for migrating live indexes to pre-created targets with different mappings, settings, shard counts, or document shapes. It backfills existing documents, replays operations made during migration, and switches an alias after a short write block, while documenting its scaling behavior and limitations. ### Source excerpt Learn how the open-source AOSC plugin migrates live OpenSearch indexes--changing mappings, settings, or shard counts--without losing writes or requiring downtime. The post Online index migration and shard scaling in OpenSearch with the AOSC plugin appeared first on OpenSearch. ## From Search to Search & Apache Lucene: Growing the heart of OpenSearchCon DevFeed: [From Search to Search & Apache Lucene: Growing the heart of OpenSearchCon]() Original publisher: [Read original article]() Author: Kris Freedain Published: 2026-08-14T21:57:12Z Content type: article Language: en Sources: [OpenSearch]() Topics: [Library](), [Maintainers]() Tags: [2026](), [apache](), [blog](), [community](), [event](), [opensearch](), [search]() ### AI overview Community feedback led OpenSearchCon to expand its Search track into Search & Apache Lucene, creating a dedicated forum for Lucene practitioners, maintainers, and search relevance experts. The article describes the revised track and the strong response to its call for presentations for OpenSearchCon North America 2026. ### Source excerpt Learn how community feedback transformed OpenSearchCon's Search track into a dedicated home for Apache Lucene practitioners. Discover the new Search & Apache Lucene track at OpenSearchCon North America 2026, September 22-24 in San Jose. The post From Search to Search & Apache Lucene: Growing the heart of OpenSearchCon appeared first on OpenSearch. ## Introducing memory retention for agentic memory in OpenSearch DevFeed: [Introducing memory retention for agentic memory in OpenSearch]() Original publisher: [Read original article]() Author: Erfan Ballew Published: 2026-08-13T22:29:25Z Content type: article Language: en Sources: [OpenSearch]() Topics: [Amazon OpenSearch Service](), [AI Agent](), [audit trail](), [model-deployment]() Tags: [agentic](), [audit-trail](), [blog](), [compliance](), [cost](), [experimental](), [lifecycle](), [memory](), [opensearch](), [precision](), [retention](), [storage](), [technical]() ### AI overview This article explains OpenSearch 3.8's experimental memory retention feature for agentic memory. It describes age-based and count-based limits for different memory types, how policies prevent stale context and uncontrolled storage growth, and how to enable retention on an existing cluster. ### Source excerpt Learn how the memory retention policy in OpenSearch automatically manages the lifecycle of agentic memory, controlling storage growth while preserving specific memories. The post Introducing memory retention for agentic memory in OpenSearch appeared first on OpenSearch. ## Building open-source observability together: The OpenSearch Observability TAG turns one DevFeed: [Building open-source observability together: The OpenSearch Observability TAG turns one]() Original publisher: [Read original article]() Author: Dotan Horovits Published: 2026-08-11T17:01:57Z Content type: article Language: en Sources: [OpenSearch]() Topics: [observability](), [Open Source](), [OpenTelemetry](), [Prometheus](), [agent observability]() Tags: [agent-observability](), [blog](), [cncf](), [community](), [metrics](), [observability](), [open-source](), [opensearch](), [opentelemetry](), [prometheus]() ### AI overview The OpenSearch Observability Technical Advisory Group marks its first anniversary after a year of community-driven guidance, RFC reviews, architecture decisions, and collaboration across organizations. The article highlights work involving OpenTelemetry, Prometheus, Perses, KEDA, Kubernetes, and the OpenSearch Observability Stack, and explains how contributors can participate in the group's second year. ### Source excerpt The OpenSearch Observability TAG's first year: 10+ orgs shipped OTLP ingestion, Prometheus metrics, an open-source Observability Stack, and AI agent observability. The post Building open-source observability together: The OpenSearch Observability TAG turns one appeared first on OpenSearch. ## What's new in OpenSearch 3.8 DevFeed: [What's new in OpenSearch 3.8]() Original publisher: [Read original article]() Author: James McIntyre Published: 2026-08-05T00:50:11Z Content type: release Language: en Sources: [OpenSearch]() Topics: [opensearch](), [Artificial Intelligence](), [observability](), [Model Context Protocol](), [Large Language Model]() Tags: [ai](), [blog](), [large-language-model](), [mcp](), [observability](), [opensearch](), [performance](), [release]() ### AI overview OpenSearch 3.8 adds broader Model Context Protocol integration, lower-latency streaming machine-learning predictions over gRPC, faster vector ingestion and radial search, expanded large-language-model provider support, and new tools for log and time-series analysis. ### Source excerpt OpenSearch 3.8 expands the platform's search, AI, and observability capabilities with enhanced vector performance, broader agent integrations, and new tools to help you simplify analytics workflows from ingestion to investigation. The post What's new in OpenSearch 3.8 appeared first on OpenSearch. ## Agentic relevance tuning: Letting LLM agents do the search engineering work DevFeed: [Agentic relevance tuning: Letting LLM agents do the search engineering work]() Original publisher: [Read original article]() Author: Kylie Wagar-Dirks Published: 2026-07-31T15:00:47Z Content type: article Language: en Sources: [OpenSearch]() Topics: [Amazon OpenSearch Service](), [Large Language Model](), [Framework](), [data](), [Deployment]() Tags: [2026](), [agents](), [aws](), [blog](), [data](), [deployment](), [evaluation](), [framework](), [llm-agents](), [opensearch](), [ranking](), [search]() ### AI overview The article introduces Agentic Relevance Tuning (ART), an end-to-end framework that uses specialized LLM-powered agents to automate search relevance improvement in OpenSearch. ART monitors user behavior, proposes ranking changes, runs offline evaluations, and coordinates deployment when improvements are validated. ### Source excerpt At OpenSearchCon Europe 2026, Bobby Mohammed (AWS) and Daniel Wrigley (OpenSource Connections) introduced Agentic Relevance Tuning (ART), a framework that uses specialized LLM agents to fully automate the search relevance lifecycle in OpenSearch. The post Agentic relevance tuning: Letting LLM agents do the search engineering work appeared first on OpenSearch. ## Connect OpenSearch to private ML endpoints DevFeed: [Connect OpenSearch to private ML endpoints]() Original publisher: [Read original article]() Author: Nathalie Jonathan Published: 2026-07-28T15:00:41Z Content type: tutorial Language: en Sources: [OpenSearch]() Topics: [Amazon OpenSearch Service](), [network security](), [VPC](), [inference-endpoints](), [Security](), [AWS IAM](), [Latency](), [Self-hosted](), [Amazon Web Services]() Tags: [aws](), [aws-identity-and-access-management-iam](), [blog](), [firewalls](), [inference](), [infrastructure](), [opensearch](), [production](), [self-hosted](), [vpc]() ### AI overview This guide explains how to connect OpenSearch and Amazon OpenSearch Service to machine learning models hosted on private infrastructure. It covers VPC-hosted endpoints, private SageMaker endpoints, internal API gateways, and self-hosted inference servers, with configuration steps for connectors, model registration, deployment, testing, and VPC egress. ### Source excerpt Connect OpenSearch to ML models hosted on private infrastructure. Configure ML Commons connectors for VPC-hosted endpoints, private SageMaker models, and internal inference servers without exposing services to the public internet The post Connect OpenSearch to private ML endpoints appeared first on OpenSearch. ## The forbidden index: Building privacy-preserving search with OpenSearch DevFeed: [The forbidden index: Building privacy-preserving search with OpenSearch]() Original publisher: [Read original article]() Author: Kylie Wagar-Dirks Published: 2026-07-24T15:00:22Z Content type: article Language: en Sources: [OpenSearch]() Topics: [Open Source](), [Access Control](), [pii](), [dashboards](), [tokenization](), [data](), [elasticsearch](), [Framework]() Tags: [analytics](), [analytics-stack](), [blog](), [compliance](), [dashboards](), [data](), [dynamic-data](), [open-source](), [opensearch](), [pii](), [plugin](), [privacy](), [search](), [tokenization]() ### AI overview The article describes a talk by Unnati Mishra and Akshat Khanna on building privacy-preserving search and analytics with OpenSearch. Their approach moves privacy controls into the ingest layer, using a custom plugin to redact PII at index time through tokenization and dynamic data masking. It also applies differential privacy to OpenSearch Dashboards by adding calibrated noise to aggregate query results. ### Source excerpt At OpenSearchCon Europe 2026, Unnati Mishra and Akshat Khanna (Angel One) argued that privacy in search must be handled during the ingest phase rather than retroactively through access controls. The post The forbidden index: Building privacy-preserving search with OpenSearch appeared first on OpenSearch. ## Blinkit at OpenSearchCon India 2026 DevFeed: [Blinkit at OpenSearchCon India 2026]() Original publisher: [Read original article]() Author: Harshit Prasad Published: 2026-07-24T10:16:24Z Content type: article Language: en Sources: [Grofers]() Topics: [opensearch](), [migration](), [linux foundation]() Tags: [2026](), [architecture](), [blinkit](), [community](), [conference](), [data](), [distributed-systems](), [engineering](), [india](), [keynote](), [linux-foundation](), [migration](), [opensearch](), [scale](), [search](), [software-engineering]() ### AI overview Blinkit describes its OpenSearchCon India 2026 keynote, including its migration from a single OpenSearch cluster to a multi-cluster architecture, the production challenges encountered, and the trade-offs and lessons shared with the community. ### Source excerpt A few weeks ago, we spoke at OpenSearchCon India about how we make search fast and reliable at scale at Blinkit. I'm Harshit, from the Search Engineering team at Blinkit, and this year we got to speak at OpenSearchCon India at the Jio World Convention Centre in Mumbai. In this post, I'll walk you through our talk, the conversations that followed, and what our team took away from being part of the OpenSearch community in a more active way this year. First Day : Keynote by Blinkit The highlight of this year's conference for our team was the opportunity to deliver a keynote session at OpenSearchCon, organised by the Linux Foundation. Along with my fellow engineer Bharti Sawaria we walked the audience through our journey of migrating from a single OpenSearch cluster to a multi-cluster architecture. We shared the challenges we faced, the solutions that failed in production, and our key learnings for the community. We also discussed Blinkit's growing scale & the trade-offs we made during our migration. To provide context for our global audience, we framed the talk around the sheer scale at which we operate, highlighting the "breaking point" where we realised a single cluster could no longer handle our needs. Bharti explaining about OpenSearch Multi-Cluster ArchitectureHarshit explaining about the OpenSearch Single-Cluster Architecture The official keynote talk video can be found on Youtube : https://medium.com/media/774b8379733c6442d3ecaa3976c2191e/hrefThe Experience at OpenSearchCon Beyond the breakout sessions, the real value of OpenSearchCon was connecting with engineers from across the industry. Many of whom are dealing with similar scale and freshness challenges, openly sharing what's worked and what hasn't. That kind of unfiltered peer exchange is hard to replicate online. Our team attended multiple breakout sessions and had several great discussions with engineers from Uber, Freshworks, Oracle, and others. A few sessions stood out enough to flag once recordings are ## Managing Databases on Kubernetes Requires Platform Engineering and Automation DevFeed: [Managing Databases on Kubernetes Requires Platform Engineering and Automation]() Original publisher: [Read original article]() Author: Oliver Wolf Published: 2026-07-21T15:00:00Z Content type: opinion Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack]() Topics: [Kubernetes](), [Databases](), [Platform Engineering](), [internal developer platform](), [Provisioning](), [opensearch](), [Redis]() Tags: [anynines](), [automation](), [backups](), [databases](), [devops](), [internal-developer-platform](), [kubernetes](), [monitoring](), [opensearch](), [platform-engineering](), [post](), [provisioning](), [redis](), [sponsor-anynines](), [sponsored-post]() ### AI overview The article argues that application teams should not be expected to manage the full operational burden of databases and data services on Kubernetes. It recommends internal developer platforms and Kubernetes-native automation so developers can request services while centralized systems handle provisioning, backups, patching, monitoring, recovery, and governance. ### Source excerpt The DevOps movement, set in motion nearly 20 years ago, broke down the traditional divide between software developers and IT The post Kubernetes made deploying easy. Nobody warned you about the databases. appeared first on The New Stack. ## Data Engineering Weekly #276 DevFeed: [Data Engineering Weekly #276]() Original publisher: [Read original article]() Author: Ananth Packkildurai Published: 2026-06-29T03:52:17Z Content type: article Language: en Sources: [Data Engineering Weekly]() Topics: [data-engineering](), [schema-evolution](), [data-architecture](), [Amazon OpenSearch Service](), [Resilience](), [data observability]() Tags: [architecture](), [compatibility](), [data-engineering](), [engineering](), [observability](), [opensearch](), [resilience](), [schema-evolution]() ### AI overview Data Engineering Weekly #276 is a newsletter roundup covering data platform fundamentals, storage and workload architecture, schema evolution in Pinterest's ingestion framework, zone-failure-resilient OpenSearch at Uber, AI modernization, and stateful reasoning systems for notebooks. ### Source excerpt The Weekly Data Engineering Newsletter ## Why Decoupling Databases from Kubernetes Clusters Improves Reliability DevFeed: [Why Decoupling Databases from Kubernetes Clusters Improves Reliability]() Original publisher: [Read original article]() Author: Zach Peirce Published: 2026-02-10T14:00:00Z Content type: article Language: en Sources: [DigitalOcean]() Topics: [Kubernetes](), [Database](), [Databases](), [Cloud](), [Inference](), [Persistence](), [Artificial Intelligence](), [Digital Ocean]() Tags: [ai](), [cloud](), [cloud-native](), [databases](), [digitalocean](), [inference](), [kubernetes](), [kubernetes-clusters](), [latency](), [mongodb](), [opensearch](), [persistence](), [postgresql](), [tech-stack-advice](), [valkey]() ### AI overview The article argues that stateful databases should generally be managed outside ephemeral Kubernetes clusters. It describes Kubernetes as the execution layer and managed databases as a stable memory layer for inference-oriented applications, citing resource contention and latency as key concerns. ### Source excerpt Kubernetes has won the cloud-native war for a reason: it's one of, if not the most powerful tool we have for scaling applications and ensuring they stay up when unexpected things happen. But as we move into the era of the Inference Cloud, we've fallen into a trap. We've become so enamored with "everything-as-code" that we're forcing our most sensitive data inside the cluster. At DigitalOcean, we see thousands of enterprises building on DigitalOcean Kubernetes (DOKS). The most successful ones have realized a counter-intuitive truth: To manage your Kubernetes clusters effectively, you must stop managing your databases inside them. Just because you can run your database in a container, doesn't mean you should. The Inference Cloud demands a new standard In 2026, the stakes have changed. We're no longer just scaling web services, we're scaling data-intensive inference workflows. AI-driven applications require massive bursts of compute and near-instant access to vector data, metadata, and user context. When your database competes for resources inside your Kubernetes cluster, your inference latency suffers. That's why DigitalOcean Managed Kubernetes and DigitalOcean Managed Databases (fully-managed PostgreSQL, MySQL, MongoDB, Caching for Valkey, and OpenSearch database services) are the two essential pillars of our inference cloud, working to solve this issue. Managed Kubernetes acts as the execution layer, while Managed Databases acts as the memory layer. Together, they deliver an attach-architecture that pairs high-performance compute with a stable, external data foundation. We will discuss this in more detail. The "stateful" friction Kubernetes was designed to be stateless-to kill, move, and restart pods at a moment's notice. For databases, this model is far from ideal. Databases are inherently stateful, and running systems like PostgreSQL or MongoDB inside a Kubernetes cluster introduces friction between the two, what is commonly referred to as the operational tax. Whe ## The search for speed in Figma DevFeed: [The search for speed in Figma]() Original publisher: [Read original article]() Author: Scott Laird Published: 2024-10-10T00:00:00Z Content type: article Language: en Sources: [Figma Blog]() Topics: [Figma](), [Amazon OpenSearch Service](), [Latency](), [Instrumentation](), [elasticsearch](), [Amazon Web Services](), [Traces](), [telemetry](), [Web]() Tags: [aws](), [elasticsearch](), [figma](), [infrastructure](), [instrumentation](), [latency](), [metrics](), [opensearch](), [performance](), [search](), [traces]() ### AI overview Figma describes an investigation into slow search performance as its search infrastructure grew. The team migrated from an older version of ElasticSearch to OpenSearch through AWS's managed OpenSearch service, then used instrumentation, metrics, and traces to reconcile major differences between reported search latency and application-level latency. The investigation found that API-library calls were substantially slower than OpenSearch's reported averages and helped establish a foundation for future scale. ### Source excerpt Our months-long investigation into slow search speeds led to a solution that not only improved performance but also set the foundation for future scale. ## Trino at Open Source Summit North America 2023 DevFeed: [Trino at Open Source Summit North America 2023]() Original publisher: [Read original article]() Author: Manfred Moser Published: 2023-05-15T00:00:00Z Content type: article Language: en Sources: [Trino Blog]() Topics: [Open Source](), [data](), [large-language-models]() Tags: [developers](), [event](), [government](), [linux](), [nasa](), [open-source](), [opensearch](), [risc-v]() ### AI overview The article recounts attendance at Open Source Summit North America 2023 in Vancouver, highlighting open source communities and projects such as OpenSearch, RISC-V, government DevHub initiatives, and NASA open source and open data projects. It also discusses Trino, query engines, lakehouses, Starburst, data use cases, large language models, and the upcoming free virtual Trino Fest. ### Source excerpt Last week, I had the pleasure to attend Open Source Summit North America 2023 in Vancouver. A quick hop across the Strait of Georgia got me right into the event and into the midst of my peers of open source developers, advocates, and enthusiasts. ## Teleport 13: New Features and Updates DevFeed: [Teleport 13: New Features and Updates]() Original publisher: [Read original article]() Author: kenneth.dumez@goteleport.com (Kenneth DuMez) Published: 2023-05-10T00:00:00Z Content type: release Language: en Sources: [Teleport]() Topics: [configuration](), [Load Balancing](), [Amazon Web Services](), [Kubernetes](), [okta](), [opensearch](), [TLS (Transport Layer Security)](), [Web]() Tags: [announcement](), [aws](), [configuration](), [kubernetes](), [load-balancing](), [new-features](), [okta](), [opensearch](), [tls](), [ui]() ### AI overview Teleport 13 introduces automatic agent updates with configurable maintenance windows, TLS routing through AWS application load balancers for Server Access and Kubernetes Access, Okta application and group imports, and AWS OpenSearch support for Database Access. Several features are marked as preview releases. ### Source excerpt An overview of all of the new features added to Teleport 13. Automatic Updating, Light Theme and more! ## Teleport 13 Newsletter DevFeed: [Teleport 13 Newsletter]() Original publisher: [Read original article]() Author: ben@goteleport.com (Ben Arent) Published: 2023-04-15T00:00:00Z Content type: release Language: en Sources: [Teleport]() Topics: [releases](), [Release notes](), [OpenSSH](), [OpenID connect (OIDC)](), [opensearch](), [terraform provider](), [Windows]() Tags: [aws](), [newsletter](), [oidc](), [opensearch](), [openssh](), [release](), [releases](), [terraform-provider](), [updates]() ### AI overview The May 2023 Teleport newsletter summarizes the Teleport 13 release, including automatic agent upgrades, no-code AWS onboarding, TLS routing through an ALB, universal binaries, improved OpenSSH support, Kubernetes tracing, Okta application protection, AWS OpenSearch support, and Windows session recording export. ### Source excerpt Teleport 13 Newsletter - May 2023 Edition ## Chainguard announces a Wolfi-based OpenSearch image with SBOMs and fewer CVEs DevFeed: [Chainguard announces a Wolfi-based OpenSearch image with SBOMs and fewer CVEs]() Original publisher: [Read original article]() Published: 2023-04-07T00:00:00Z Content type: release Language: en Sources: [Chainguard: Unchained]() Topics: [Amazon OpenSearch Service](), [chainguard images](), [Containers](), [Security]() Tags: [chainguard-images](), [containers](), [opensearch](), [provenance](), [sboms](), [security](), [slsa]() ### AI overview Chainguard announces a new OpenSearch container image built on Wolfi with a hardened Java toolchain and runtime. The article says the image is less than 25% the size of an alternative image and has significantly fewer CVEs, and that it includes SBOMs and provenance information. ### Source excerpt Chainguard's new OpenSearch image is smaller, more secure, and perfect for container deployments. ## DuckDuckGo Onion Search for Firefox DevFeed: [DuckDuckGo Onion Search for Firefox]() Original publisher: [Read original article]() Published: 2021-07-30T18:42:23Z Content type: tutorial Language: en Sources: [Signs of Triviality]() Topics: [DuckDuckGo](), [Firefox](), [opensearch]() Tags: [firefox](), [how-to](), [opensearch](), [search]() ### AI overview A tutorial explaining how to add DuckDuckGo Tor OpenSearch as the default search engine in Firefox. ### Source excerpt How to add DuckDuckGo Tor OpenSearch as the default search in Firefox.