# SIEM, Security, Observability A computing discipline encompassing security information and event management (SIEM) and software observability, which analyzes telemetry such as logs, metrics, and traces. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Elastic announces GA of cross-project search on Serverless, enabling teams to query across all linked projects without moving a byte DevFeed: [Elastic announces GA of cross-project search on Serverless, enabling teams to query across all linked projects without moving a byte]() Original publisher: [Read original article]() Author: Jordi Mon Companys,Lucy Wang Published: 2026-09-16T00:00:00Z Content type: release Language: en Sources: [Elastic Blog - Elasticsearch, Kibana, and ELK Stack]() Topics: [Serverless](), [Elastic Cloud](), [Cloud](), [observability](), [Security](), [SIEM, Security, Observability]() Tags: [architecture-cloud-migration-migrating-cloud-native-scaling-search-analytics-search-applicatio](), [cloud](), [cloud-elasticsearch-platform](), [customers](), [elastic](), [elastic-cloud](), [observability](), [observability-security-search](), [security](), [serverless]() ### AI overview Elastic announced the general availability of cross-project search for Elastic Cloud Serverless. It lets teams query multiple linked projects in a single session across regions, project types, and cloud providers, while keeping data in place and avoiding certificates, remote-cluster configuration, and per-connection authentication. ### Source excerpt Cross-project search is now GA on Elastic Cloud Serverless. Link multiple projects and query all of them from a single Discover or ES|QL session: no certificates, no remote cluster config, and three clicks to set up. Available from September 1, 2026. ## Atlassian Automates Root Cause Analysis by Correlating Metrics, Logs and Traces DevFeed: [Atlassian Automates Root Cause Analysis by Correlating Metrics, Logs and Traces]() Original publisher: [Read original article]() Author: Craig Risi Published: 2026-09-15T12:00:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [incident](), [atlassian](), [telemetry](), [SIEM, Security, Observability](), [tracing](), [Cloud Native Ecosystem](), [OpenTelemetry]() Tags: [atlassian](), [atlassian-automated-rca](), [cloud-native](), [defects](), [devops](), [distributed](), [incident](), [incident-response](), [logging](), [logs](), [metrics](), [news](), [opentelemetry](), [root-cause-analysis](), [services](), [telemetry](), [traces](), [tracing]() ### AI overview Atlassian has outlined an approach to automating root cause analysis for large-scale cloud-native incidents. It correlates metrics, logs, distributed traces, and service topology to detect anomalies, align them in time, trace dependencies, and produce ranked hypotheses about likely fault origins and propagation paths. ### Source excerpt Atlassian has outlined a new approach to automating root cause analysis for large-scale cloud-native incidents, using correlation across metrics, logs, distributed traces, and service topology to generate ranked hypotheses about where failures originate and how they propagate. By Craig Risi ## Unmasking Cloud Identities: From Behavioral Clustering to Automated Detection DevFeed: [Unmasking Cloud Identities: From Behavioral Clustering to Automated Detection]() Original publisher: [Read original article]() Author: Osher Jacob Published: 2026-09-14T10:00:01Z Content type: article Language: en Sources: [Unit 42]() Topics: [AWS CloudTrail](), [Cloud](), [threat detection](), [Threat Research](), [SIEM, Security, Observability](), [Machine learning](), [Algorithms](), [SQL](), [IAM](), [identity and access management](), [Amazon Web Services]() Tags: [algorithms](), [amazon-web-services-aws](), [analysis](), [aws-cloudtrail](), [cloud](), [cloud-cybersecurity-research](), [cloud-detection](), [devops](), [iam](), [identity-and-access-management](), [logs](), [machine-learning](), [post](), [sql](), [threat-detection](), [threat-research]() ### AI overview This article presents a behavioral clustering model for mapping cloud identities to functional roles using activity patterns from audit logs. It applies unsupervised machine learning with UMAP and HDBSCAN to data from more than 40,000 identities across 125 cloud environments, and shows how the resulting map can support automated threat detection. The article also explains how lightweight heuristics extracted from the map can classify identities at scale using standard SQL, reducing the need for continuous resource-intensive machine learning pipelines. ### Source excerpt We designed a behavioral clustering model to map cloud identity roles from audit logs, enabling continuous threat detection using standard SQL queries. The post Unmasking Cloud Identities: From Behavioral Clustering to Automated Detection appeared first on Unit 42. ## How AWS Lambda logs every flow across thousands of microVMs per host with eBPF and Rust DevFeed: [How AWS Lambda logs every flow across thousands of microVMs per host with eBPF and Rust]() Original publisher: [Read original article]() Author: Prashant Kumar Singh Published: 2026-09-11T12:00:00Z Content type: article Language: en Sources: [The New Stack]() Topics: [AWS Lambda](), [Architecture & Design](), [SIEM, Security, Observability](), [telemetry](), [Amazon EC2](), [Amazon S3](), [VPC]() Tags: [architecture](), [aws](), [aws-lambda](), [aws-marketplace](), [compliance](), [ebpf](), [firecracker](), [incident](), [incident-response](), [logs](), [monitoring](), [observability](), [post-contributed](), [rust](), [s3](), [scale](), [security](), [server](), [serverless](), [sponsor-aws-marketplace](), [sponsored-post-contributed](), [vpc]() ### AI overview AWS Lambda describes replacing an aging network-capture system with an eBPF and Rust pipeline that records network flows across short-lived, tenant-isolated microVMs. The system prioritizes complete, correctly attributed records with minimal overhead for security investigation, metering, audit, observability, and monitoring. ### Source excerpt On any compute platform, when a security alert fires, the question is always the same. Which workload talked to that The post How AWS Lambda logs every flow across thousands of microVMs per host with eBPF and Rust appeared first on The New Stack. ## Customize Amazon API Gateway destinations for execution logs DevFeed: [Customize Amazon API Gateway destinations for execution logs]() Original publisher: [Read original article]() Author: Giedrius Praspaliauskas Published: 2026-09-09T22:35:42Z Content type: tutorial Language: en Sources: [AWS Compute Blog]() Topics: [Amazon API Gateway](), [Amazon CloudWatch Logs](), [log management](), [Amazon S3](), [SIEM, Security, Observability]() Tags: [amazon-api-gateway](), [amazon-cloudwatch-logs](), [amazon-s3](), [announcements](), [intermediate-200](), [logs](), [observability](), [rest-api]() ### AI overview This tutorial explains how to route Amazon API Gateway REST API execution logs to CloudWatch Logs, Amazon S3, or Amazon Data Firehose. It contrasts execution logs with access logs and describes their use for diagnosing authorization, validation, integration, mapping, and error-handling behavior. ### Source excerpt Amazon API Gateway execution logs help you trace request processing step by step through your REST API stages. They capture authorization results, integration latency, mapping template output, and error details that are otherwise invisible at the API surface. When a production request fails in a way the access log cannot explain, the execution log is [...] ## Whose GPUs are these, anyway? Secure, self-service metrics for multi-tenant Kubernetes DevFeed: [Whose GPUs are these, anyway? Secure, self-service metrics for multi-tenant Kubernetes]() Original publisher: [Read original article]() Author: Bingi Narasimha Karthik (Golden Kubestronaut, Adobe) and Ramkumar Nagaraj (Golden Kubestronaut, Adobe) Published: 2026-09-09T11:27:00Z Content type: article Language: en Sources: [Cloud Native Computing Foundation]() Topics: [Kubernetes](), [GPU](), [telemetry](), [SIEM, Security, Observability]() Tags: [blog](), [cost](), [gpu](), [kubernetes](), [metrics](), [prometheus](), [security]() ### AI overview The article describes providing Kubernetes tenants with secure, self-service access to their own GPU metrics without exposing a central Prometheus instance or allowing noisy queries to affect the wider fleet. ### Source excerpt The question that stopped the meeting It was a routine cost review. The slide showed the month's GPU spend, the biggest line on the whole infrastructure bill, and someone asked a five-word question: "Are we using... ## Black Hat USA 2026: Building the Agentic SOC, One Live Event at a Time DevFeed: [Black Hat USA 2026: Building the Agentic SOC, One Live Event at a Time]() Original publisher: [Read original article]() Author: Jessica (Bair) Oppenheimer Published: 2026-09-07T15:00:58Z Content type: article Language: en Sources: [Security @ Cisco Blogs]() Topics: [Detection engineering](), [SIEM, Security, Observability](), [Threat Hunting & Intel](), [telemetry](), [NOC](), [Malware]() Tags: [agentic-soc](), [black-hat](), [cisco-secure-access](), [cisco-talos](), [cybersecurity](), [duo](), [firewall](), [malware](), [network-operations-center](), [noc](), [security](), [security-operations-center](), [soc](), [splunk-cloud](), [splunk-enterprise-security](), [telemetry](), [thousandeyes]() ### AI overview Cisco describes its work protecting the Black Hat USA 2026 network alongside NOC leaders and technology partners. The team combined security telemetry and workflows to support visibility, detection engineering, threat hunting, malware analysis, AI protection, and Agentic SOC development. ### Source excerpt Cisco is the Security Cloud Provider for the Black Hat conferences. Learn about the latest innovations for the Agentic SOC. ## Black Hat USA 2026: Safeguarding DNS with Secure Access DevFeed: [Black Hat USA 2026: Safeguarding DNS with Secure Access]() Original publisher: [Read original article]() Author: Steve Vida Published: 2026-09-07T15:00:32Z Content type: article Language: en Sources: [Security @ Cisco Blogs]() Topics: [SIEM, Security, Observability](), [telemetry](), [NOC]() Tags: [apple](), [black-hat](), [cisco-secure-access](), [cisco-security-cloud](), [cisco-talos](), [cisco-xdr](), [cloudflare](), [cybersecurity](), [dns](), [google](), [network-operations-center](), [noc](), [phishing](), [privacy](), [security](), [security-operations-center](), [soc](), [splunk-cloud](), [splunk-enterprise-security](), [statistics](), [telemetry]() ### AI overview Cisco reports on using Secure Access and DNS telemetry to protect the Black Hat USA 2026 network. The article highlights blocking unapproved encrypted DNS resolvers, DNS request statistics, and activity classified as hacking. ### Source excerpt Cisco is the Security Cloud Provider for the Black Hat conferences, over a decade providing DNS Security. Learn about protecting DNS with Secure Access. ## WSIS Forum 2026: From commitments to measurable implementation DevFeed: [WSIS Forum 2026: From commitments to measurable implementation]() Original publisher: [Read original article]() Author: Joyce Chen Published: 2026-09-06T23:14:00Z Content type: article Language: en Sources: [APNIC Blog]() Topics: [Development](), [ai-governance](), [SIEM, Security, Observability]() Tags: [2026](), [community](), [development](), [global](), [governance](), [igf](), [internet-governance](), [metrics](), [platform](), [policy](), [recommendations](), [wsis]() ### AI overview The WSIS Forum 2026 marked a shift from documenting digital-development commitments to demonstrating measurable implementation. The forum emphasized implementation roadmaps, evidence, targets, indicators, metrics, gap analysis, and policy recommendations aligned with the WSIS framework, the Sustainable Development Goals, and Global Digital Compact commitments. ### Source excerpt WSIS Forum 2026 marked the start of a new phase for global digital development, shifting the focus from commitments to measurable implementation. ## The security attack that hid inside your observability data DevFeed: [The security attack that hid inside your observability data]() Original publisher: [Read original article]() Author: Roberto Arico Published: 2026-09-03T00:00:00Z Content type: article Language: en Sources: [Elastic Blog - Elasticsearch, Kibana, and ELK Stack]() Topics: [SIEM, Security, Observability](), [telemetry](), [cpu]() Tags: [cost](), [cpu](), [endpoint-security](), [endpoint-security-observability-security-siem-log-analytics](), [observability](), [security](), [security-analytics-security-compliance-threat-hunting-tool-consolidation-agentic-ai-alerting]() ### AI overview The article explains how separating observability and security platforms can conceal threats such as cryptominers, duplicate data costs, and prevent teams from seeing the full operational and security picture. ### Source excerpt Your ops team sees a CPU spike. Your security team sees nothing. The cryptominer runs for six hours. Avoid duplication of cost and time and see how a unified observability and security platform with grounded AI closes the gap. ## Monitor prompt caching to optimize your token usage DevFeed: [Monitor prompt caching to optimize your token usage]() Original publisher: [Read original article]() Author: Thomas Sobolik Published: 2026-09-02T00:00:00Z Content type: tutorial Language: en Sources: [Datadog | The Monitor blog]() Topics: [Caching](), [Large Language Model](), [Latency](), [Traces](), [SIEM, Security, Observability](), [anthropic]() Tags: [agent-observability](), [agents](), [ai](), [ai-engineering](), [ai-observability](), [anthropic](), [caching](), [cost](), [how-to](), [latency](), [llm](), [models](), [monitor](), [openai](), [traces]() ### AI overview A tutorial on prompt caching for LLM and agent workloads, covering cache behavior, provider differences, and monitoring token use and latency. ### Source excerpt Learn how to use prompt caching effectively and monitor your models and agents to troubleshoot cache invalidations. ## VAST Data CrowdStrike Integration Goes Live: Native Falcon Sensor Now, Next-Gen SIEM and AIDR in Preview DevFeed: [VAST Data CrowdStrike Integration Goes Live: Native Falcon Sensor Now, Next-Gen SIEM and AIDR in Preview]() Original publisher: [Read original article]() Author: Harold Fritts Published: 2026-09-01T15:37:31Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [Cybersecurity](), [Securing AI](), [AI Infrastructure](), [SIEM, Security](), [SIEM, Security, Observability](), [prompt injection](), [Jailbreak](), [pii](), [Retrieval Augmented Generation (RAG)](), [Nvidia]() Tags: [ai](), [ai-infrastructure](), [ai-security](), [cybersecurity](), [enterprise](), [infrastructure](), [nvidia](), [pii](), [prompt-injection](), [security]() ### AI overview VAST Data and CrowdStrike have launched an integration that embeds Falcon security capabilities into VAST AI storage infrastructure, data pipelines, and production AI workloads. The integration supports native Falcon sensors, sends VAST audit telemetry to CrowdStrike Next-Gen SIEM, inspects data in flight with Falcon AIDR, helps identify PII before downstream use, and detects prompt injection and jailbreak attempts during model interactions. ### Source excerpt VAST Data and CrowdStrike are turning the AI security partnership they announced at VAST Forward in February into a shipping product, detailing a multi-layered integration that embeds enterprise-grade cybersecurity directly into AI storage infrastructure, data pipelines, and production AI workloads. By combining the VAST AI Operating System with the CrowdStrike Falcon platform, the collaboration addresses The post VAST Data CrowdStrike Integration Goes Live: Native Falcon Sensor Now, Next-Gen SIEM and AIDR in Preview appeared first on StorageReview.com. ## Asia Pacific privacy laws are arriving. Your NREN holds more personal data than you think. DevFeed: [Asia Pacific privacy laws are arriving. Your NREN holds more personal data than you think.]() Original publisher: [Read original article]() Author: Tuwan Azgar Jaleel Published: 2026-08-19T05:10:00Z Content type: article Language: en Sources: [APNIC Blog]() Topics: [data](), [SIEM, Security, Observability](), [Network](), [telemetry]() Tags: [article](), [compliance](), [data](), [guest-post](), [how-to](), [legal](), [networks](), [nren](), [privacy](), [security](), [tech-matters](), [telemetry]() ### AI overview The article examines emerging Asia Pacific privacy laws and their implications for National Research and Education Networks (NRENs). It argues that although an NREN's open backbone may have relatively low exposure, surrounding services such as federated identity, eduroam, CSIRT operations, and network telemetry can process personal data and may create compliance obligations. The article emphasizes that requirements differ by jurisdiction and that NRENs should begin by understanding the data handled by their service portfolios. ### Source excerpt Guest Post: Privacy compliance starts with knowing your data. Many NREN services, including federated identity, eduroam, CSIRT operations, and network telemetry, process personal data and may already fall under emerging privacy laws. ## Connect client traces to your logs DevFeed: [Connect client traces to your logs]() Original publisher: [Read original article]() Author: Katerina Skroumpelou; Steven Eubank Published: 2026-08-18T07:00:00Z Content type: tutorial Language: en Sources: [Supabase Blog]() Topics: [Supabase](), [tracing](), [OpenTelemetry](), [client](), [Amazon API Gateway](), [browser](), [SIEM, Security, Observability]() Tags: [api](), [backend](), [browser](), [how-to](), [integration](), [opentelemetry](), [traces](), [tracing]() ### AI overview A walkthrough of connecting client-side traces to Supabase logs by propagating W3C Trace Context. It explains how to configure a tracer and client propagation so requests can be followed from the browser through Supabase's API Gateway and Edge Function logs, including with external log backends. ### Source excerpt supabase-js now propagates W3C Trace Context to Supabase, so a client trace and the matching Supabase log share one trace_id. ## One audit trail for every coding agent, and what it proves DevFeed: [One audit trail for every coding agent, and what it proves]() Original publisher: [Read original article]() Author: WorkOS Published: 2026-08-13T00:00:00Z Content type: article Language: en Sources: [WorkOS Blog]() Topics: [audit trail](), [audit](), [coding](), [Claude Code](), [codex](), [OpenClaw](), [SIEM, Security, Observability](), [MCP]() Tags: [agent](), [agents](), [api](), [audit](), [audit-trail](), [claude](), [claude-code](), [code](), [codex](), [coding](), [logging](), [mcp](), [siem](), [streaming](), [visibility]() ### AI overview This article describes WorkOS audit logging for Claude Code, Codex, OpenClaw, and pi. Its shared plugin and harness capture agent session, prompt, and tool lifecycle events, resolve activity to people, and make events queryable through a console, Export API, SIEM streaming, and MCP. ### Source excerpt We built audit logging for Claude Code, Codex, OpenClaw and pi with no API key on any laptop. Use it to get total visibility into your entire org's agentic activity. ## Audit Log Drains now support Datadog, Splunk, and Panther DevFeed: [Audit Log Drains now support Datadog, Splunk, and Panther]() Original publisher: [Read original article]() Author: Nate McGrady Published: 2026-08-07T04:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [SIEM, Security](), [Streaming](), [Amazon S3](), [SIEM, Security, Observability]() Tags: [amazon-s3](), [datadog](), [documentation](), [enterprise](), [integration](), [logs](), [migration](), [migration-guide](), [s3](), [streaming]() ### AI overview Vercel Audit Log Drains can stream team audit events and metadata to Datadog, Splunk, or Panther, in addition to custom HTTPS endpoints and Amazon S3. The feature is available on Enterprise plans and replaces Custom SIEM Log Streaming. ### Source excerpt Audit Log Drains now stream your team's audit events into Datadog, Splunk, and Panther, joining the existing custom HTTPS endpoint and Amazon S3 destinations. An Audit Log Drain forwards every event from your team's Activity Log, plus additional audit metadata, to the destination you choose. They're available on Enterprise plans. To create one, go to Drains in your team settings. Click Add Drain, choose Audit Log as the data type, and pick a destination. Audit Log Drains replace Custom SIEM Log Streaming. If you already stream audit logs to a SIEM, follow the migration guide to move your integration over. Learn more about Drains in the documentation. Read more ## Centralize cross-account Amazon ECS telemetry with an ADOT gateway DevFeed: [Centralize cross-account Amazon ECS telemetry with an ADOT gateway]() Original publisher: [Read original article]() Author: Rahul Kumar Published: 2026-08-06T16:13:46Z Content type: tutorial Language: en Sources: [Containers]() Topics: [Amazon Elastic Container Service](), [telemetry](), [OpenTelemetry](), [SIEM, Security, Observability](), [Amazon CloudWatch](), [Amazon Web Services](), [Windows](), [.NET Framework](), [Traces](), [log management](), [Amazon Elastic Kubernetes Service]() Tags: [amazon-cloudwatch](), [amazon-eks](), [amazon-elastic-container-service](), [amazon-elastic-kubernetes-service](), [aws](), [intermediate-200](), [logs](), [metrics](), [net-framework](), [observability](), [opentelemetry](), [technical-how-to](), [telemetry](), [traces](), [windows]() ### AI overview This tutorial presents a centralized AWS Distro for OpenTelemetry gateway for collecting telemetry from Amazon ECS workloads across multiple AWS accounts. It replaces per-task sidecars, supports Windows .NET Framework tasks, receives OTLP over private connectivity, and exports traces to AWS X-Ray plus metrics and logs to Amazon CloudWatch. ### Source excerpt Running an OpenTelemetry collector as a sidecar in every Amazon ECS task does not scale across a multi-account estate, and it cannot run at all on Windows. Learn how to replace per-task sidecars with a single centralized ADOT gateway that ingests OTLP from workloads across accounts and exports traces to AWS X-Ray and metrics and logs to Amazon CloudWatch. ## AI Gateway logs now have a dedicated page DevFeed: [AI Gateway logs now have a dedicated page]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-07-31T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Artificial Intelligence](), [SIEM, Security, Observability](), [telemetry](), [Routing (disambiguation)](), [CSV](), [JSON]() Tags: [ai](), [ai-gateway](), [cache](), [cost](), [json](), [logs](), [model](), [routing](), [time]() ### AI overview Vercel AI Gateway now provides a dedicated Logs page for inspecting team and project requests, including cost, token usage, duration, model, provider, region, routing, filtering, search, chart-based time ranges, and CSV or JSON export. Request details include token categories, time to first token, retention and region settings, and provider fallback attempts with failure reasons. ### Source excerpt AI Gateway now has a dedicated Logs page listing every request your team sends through the gateway, newest first, with cost, token counts, duration, and the model, provider, and region that served it. Open any request to see how it was routed. It's available at the team scope and per project. Filter and search Filter by provider, model, modality, credentials, or status, or search by model, provider, or request ID to jump straight to one request. Every filter is stored in the URL, so you can share a filtered view by copying the address. A chart above the table shows request counts over the selected range, and you can drag across it to zoom into a narrower window. You can also export the current view as CSV or JSON, with your filters applied. Drill into a request Click any row to open its details next to the list: total cost, a token breakdown across input, output, reasoning, and cache reads and writes, duration, time to first token, and whether Zero Data Retention and region restrictions were applied. The fallback path lists every provider attempt for the request in order. Each attempt shows the model, provider, status code, credentials, and how long it took, and failed attempts include the reason, such as a provider timeout or an exhausted routing budget. To learn more about AI Gateway logs, read the documentation. Read more ## How to structure a log DevFeed: [How to structure a log]() Original publisher: [Read original article]() Author: Kyle Tryon Published: 2026-07-21T09:00:00Z Content type: tutorial Language: en Sources: [Sentry Blog]() Topics: [Logging](), [Structured-data](), [TypeScript](), [ESLint](), [SIEM, Security, Observability]() Tags: [code](), [guide](), [lint](), [logs](), [programming](), [schema]() ### AI overview A practical guide to writing structured logs that are consistent, queryable, and useful for debugging in production. It covers event naming, flattened attributes, predictable low-cardinality values, severity levels, primitive-value constraints, and enforcing conventions with an ESLint plugin for TypeScript. ### Source excerpt A practical guide to writing structured, queryable, lint-enforceable logs with consistent event names, attributes, severity, and schema checks. ## Introducing the new Vercel Agent DevFeed: [Introducing the new Vercel Agent]() Original publisher: [Read original article]() Author: Amelia Charles Published: 2026-07-21T04:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Vercel](), [Security](), [Deployment](), [Pull Request](), [dashboards](), [SIEM, Security, Observability](), [Command-line interface](), [Grafana](), [Caching](), [ci]() Tags: [agent](), [agents](), [caching](), [cli](), [cost](), [deployment](), [errors](), [github](), [logs](), [metrics](), [on-call](), [performance](), [production](), [pull-request](), [security](), [vercel]() ### AI overview Vercel expands Vercel Agent with a dashboard-based production investigation and response workflow. The agent can inspect logs, metrics, and deployments, answer project questions, review pull requests, diagnose cost increases and failed builds, and propose fixes. It is read-only by default, operates under its own identity, and requires approval before changing production or opening corrective changes. ### Source excerpt Today we're expanding Vercel Agent. It started by triaging alerts and reviewing your pull requests. Now it has a home in your dashboard, where it can investigate production, answer questions about your projects, and take action once you approve it. Because Vercel Agent is built into the platform that deploys and runs your app, when something changes in production, it's your first responder. It autonomously investigates your logs, metrics, and deployments, finds the root cause, and proposes a fix, before you've opened your laptop. Vercel Agent works under its own identity and is read-only by default. You can reach it through the Vercel Dashboard, GitHub, and the CLI. What Vercel Agent does for you We've been running Vercel Agent on our production deployments for months. This is what a typical investigation looks like. A bad deploy ships at 11pm and the checkout endpoint starts throwing 500s. By the time the on-call engineer logs in, Vercel Agent has already traced the errors to the deploy that shipped four minutes earlier, and recommends an instant rollback. The engineer approves the plan. With permission, Vercel Agent rolls back to the previous production deployment and begins working on a PR to fix the endpoint. The time from alert to mitigated: less than three minutes. What you can do with Vercel Agent You can also direct Vercel Agent yourself. Hand it a task and it does the legwork, then either answers your question or hands you a fix to approve. It never changes production on its own. For example: Review a pull request. Tell it to look at a PR and it flags performance regressions and risky changes that a passing CI run won't show. Trace a cost increase. Ask why your bill jumped and it finds the culprit, like a code change that server-renders a page on every request instead of caching. With approval, it writes the fix and opens a PR. Fix a broken build. Point Vercel Agent at a failed deployment and it reads the logs, finds the failing config, asks permission to u ## Deploy agents you can trust with centralized AI governance DevFeed: [Deploy agents you can trust with centralized AI governance]() Original publisher: [Read original article]() Author: Kristin Crosier Published: 2026-07-21T00:00:00Z Content type: article Language: en Sources: [Redpanda]() Topics: [ai-governance](), [Responsibility & Safety](), [audit trail](), [SIEM, Security, Observability](), [Model Context Protocol](), [observability]() Tags: [agentic](), [ai](), [ai-governance](), [audit-trail](), [autonomous](), [autonomous-agents](), [enterprise](), [hosting](), [infrastructure](), [mcp](), [observability](), [thought-leadership](), [vibe-coding]() ### AI overview This article explains why enterprises struggle to deploy autonomous agentic systems: organizations lack confidence in agents that can access data and tools without unique identities, audit trails, or kill switches. It argues for a centralized AI governance layer enforced by infrastructure that agents cannot access or modify, positioned between agents and the data, tools, identities, and models they use. The proposed governance platform also supports scaling through AI gateways, MCP hosting, observability, and budgeting. ### Source excerpt Discover why organizations are struggling to deploy and scale agentic systems, and how a centralized AI governance platform can help you trust and scale agents. ## Unified Logs is now in open beta DevFeed: [Unified Logs is now in open beta]() Original publisher: [Read original article]() Author: Jordi Enric; Joshen Lim; Kemal Y; Steven Eubank Published: 2026-07-16T07:00:00Z Content type: release Language: en Sources: [Supabase Blog]() Topics: [Supabase](), [SIEM, Security, Observability](), [telemetry](), [dashboards](), [API](), [Database]() Tags: [api](), [auth](), [database](), [debugging](), [errors](), [event](), [events](), [json](), [logs](), [open](), [search](), [update]() ### AI overview Supabase Unified Logs is now in open beta, combining logs from project services into one searchable dashboard view with filtering, live tailing, timeline visualization, and request tracing across services. ### Source excerpt One searchable view for logs across every Supabase service, with live tail, filtering, and a timeline. ## Preparing for OMB M-26-14: How Datadog supports federal logging maturity DevFeed: [Preparing for OMB M-26-14: How Datadog supports federal logging maturity]() Original publisher: [Read original article]() Author: Chris Leffler; Sophie Wang Published: 2026-06-29T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [SIEM, Security, Observability](), [log management](), [Monitoring](), [threat detection](), [incident](), [Incident response](), [observability](), [Security](), [Security Operations Center](), [Resilience](), [Cybersecurity]() Tags: [bits-ai](), [cloud-siem](), [compliance](), [cybersecurity](), [fedramp](), [govcloud](), [incident-response](), [log-management](), [logging](), [monitoring](), [observability](), [resilience](), [security](), [security-operations-center](), [soc](), [systems](), [telemetry](), [threat-detection](), [workflow-automation]() ### AI overview This article explains how OMB Memorandum M-26-14 changes federal logging guidance from prescriptive requirements to a risk- and maturity-based model. It describes continuous event monitoring and threat hunting, investigation, response, and forensics, including centralized security telemetry, visibility across IT, OT, and IoT environments, threat detection, searchable and retrievable logs, cross-source correlation, incident response, and forensic analysis. It also presents Datadog as a unified observability and security platform for helping agencies meet these requirements. ### Source excerpt Learn how Datadog helps federal agencies prepare for OMB M-26-14 by providing centralized telemetry data, threat detection, and automated incident response. ## ClickHouse achieves AWS Cloud Operations Competency DevFeed: [ClickHouse achieves AWS Cloud Operations Competency]() Original publisher: [Read original article]() Author: Aditya Chidurala Published: 2026-06-26T08:27:37Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [SIEM, Security, Observability](), [observability](), [telemetry](), [Amazon Web Services](), [OpenTelemetry](), [Monitoring](), [Cloud](), [Traces](), [real-time](), [Amazon S3]() Tags: [aws](), [clickhouse](), [cloud](), [compression](), [concurrency](), [logs](), [metrics](), [monitoring](), [observability](), [opentelemetry](), [real-time](), [telemetry](), [traces]() ### AI overview ClickHouse has achieved the AWS Cloud Operations Competency in Monitoring and Observability. The article describes how ClickHouse Cloud handles high-volume, high-cardinality logs, metrics, and traces with compressed columnar storage, real-time querying, continuous ingestion, separated compute and storage, and OpenTelemetry-native ClickStack on AWS. ### Source excerpt ClickHouse has achieved the AWS Cloud Operations Competency in Monitoring and Observability. Teams like Modal, Exabeam, and Langfuse run full-fidelity logs, metrics, and traces on ClickHouse, querying them in real time without sampling or runaway cost. [Next page]()