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	<title>Logz.io</title>
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	<link>https://logz.io/</link>
	<description>Innovate Faster, Recover Quicker, and Get Smarter Insights with AI-Powered Log Management and Observability.</description>
	<lastBuildDate>Wed, 29 Jul 2026 08:48:49 +0000</lastBuildDate>
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		<title>Introducing OrionIQ Chat in Open 360 AI</title>
		<link>https://logz.io/blog/orioniq-chat-open-360-ai/</link>
		
		<dc:creator><![CDATA[Libi Michelson]]></dc:creator>
		<pubDate>Mon, 27 Jul 2026 15:34:35 +0000</pubDate>
				<category><![CDATA[AI Agents]]></category>
		<category><![CDATA[Blog]]></category>
		<category><![CDATA[Guides]]></category>
		<category><![CDATA[Observability]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[DevOps Community]]></category>
		<guid isPermaLink="false">https://logz.io/?p=69918</guid>

					<description><![CDATA[OrionIQ&#8217;s agentic investigation is now built into Logz.io Open 360 AI. Ask a question and OrionIQ investigates across your telemetry, shows its work as it goes, links every finding back to the exact query behind it, and tells you how much to trust the answer. Today we&#8217;re bringing OrionIQ Chat into Open 360 AI. This [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>Executive Roundtable: Guardrails for the Autonomous Era</title>
		<link>https://logz.io/blog/guardrails-autonomous-ai-engineering-adoption/</link>
		
		<dc:creator><![CDATA[Libi Michelson]]></dc:creator>
		<pubDate>Mon, 27 Jul 2026 11:57:30 +0000</pubDate>
				<category><![CDATA[AI Agents]]></category>
		<category><![CDATA[Blog]]></category>
		<category><![CDATA[Guides]]></category>
		<category><![CDATA[Observability]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[DevOps Community]]></category>
		<guid isPermaLink="false">https://logz.io/?p=69910</guid>

					<description><![CDATA[Ask ten engineering leaders how far their organization has actually gotten with autonomous AI, and most will admit the same thing once the marketing language drops away: not nearly as far as it looks from the outside. That was the undercurrent of a roundtable Logz.io and Twingate hosted on July 22, 2026, bringing together VPs [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>Prometheus Metrics Just Got a Cardinality Fix: What Native Histograms Change, and Why the Ecosystem Is Reacting</title>
		<link>https://logz.io/blog/prometheus-metrics-native-histograms/</link>
		
		<dc:creator><![CDATA[Amos Etzion]]></dc:creator>
		<pubDate>Mon, 20 Jul 2026 14:30:21 +0000</pubDate>
				<category><![CDATA[Blog]]></category>
		<category><![CDATA[ELK Stack]]></category>
		<category><![CDATA[Guides]]></category>
		<category><![CDATA[Kubernetes]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[DevOps Community]]></category>
		<category><![CDATA[Observability]]></category>
		<guid isPermaLink="false">https://logz.io/?p=69897</guid>

					<description><![CDATA[TL;DR: Prometheus&#8217;s biggest structural weakness has always been cardinality. A stable feature years in the making is finally addressing it, and the rest of the observability market is already responding. Native histograms allow for more efficient metrics storage, reducing cardinality strain and enabling faster, more cost-effective AI-powered observability. Ready to see how AI-powered observability can [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>OrionIQ Chat Cuts Resolve Time Significantly</title>
		<link>https://logz.io/learn/orioniq-chat-demo/</link>
		
		<dc:creator><![CDATA[Libi Michelson]]></dc:creator>
		<pubDate>Tue, 14 Jul 2026 13:28:15 +0000</pubDate>
				<category><![CDATA[Learn]]></category>
		<category><![CDATA[Videos]]></category>
		<guid isPermaLink="false">https://logz.io/?p=69820</guid>

					<description><![CDATA[Book a demo If you want to know more, fill out the form below to schedule a personalized demo.]]></description>
		
		
		
			</item>
		<item>
		<title>Part II: Inside Alert AI Analysis: From a Single-Agent Prompt to an Agent Harness</title>
		<link>https://logz.io/blog/alert-ai-analysis-agent-harness-engineering/</link>
		
		<dc:creator><![CDATA[Kevin Klein]]></dc:creator>
		<pubDate>Mon, 13 Jul 2026 12:58:25 +0000</pubDate>
				<category><![CDATA[Blog]]></category>
		<category><![CDATA[How To]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[DevOps Community]]></category>
		<category><![CDATA[Observability]]></category>
		<guid isPermaLink="false">https://logz.io/?p=69801</guid>

					<description><![CDATA[TL;DR: This is the engineering companion to our announcement post, Upgraded Alert AI Analysis: Automated Incident Investigation, read that one for what the new generation does for your team; read on for how it works under the hood. Interested in hearing more? Book a demo to see the Alert AI Analysis Agent live. Root cause [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>Upgraded Alert AI Analysis: Automated Incident Investigation</title>
		<link>https://logz.io/blog/devops/alert-ai-analysis-autonomous-incident-investigation/</link>
		
		<dc:creator><![CDATA[David Lotan Bolotnikoff]]></dc:creator>
		<pubDate>Mon, 13 Jul 2026 12:15:42 +0000</pubDate>
				<category><![CDATA[Blog]]></category>
		<category><![CDATA[DevOps]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[DevOps Community]]></category>
		<category><![CDATA[Observability]]></category>
		<guid isPermaLink="false">https://logz.io/?p=69800</guid>

					<description><![CDATA[TL;DR: OrionIQ has launched the next generation of its Alert AI Analysis agent within the Open 360 AI platform, designed to automate and accelerate incident investigation. Key features of this evolution include: Agent-Based Investigation: Instead of relying on a single prompt, the system coordinates specialized AI agents to correlate data across diverse sources like logs, [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>From Alert Noise to Automated Action: The Case for Workflow-Driven Monitoring</title>
		<link>https://logz.io/blog/workflow-driven-monitoring/</link>
		
		<dc:creator><![CDATA[David Lotan Bolotnikoff]]></dc:creator>
		<pubDate>Thu, 02 Jul 2026 19:04:20 +0000</pubDate>
				<category><![CDATA[Blog]]></category>
		<category><![CDATA[Training]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[DevOps Community]]></category>
		<category><![CDATA[Observability]]></category>
		<guid isPermaLink="false">https://logz.io/?p=69789</guid>

					<description><![CDATA[TL;DR: Modern monitoring platforms face a &#8220;workflow problem&#8221;: engineers are drowning in telemetry but lack tools that connect detection to resolution, often leading to fragmented, manual incident investigations. Most organizations have mastered data collection but fail at incident response. Engineers waste precious time manually stitching together logs, metrics, and traces across siloed tools. The Solution: [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>Logz.io Webinar Recap: A Four-Step Blueprint for Faster Root Cause Analysis</title>
		<link>https://logz.io/blog/webinar-raw-telemetry-2/</link>
		
		<dc:creator><![CDATA[Kevin Klein]]></dc:creator>
		<pubDate>Mon, 29 Jun 2026 13:53:13 +0000</pubDate>
				<category><![CDATA[Best Practices]]></category>
		<category><![CDATA[Blog]]></category>
		<category><![CDATA[How To]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[DevOps Community]]></category>
		<category><![CDATA[Observability]]></category>
		<guid isPermaLink="false">https://logz.io/?p=69751</guid>

					<description><![CDATA[Incident investigations take so long not because the fix is hard, but because finding the right fix is. Most engineers spend 20 to 60 minutes just understanding what&#8217;s wrong before they can act, not fixing anything, just trying to see the full picture. The framework that changes this has four steps: Orient, Isolate, Hypothesize, and [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>What Is Agentic Observability? The Complete Guide for Enterprise Engineering Teams</title>
		<link>https://logz.io/blog/ai-agents/what-is-agentic-observability/</link>
		
		<dc:creator><![CDATA[David Lotan Bolotnikoff]]></dc:creator>
		<pubDate>Mon, 29 Jun 2026 12:43:58 +0000</pubDate>
				<category><![CDATA[AI Agents]]></category>
		<category><![CDATA[Blog]]></category>
		<category><![CDATA[Observability]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[DevOps Community]]></category>
		<guid isPermaLink="false">https://logz.io/?p=69629</guid>

					<description><![CDATA[TL;DR Agentic observability uses AI agents to autonomously investigate incidents, identify root causes, and take action in production environments. Unlike traditional monitoring (which alerts and waits) or AIOps (which assists human analysis), agentic platforms conduct the investigation themselves. Key capabilities include autonomous incident triage, evidence-backed root cause analysis, alert noise reduction, and governed remediation. Enterprise [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>Webinar: From Raw Telemetry to Actionable RCA</title>
		<link>https://logz.io/learn/webinar-from-raw-telemetry-to-actionable-rca/</link>
		
		<dc:creator><![CDATA[Libi Michelson]]></dc:creator>
		<pubDate>Tue, 23 Jun 2026 15:48:13 +0000</pubDate>
				<category><![CDATA[Learn]]></category>
		<category><![CDATA[Videos]]></category>
		<category><![CDATA[Webinars]]></category>
		<guid isPermaLink="false">https://logz.io/?p=69646</guid>

					<description><![CDATA[Speakers: David Lotan Bolotnikoff, VP Product, Logz.ioKevin Klein, AI Engineer, OrionIQ RCA Lead, Logz.io What we discuss in the webinar: Logz.io’s blueprint for cutting investigation time and what happens when you put an AI agent on top of it.Why incidents still take too long. The real reason isn&#8217;t the bug. It&#8217;s what happens before you [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>Which AI-Powered Observability Tools Accelerate Root Cause Analysis (RCA)?</title>
		<link>https://logz.io/blog/ai-powered-observability-tools-root-cause-analysis/</link>
		
		<dc:creator><![CDATA[Seth King]]></dc:creator>
		<pubDate>Sun, 21 Jun 2026 08:59:39 +0000</pubDate>
				<category><![CDATA[Best of]]></category>
		<category><![CDATA[Blog]]></category>
		<category><![CDATA[DevOps]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[DevOps Community]]></category>
		<category><![CDATA[Observability]]></category>
		<guid isPermaLink="false">https://logz.io/?p=69621</guid>

					<description><![CDATA[TL;DR Choosing the right AI-powered observability platform isn&#8217;t about who has the most AI features. It&#8217;s about which platform helps your team identify root causes faster and spend less time investigating incidents. Here&#8217;s the short version: Logz.io + OrionIQ: Autonomous AI agents investigate incidents, perform root cause analysis, and surface next steps. Open standards, Kubernetes-ready, [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>Best Log Management Software for DevOps and SRE Teams in 2026: Feature and Cost Breakdown</title>
		<link>https://logz.io/blog/best-log-management-software-2026-2/</link>
		
		<dc:creator><![CDATA[Amos Etzion]]></dc:creator>
		<pubDate>Wed, 03 Jun 2026 07:45:50 +0000</pubDate>
				<category><![CDATA[Best of]]></category>
		<category><![CDATA[Blog]]></category>
		<category><![CDATA[DevOps]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[DevOps Community]]></category>
		<category><![CDATA[Observability]]></category>
		<guid isPermaLink="false">https://logz.io/?p=69489</guid>

					<description><![CDATA[TL;DR Picking the right log management platform in 2026 comes down to three things: how much operational overhead you can absorb, how much AI automation you need, and what you&#8217;re willing to spend. Here&#8217;s the short version: ELK Stack / Graylog: Free, but you manage everything. High operational overhead. Splunk: Enterprise-grade and feature-rich, but the [&#8230;]]]></description>
		
		
		
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