Operations | Monitoring | ITSM | DevOps | Cloud

elastic

From noise to knowledge: How GenAI is revolutionizing log management and analytics

May 8, 2026 By Elastic Observability Team In Elastic
Focusing on GenAI and logs for IT efficiency Efficiency is everything for managing today’s digital systems. Technology is constantly transforming and expanding operations are driving an explosion in data. Consequently, data ingest and storage costs have soared. But it’s not just storage data costs that keeps teams behind.The challenge of managing all that observability data forces IT teams to choose between efficiency and the bottom line.
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upsun

The zero-trust agent: why your AI needs a sandbox, not a blank check

May 8, 2026 By Upsun In Upsun
Key takeaway: Granting AI agents unrestricted access to cloud infrastructure is an unacceptable security risk. Upsun provides a "zero-trust" framework by utilizing isolated, production-perfect preview environments that allow AI to be productive without the risk of a hallucinated production outage.
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Real-Time Analytics Is Quietly Reshaping Network Operations and Service Assurance for Modern CSPs

Real-Time Analytics Is Quietly Reshaping Network Operations and Service Assurance for Modern CSPs

May 8, 2026 By OpsMatters In OpsMatters
For years, telecom operators treated analytics as a reporting layer. Data went into dashboards, engineers reviewed incidents after the fact, and performance reports helped leadership understand what had already gone wrong. That model is starting to break. Modern telecom infrastructure changes too quickly for delayed analysis to be useful. A latency spike inside a cloud-native core can ripple across services in seconds. A software bug in one region can affect thousands of enterprise users before a traditional monitoring workflow even flags the issue.
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Founder keynote: Human-AI collaboration at scale | Team '26 | Atlassian

May 7, 2026 By Atlassian In Atlassian
It’s time to reimagine teamwork for the AI era. Join Atlassian leaders to hear how human-AI teams collaborating in one system of work will propel your entire organization forward. About Atlassian: Behind every great human achievement, there is a team. From medicine and space travel to disaster response and pizza deliveries, we help teams all over the planet advance humanity through the power of software. Our mission is to help unleash the potential of every team.
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civo

What is sovereign AI, and why does it matter for your business?

May 7, 2026 By Emma Kinsey-Coates In Civo
With AI reshaping every corner of the modern business, the highest-value workloads are often locked behind complex regulatory frameworks. Yet many organizations are still running them on infrastructure they don't fully control, trusting external platforms to decide where their data lives, where workloads run, and how their AI operates. Civo was built to change that.
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upsun

Infrastructure for AI Agents: what platform teams need to build now

May 7, 2026 By Upsun In Upsun
If an AI agent in your development workflow needed to spin up a test environment tonight, how many manual steps would stand between the request and the environment being ready? By early 2026, AI agents have transitioned from simple code assistants to first-class platform citizens. They are running test suites, analyzing performance, and triggering deployments.
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cloudzero

Why I Give My Engineers $5,000 Per Month Of Claude Code Tokens

May 7, 2026 By Bill Buckley In CloudZero
A few weeks ago, a group of engineering leaders I trade notes with got into it over a question none... A few weeks ago, a group of engineering leaders I trade notes with got into it over a question none of us has a clean answer to: How much should you let an engineer spend on AI? One SVP at a company of similar size and stage is in calibration mode and capping engineers at $200 per month. Hit the cap, you can self-bump by $100. Hit that, you need your manager. I told the thread our number. $5,000.
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onpage

AI matched or beat physicians on real-world clinical reasoning

May 7, 2026 By Ritika Bramhe In OnPage
A major new study from Harvard Medical School and Beth Israel Deaconess Medical Center has found that a large language model (LLM) outperformed physicians across a wide range of clinical reasoning tasks, including making emergency-room triage decisions from messy, real-world patient data. The findings, published April 30 in Science, represent one of the largest comparisons yet between AI and physicians on clinical tasks.
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