Operations | Monitoring | ITSM | DevOps | Cloud

Stop Spending Hours on Slides: Use This Free AI Tool Instead

Stop Spending Hours on Slides: Use This Free AI Tool Instead

Dec 3, 2025 By OpsMatters In OpsMatters
In nowadays society, time is our most valuable asset. Whether you are a social media manager creating a monthly report or a startup founder pitching to investors, the pressure to deliver visually stunning slides is constant. However, traditional slide design is often a bottleneck. Enter the era of the ppt ai maker. These intelligent tools are no longer just a futuristic concept; they are essential productivity hacks for anyone looking to scale their output without sacrificing quality.
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datadog

Observability in the AI age: Datadog's approach

Dec 2, 2025 By Yanbing Li In Datadog
Ten years ago, Datadog was a single-product company focused on breaking down the silos between dev and ops. As the shift towards the cloud accelerated and organizations transitioned to the new DevOps model, we set out to develop an observability platform that would enable these teams to safely scale faster and answer the essential questions about their services: are they available, secure, compliant, performant, and cost-efficient?
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ScienceLogic

Part 1: What If Data Wasn't Just the Fuel for AI but the Foundation of Everything It Knows?

Dec 2, 2025 By ScienceLogic In ScienceLogic
Every breakthrough begins with a question. What if we looked beyond today’s tools, buzzwords, and hype and examined the design principles shaping tomorrow’s intelligent enterprises? The What If series explores those inflection points: moments where technology meets human judgment, where automation meets accountability, and where AI begins to resemble something more like understanding than output.
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Enhancing Productivity with Predictive Analytics and AI

Dec 2, 2025 By Ivanti In Ivanti
Dex aims to improve productivity and strategic leadership through predictive analytics and AI solutions. It highlights proactive problem-solving and the necessity for visibility in monitoring systems. Leadership is urged to understand how IT affects staff satisfaction and business outcomes. Immediate goals focus on enhancing visibility, while long-term strategies should align Dex's results with business priorities to secure support and investment.
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Datadog Bits AI SRE: Your new teammate for on-call shifts

Dec 2, 2025 By Datadog In Datadog
Bits AI SRE is an always-on SRE agent built to handle complex troubleshooting and late-night alerts. Developed against thousands of real-world incidents and powered by Datadog’s platform, Bits AI SRE analyzes your entire stack, tests hypotheses, and identifies root causes in minutes. Resolve faster, get back to sleep sooner, and give your on-call team the confidence and capacity they need.
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Your AI Needs Git Context. Meet GitKraken MCP

Dec 2, 2025 By GitKraken In GitKraken
Give your AI-assistants and agents the repo context they need with GitKraken MCP. Now bundled with GitLens for IDEs. Give your agents full Git context, streamline decisions, and work faster across VS Code, Cursor, and your favorite AI tools. See how MCP connects your repos, providers, and Git into one smart, seamless layer if Git intelligence your agents and you can use. Perfect for developers building with AI. Perfect for teams who want clarity, speed, and zero context loss.
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upsun

Managing cloud infrastructure with AI assistant and Upsun MCP server

Dec 2, 2025 By Anita Okem-Achu In Upsun
Artificial intelligence is changing the way we execute our everyday operations. AI assistants are incredibly intelligent; they can write code, explain complex concepts, and answer any question you throw at them. However, they can't execute actions on their own. If you ask your AI assistant to “create a backup of my database,” it may provide you with clear instructions, run the CLI commands directly or in some cases, even trigger actions through connected agent workflows.
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cloudzero

Mastering AI Spend With CloudZero And LiteLLM

Dec 2, 2025 By Kaitlin Woo In CloudZero
The AI landscape today feels a lot like the early days of the cloud: exciting, fast-moving, and completely fragmented. Every week, engineering teams are experimenting with dozens of large language models (LLMs) from providers like OpenAI, Anthropic, Google, Mistral, Meta, and beyond. They’re tweaking prompts, testing model performance, swapping context windows, and even running multiple models in parallel to figure out which one works best for each unique use case.
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