InfluxDB 3 MCP Server v1.3.0: AI Access to Time Series Data
A more reliable agent that learns your schema, queries your data, and investigates alerts - that’s what’s possible with this release of our MCP server v1.3.0.
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Building Agents that Remember: The OpenSearch Developer Tier
OpenSearch isn't just a search engine anymore. Recent releases moved it into AI infrastructure: agentic memory built in, Better Binary Quantization (BBQ) compressing vectors 32x, token-usage tracking, and a one-command Observability Stack. A stack for building practical AI applications, not just indexing. The catch is that production-sized OpenSearch clusters aren't where you want to prototype.
Data Science Services for Enterprises: Use Cases, Stack, Vendor Selection
Day after day, large-scale enterprises generate terabytes of information: supply logs, transactions, equipment telemetry, CRM data, and never-ending reports. Most executives realize there is a major asset hidden within this information. But how can unfiltered findings be transformed into yielding profits?
Top 5 AI-Powered Database Query Tools for Data Analysts
Data analysts spend a large part of their workday translating business questions into database logic. A stakeholder asks why revenue changed. A product manager wants to compare cohorts. A finance team needs a variance explained. The question may sound simple, but the path to the answer often involves finding the right tables, understanding how fields are defined, writing SQL, validating joins, checking filters, and making sure the result matches the intended business meaning.
How to Build a Data-Driven SEO Strategy: From Audit to Actionable Insights
You publish great content. You tweak your titles. You build a few backlinks. And yet - your traffic stays flat, your rankings barely budge, and your competitors seem to leapfrog you effortlessly. Sound familiar? The problem isn't effort. The problem is guesswork. Most SEO strategies fail because they treat optimization as an art rather than a science. They skip the foundational step of understanding what's actually broken on their site, which keywords genuinely move the needle, and how to use data to make smarter decisions every step of the way.
Exploring Powerful Power BI Dashboards for Smarter Decision-Making
Operational dashboards help teams answer urgent business questions quickly. They show whether production is on track, inventory is healthy, downtime is rising, or resources are being stretched too thin. This article explores practical Power BI dashboard examples for operational efficiency across production, supply chain management, resource planning, and performance measurement. It also explains how to build dashboards that support real decisions rather than simply displaying data.
A Runnable Reference Architecture for Industrial IoT on InfluxDB 3
Industrial teams keep telling us the same thing: the data is there, but the stack to act on it isn’t. PLCs, CNCs, SCADA systems, vibration sensors, and quality stations all generate high-frequency telemetry that gets stranded in proprietary historians or stitched together with point integrations nobody wants to own. By the time anyone looks at it, the moment to act has passed.
The product analytics you already have
You already have everything you need. If you’re using Sentry, you have traces, structured logs, and now application metrics. Most teams use that stuff for debugging and stop there. But get this: that same data can answer most of the product questions you’ve been sending to a separate analytics tool, maintained by a separate team, with a separate data model and a separate bill. (Not all of them.
A Runnable Reference Architecture for Network Telemetry on InfluxDB 3
Networks generate the most data of any system in your stack and have the least patience for stale dashboards. Interface counters tick every second. BGP sessions flap. Flow records arrive in bursts. When something goes wrong, you don’t have 10 seconds to wait for an aggregation to finish.
Get Kafka-Nated S2E5: Nobody Understands Kafka Costs
In this episode of Get Kafka-Nated, host Hugh Evans is joined by Stanislav Kozlovski, Apache Kafka committer, independent consultant, and author of 2 Minute Streaming — a newsletter with over 7,000 subscribers. After six years at Confluent, including time on the Kafka Serverless team, Stan went independent and has been writing and consulting full-time. He's one of the most recognised voices in the Kafka community, with over 50k followers across social media. In this session we go somewhere the streaming industry rarely goes honestly: Kafka costs.