Systems | Development | Analytics | API | Testing

Ep 80 | Decision Logic: The Difference Between an Answer and a Decision

Jul 27, 2026 By Cloudera, Inc. In Cloudera
Ask an AI system a question, and you'll get an answer. Decision logic determines whether you should trust it. In this episode of The AI Forecast, Paul Muller sits down with Darlene Newman, Innovation Lead at Duczer East, to explore the hidden layer that helps AI move from pattern matching to practical decision-making.
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The Best Tier 1 SOC Automation Tools in 2026

The Best Tier 1 SOC Automation Tools in 2026

Jul 27, 2026 By SystemsDigest In SystemsDigest
Tier 1 SOC is alert triage, enrichment, initial investigation, and escalation. Most of this work is repetitive and hard to scale, and legacy options for automating it (e.g., SOAR) can't keep pace with modern workloads because they're engineering-led, not analyst-led or browser-based (where the actual work happens). The tools below automate tier 1 work, and all of them use AI in some way. They range from AI SOC analysts that investigate alerts the way a human would to automation platforms with AI layered on top, plus AI built into platforms you may already run.
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yellowfin

Beyond Static KPIs: Leveraging Augmented Analytics for Predictive Business Growth

Jul 26, 2026 By Hagop Panosian In Yellowfin
In volatile markets, a KPI dashboard that only tells you what happened last week is already too late to guide confident action. Many companies have dashboards. Fewer have KPI systems that help them spot revenue shifts, retention risk, margin pressure, or supply-chain trouble before those issues hit the business hard. That gap is where augmented analytics comes in.
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speedscale

Two confident fixes missed this production bug

Jul 24, 2026 By Ken Ahrens In Speedscale
Every new signup posts a message to our Slack. The format is dull and reliable: Overnight this week one arrived like this: That trailing nothing was the entire incident. No error logs, no alerts. A returning user had signed up, our signup service had attached them to a tenant we deprovisioned back in December, and the only symptom in the whole company was a Slack message that ran out of words.
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ClearML

Managing Across Schedulers: HPC Meets Kubernetes

Jul 24, 2026 By Adam Wolf & Damian Erangey In ClearML
Almost every infrastructure team running modern AI is wrestling with the same question. The orchestrator their AI workloads want, Kubernetes, and the orchestrator their HPC environment was built on, Slurm, pull in different directions. This piece, drawn from the HPCKP 2026 session of the same name, looks at why that tension exists, what the workloads actually look like, how teams are bridging the two today, and where the pattern is heading.
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smartbear

What Is the SmartBear Zephyr Agent for Rovo? AI testing in Jira, explained

Jul 24, 2026 By Alisha Siddhartha In SmartBear
AI can now handle the slowest parts of test management, inside Jira. – The Zephyr Agent for Rovo creates test cases and links them to your work items, in the projects where your team already plans and builds. This guide covers how testing is changing in the AI age, what the agent is, where to find it, and how to run your first task.
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smartbear

API definition-native AI testing: Support faster, confident shipping with your existing Swagger and OpenAPI specification

Jul 24, 2026 By Vyshnavi Dabbir In SmartBear
APIs are the backbone of modern software. They connect microservices, power mobile experiences, and make integrations possible across industries. For all their importance, API testing remains one of the most fragmented, manual, and maintenance-heavy parts of the software development lifecycle (SDLC). So as development accelerates in an AI-disrupted SDLC, application integrity – continuous, measurable assurance that your software just works as intended – becomes harder to maintain, not easier.
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katalon

Building a Playwright AI Agent: How Claude Code Drives Katalon True Platform End to End

Jul 24, 2026 By Huy Tieu In Katalon
Claude Code shipped workflows: reusable, versioned instructions an agent can follow instead of improvising a process from scratch each time. We used that feature to hand Claude Code our entire QA job. Not "write a test case." The whole loop: read the requirement, design the coverage, run it on the platform, file the defect, report back with evidence. The kind of work a QE does in a day, compressed into one skill triggered with a sentence.
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databox

AI Marketing Forecasting: The Plan Is Only as Good as the Data It Can See

Jul 24, 2026 By Nevena Rudan In Databox
Ask a Marketing Lead how the quarterly plan actually gets built. Not the strategy, the mechanics. The answer, in most teams, is a spreadsheet: spend pulled from five ad platforms with five different backends, pipeline exported from the CRM, last quarter’s numbers copied from a deck, targets negotiated in a separate thread. One customer described their version of it to us in a sentence that needs no editing.
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