Systems | Development | Analytics | API | Testing

Digital Twins for Devs & AI Agents - Record, Replay & Catch Regressions | Keploy

Jun 25, 2026 By Keploy In Keploy
Give your developers — and your AI agents — a digital twin of your live environment. Keploy records real traffic from your live services (no production access, nothing to spin up) and replays it as a faithful twin, so you can continuously verify behavior and catch regressions before they ship. In this demo: record a live service, turn that traffic into integration tests and mocks automatically, replay everything against digital-twin sandboxes, and wire it into CI for continuous verification.
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smartbear

Mobile testing, reimagined: How Reflect's Mobile Testing Changes QA

Jun 25, 2026 By Pratik Pal Bariha In SmartBear
Mobile application users expect flawless experiences on every device, every OS version, and every screen size, and they have little patience for anything less. Yet for QA teams, achieving that level of coverage traditionally means wrestling with brittle automation scripts, complex Appium setups, and endless device fragmentation. Even after all this manual effort, your mobile app quality could contain unseen gaps.
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kong

Moving from Probabilistic Reasoning to Deterministic Execution

Jun 24, 2026 By Hugo Guerrero In Kong
Generative AI systems do not fail because models are weak. They fail because architectures are incomplete. Once organizations accept that prompts cannot guarantee reliability, a new challenge emerges: how to design systems that systematically convert successful AI behavior into repeatable, governable, and auditable workflows.
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smartbear

TestComplete vs. Reflect: Which SmartBear test automation platform fits your team?

Jun 24, 2026 By Rob McNeil In SmartBear
Not every test automation problem looks the same. A team maintaining complex desktop applications in a controlled financial services environment has different automation needs than a team shipping web and mobile updates every two weeks. The application, the environment, and the people creating tests all shape what “good automation” has to do.
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kong

Why We Need to Stop Prompt Hacking

Jun 23, 2026 By Hugo Guerrero In Kong
Generative AI has completely changed the landscape of enterprise automation, knowledge work and operational efficiency. In 2026, the question is no longer whether these models can perform complex tasks, but whether they can do so reliably enough for mission-critical systems. Despite the availability of sophisticated models and expansive context windows, technology leaders continue to face frustration. Organizations struggle to produce consistent and repeatable results.
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speedscale

The Kubeshark Workflow That Doesn't Stop at the Dashboard

Jun 22, 2026 By Matthew LeRay In Speedscale
The Observability Gap shows up the moment you try to reproduce a production bug locally. Your traces tell you a request was slow. Your logs tell you which line printed. Neither tells you what was actually on the wire: the headers, the JSON body, the surprise field your client started sending last Tuesday. Until now, closing that gap meant SSHing to a node, attaching a debugger, or shipping a sidecar through change review.
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kong

From Kong Konnect to Insomnia: A Developer Workflow for Testing Gateway APIs

Jun 22, 2026 By Juhi Singh In Kong
As API ecosystems grow, developers and platform teams often work in separate environments. Platform teams manage APIs, gateways, and governance centrally, while developers recreate those configurations locally for testing and debugging. Over time, this can lead to configuration drift, inconsistent workflows, and security gaps. The release introduces our first native Kong Konnect integration, allowing developers to discover, import, and test Gateway configurations directly from Konnect.
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speedscale

Beware of PII in Testing Data: The Security Iceberg and Where PII Actually Hides

Jun 19, 2026 By Speedscale Team In Speedscale
If you run a platform tools or security team, you have likely heard this request from developers: “I just need a copy of the production database for staging so I can run realistic load and integration tests.” It is a completely reasonable request. Production traffic and data contain the actual request shapes, real-world value distributions, long-tail anomalies, and timing patterns that make tests useful.
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Automatically catch API drift before your users do | Swagger Contract Testing

Jun 19, 2026 By SmartBear In SmartBear
our API didn't break – it just stopped matching its contract. API drift is one of the sneakiest problems in modern API development. Your OpenAPI definition says one thing, your running implementation does another, and nobody notices until a consumer integration fails or a user hits an unexpected error. The longer it goes undetected, the harder it is to trace back to the source.
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