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devart

Best ADO.NET Tools for SQLite in 2026

May 11, 2026 By Dereck Mushingairi In Devart
The best ADO.NET tools for SQLite should preserve the speed that makes SQLite worth using in the first place. Recent benchmarks show it completing 100,000 sequential reads in 272 milliseconds, nearly 5x faster than MySQL on the same hardware, because there’s zero network overhead between your app and the database. A slow or poorly matched provider wipes out that advantage. Queries drag, operations behave unpredictably under concurrency, and simple data access turns into a scaling problem.
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netdata

Monitoring Your Azure to Azure Local Migration: One Dashboard for Both Sides

May 11, 2026 By Satyadeep Ashwathnarayana In netdata
More organizations are moving workloads from Azure public cloud to Azure Local (formerly Azure Stack HCI) than most people realize. The reasons vary: data sovereignty requirements, latency-sensitive workloads that need to be closer to the edge, cost optimization for predictable workloads where reserved cloud capacity doesn’t make financial sense, or regulatory constraints that require data to stay on-premises.
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Incident.io

Humans aren't fast enough for 4 9's

May 11, 2026 By Article In Incident.io
When thinking about Service Level Objectives (SLOs) and contractual Service Level Agreements (SLAs) for availability, I always like to put the percentages into concrete numbers. It’s easy to lose track of what’s meant when saying “99.95%” availability, and even more is lost when thinking how much harder it is to achieve 99.99% compared to 99.95%. On a monthly basis, and in concrete terms, 99.95% availability means you get 21 minutes and 55 seconds of downtime.
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AURA in Practice: Mezmo's SRE bot, demo walkthrough

May 11, 2026 By Mezmo In Mezmo
A walkthrough of the Slack-based SRE bot Mezmo's engineering team built on AURA, the open-source agent harness, running against Mezmo's own production tooling. Adrian Furlong shows the bot answering questions in a DM with tool calls visible inline, then in a shared channel where it reads the conversation before responding. He opens a fresh PagerDuty incident on camera. The webhook fires AURA, and within seconds, the agent posts a triage note back on the incident and a structured analysis in the dedicated incident channel.
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Why Mandating AI Tools Backfires on Engineering Teams

May 11, 2026 By GitKraken In GitKraken
Responsible AI adoption for engineering teams starts with culture, not compliance. In this GitKon talk, Rizel Scarlett (Tech Lead of Open Source DevRel at Block) shares how Block helped thousands of engineers actually want to use AI tools, including Goose, Cursor, Claude Code, and more, without mandates, vibe coding disasters, or security gaps.
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upsun

"It works on my machine": why environment parity is still a platform problem in 2026

May 11, 2026 By Upsun In Upsun
How many hours did your team spend last quarter debugging issues that only appeared in one environment? What would change if every environment were guaranteed to be identical? In 2026, environment inconsistency remains one of the most expensive bottlenecks in software development. Developers frequently spend more time debugging differences between infrastructure setups than they do on their own code.
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scout

Best Elixir APM Tools in 2026: A Developer's Guide

May 11, 2026 By Sarah Morgan In Scout
Last updated: May 2026 Elixir applications have performance characteristics that are genuinely different from Ruby or Python. The BEAM virtual machine handles concurrency through lightweight processes, supervision trees restart failed processes automatically, and Phoenix channels can hold tens of thousands of persistent connections on a single node. These are strengths, but they also mean that the performance problems you encounter are different from what most APM tools were built to detect.
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logz.io

The Best Kubernetes Monitoring Tools of 2026

May 11, 2026 By Libi Michelson In logz.io
Effective Kubernetes monitoring in 2026 is critical due to increased cluster scale and microservices complexity, demanding a shift toward unified observability (logs, metrics, and traces). The core focus is leveraging AI-driven features to automate anomaly detection, correlate diverse data, and significantly reduce Mean Time to Recovery (MTTR).
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