High TTFB After Frontend Fixes? The Real Culprits Are Server-Side

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A high Time to First Byte (TTFB) can persist even after deploying a CDN, caching plugins, and theme optimizations, pointing to unresolved server-side issues. On WordPress and PHP stacks, the root causes often include excessive PHP execution, slow database queries, remote API calls during page builds, and background jobs competing for server resources. WordPress's default WP-Cron system runs scheduled tasks on page requests, meaning heavy jobs like backups, sitemap builds, or security scans can delay real visitor responses. Developers are advised to disable request-driven WP-Cron and instead trigger scheduled tasks via system cron at fixed intervals to reduce contention. Auditing scheduled events, reviewing object cache usage, and examining query counts are recommended diagnostic steps before considering a hosting upgrade.

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How IoT Architecture Enables Scalable Telecom Tower Monitoring at Scale

Telecom towers house complex infrastructure—including power systems, generators, cooling units, and security equipment—that is difficult to supervise efficiently through traditional periodic inspections. A modern IoT monitoring architecture connects heterogeneous site equipment through edge gateways, normalizes telemetry, and transmits operational data to a centralized platform. A key design principle is correlating related data points rather than treating sensor readings in isolation, such as linking grid outages, battery switchovers, and generator startups into a single operational event. Fuel levels, environmental conditions, and security alerts can similarly be cross-referenced to distinguish normal activity from anomalies. The primary engineering challenge is ensuring the architecture remains reliable and consistent as the number of monitored towers, vendors, and data streams continues to grow.

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ProgrammingDEV Community ·

Go 1.26 iterators spark debate over language complexity vs. readability

Go, long praised for its simplicity, introduced iterator support via range-over-func syntax in Go 1.23 (August 2024), expanding further in Go 1.26 (February 2026) with iterator-based reflection methods. The changes require developers to understand push/pull iterators, yield callbacks, and boolean early-termination signals — concepts critics say replace what simple for-loops already handled. Benchmarks by Val Deleplace (September 2024) and researcher Rost Glukhov (January 2025) found custom iterators are generally slower than classical approaches, with the trade-off described as largely aesthetic. A new library called Iterium, released in 2026, brought lazy pipeline functions like Map, Filter, and TakeWhile to Go, drawing comparisons to Rust's iterator model. The community remains divided, with some welcoming the expressiveness and others arguing the additions undermine Go's founding principle that clarity matters more than cleverness.

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ProgrammingDEV Community ·

Four CI checks stayed green while broken — a team's account of silent pipeline failures

A software team discovered that four separate automated checks in a single repository had stopped being able to detect failures, yet continued showing green status in their CI pipeline. Among the issues was a GitHub Actions lint job where the tool's timeout matched the job's timeout, causing silent cancellations instead of diagnosable errors across three consecutive commits. A .gitattributes line-ending rule that appeared fixed locally left over 1,200 files with incorrect CRLF endings in pre-existing working trees, with CI and local environments reporting wildly different counts. A guard written to prevent the timeout misconfiguration from recurring falsely flagged a comment in the workflow file, because it scanned raw text without distinguishing code from prose. The team concluded that a check which cannot fail is more dangerous than a broken one, since silent false-positives eventually train developers to ignore alerts altogether.

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ProgrammingDEV Community ·

Developer Refactors Link View Tracking System to Fix N+1 and Duplicate Count Bugs

A developer has refactored the view-tracking system in their open-source link tool, which previously cached link views in Redis and flushed them every 10 seconds using a manual loop. The old approach suffered from an N+1 problem, where each link ID triggered a separate database update, risking resource exhaustion under heavy traffic. It also caused duplicate view counts because cached data was never cleared after flushing, and wasted resources by running updates even when no data existed. The new system uses Redis's hGetAll to fetch all views at once, validates that data exists before proceeding, and batches all updates into a single bulkWrite database operation. Cached views are only deleted after the database acknowledges the write, ensuring no data is lost if the server crashes mid-process.

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