# Logging Logging is the creation and management of records of events occurring in computing assets, including platforms, networks, services, and cloud environments. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Profiling App Engine Memcached DevFeed: [Profiling App Engine Memcached]() Original publisher: [Read original article]() Author: Khan Academy Published: 2017-05-01T22:00:00Z Content type: article Language: en Sources: [Khan Academy]() Topics: [Latency](), [Logging](), [Data structures]() Tags: [engineering](), [infrastructure](), [latency](), [logging](), [memcached](), [news](), [patterns](), [profiling](), [tests]() ### AI overview Khan Academy engineers profile App Engine Memcached to estimate access latency and evaluate whether on-demand content fetching could support separate content trees for each language. Most requests showed 1-4 ms latency, usually below 10 ms, while a single multi-get performed similarly to a single get. ### Source excerpt By Ben Kraft Last year, Willow wrote about how we optimized our in-memory content data to take up ... Read more ## A Threat Hunter's Guide to Detecting Malicious Activity in GitHub Audit Logs DevFeed: [A Threat Hunter's Guide to Detecting Malicious Activity in GitHub Audit Logs]() Original publisher: [Read original article]() Author: Julie Agnes Sparks, Juvenal Araujo Published: 2026-09-16T00:00:00Z Content type: article Language: en Sources: [Datadog Security Labs]() Topics: [GitHub](), [Threat Hunting & Intel](), [Security](), [Logging](), [Authentication](), [personal access token]() Tags: [authentication](), [github](), [logging](), [oauth](), [personal-access-token](), [secrets](), [security](), [security-research]() ### AI overview This article examines threats targeting GitHub organizations, including compromised accounts, personal access tokens, OAuth tokens, leaked secrets, phishing, and malicious extensions or OAuth apps. It describes GitHub audit-log queries and behaviors that can help detect account compromise, reconnaissance, and source-code exfiltration. ### Source excerpt In this post, we walk through different threats to GitHub and how to detect them. ## CISA's Logging Reference Architecture for OMB M-26-14: What federal agencies should do next DevFeed: [CISA's Logging Reference Architecture for OMB M-26-14: What federal agencies should do next]() Original publisher: [Read original article]() Author: Woody Walton Published: 2026-09-16T00:00:00Z Content type: article Language: en Sources: [Elastic Blog - Elasticsearch, Kibana, and ELK Stack]() Topics: [cisa](), [Logging](), [cybersecurity and infrastructure security agency](), [log management](), [Architecture & Design](), [implementation](), [audit](), [Security]() Tags: [architecture](), [audit](), [cisa](), [cybersecurity-and-infrastructure-security-agency](), [cybersecurity-open-source-standards-log-management-government](), [government](), [implementation](), [logging](), [logs](), [public-sector](), [security]() ### AI overview This Elastic blog explains CISA's Logging Reference Architecture for OMB M-26-14 and the actions federal civilian executive branch agencies must take. It highlights planning and maturity deadlines, recommends assessing existing capabilities and documenting gaps, and discusses storage tiers, retrieval, immutability, and audit requirements. ### Source excerpt Now that CISA has released its Logging Reference Architecture (LRA) for OMB M-26-14, federal agencies tasked to complete their logging plans. In this blog, we walk you through the most important aspects of the LRA guidance. ## AWS Security Reference Architecture: A deep dive into PCI DSS compliance DevFeed: [AWS Security Reference Architecture: A deep dive into PCI DSS compliance]() Original publisher: [Read original article]() Author: Avik Mukherjee Published: 2026-09-14T17:46:56Z Content type: article Language: en Sources: [AWS Security Blog]() Topics: [Amazon Web Services](), [Security](), [Architecture & Design](), [Network Segmentation](), [Encryption](), [Logging](), [Access Control](), [Cloud]() Tags: [access-control](), [amazon-web-services](), [announcements](), [architecture](), [compliance](), [encryption](), [foundational-100](), [logging](), [network-segmentation](), [pci-dss](), [security](), [security-blog](), [security-identity-compliance]() ### AI overview AWS announces the AWS Security Reference Architecture (AWS SRA) PCI DSS Deep Dive, a guide that extends the core AWS SRA with prescriptive architecture-level guidance for organizations handling cardholder data on AWS. It explains how AWS SRA patterns address PCI DSS concerns including account scoping, network segmentation, encryption, logging, and access control. ### Source excerpt Amazon Web Services (AWS) is excited to announce the publication of the AWS Security Reference Architecture (AWS SRA) Payment Card Industry (PCI) Data Security Standard (DSS) Deep Dive. This new guide extends the core AWS SRA to provide prescriptive, architecture-level guidance for organizations that store, process, or transmit cardholder data on AWS. Organizations subject to [...] ## Percona Operator for PostgreSQL 3.1.0: Transparent Data Encryption, Logical Replicas, and Persistent Logging DevFeed: [Percona Operator for PostgreSQL 3.1.0: Transparent Data Encryption, Logical Replicas, and Persistent Logging]() Original publisher: [Read original article]() Author: Slava Sarzhan Published: 2026-09-09T16:08:31Z Content type: release Language: en Sources: [Blog - Percona]() Topics: [PostgreSQL](), [Encryption](), [Logging](), [Kubernetes](), [Open Source]() Tags: [cloud](), [encryption](), [hashicorp-vault](), [kubernetes](), [logging](), [open-source](), [operator](), [percona](), [percona-operator-for-postgresql](), [postgresql](), [release](), [replication](), [security](), [slavasarzhan-pg]() ### AI overview Percona Operator for PostgreSQL 3.1.0 adds transparent data encryption with pg_tde, logical replicas for read-only workloads, and persistent logging across Pod restarts. The release also adds official RKE2 support and full ARM64 images. ### Source excerpt Percona Operator for PostgreSQL 3.1.0 takes on three things that decide whether a PostgreSQL platform passes review: is the data encrypted at rest, can it serve reads without straining the primary, and are the logs there when you need them. This release answers all three inside the custom resource, so none of them is a ... Continued The post Percona Operator for PostgreSQL 3.1.0: Transparent Data Encryption, Logical Replicas, and Persistent Logging appeared first on Percona. ## When the action succeeds and the audit write doesn't DevFeed: [When the action succeeds and the audit write doesn't]() Original publisher: [Read original article]() Author: WorkOS Published: 2026-09-04T00:00:00Z Content type: article Language: en Sources: [WorkOS Blog]() Topics: [Logging](), [systems](), [payload]() Tags: [audit](), [distributed-transaction](), [logging](), [metric](), [retry]() ### AI overview The article examines why audit logs can become unreliable when an application performs an action and writes its audit record as separate operations. It describes silent gaps, phantom events, and duplicate events caused by failures, ordering, and retries, emphasizing that audit records must remain trustworthy evidence. ### Source excerpt When the action succeeds and the log write fails, you get a gap that nothing alerts on. Here is the write path that closes it. ## 5 Billion Records, 10 Terabytes, Four Weeks: A Real Data Migration Playbook DevFeed: [5 Billion Records, 10 Terabytes, Four Weeks: A Real Data Migration Playbook]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-09-02T07:27:50Z Content type: article Language: en Sources: [Wix Engineering]() Topics: [migration](), [data](), [Databases](), [API](), [Logging](), [Tech Debt]() Tags: [api](), [data](), [database](), [logging](), [migration](), [tech-debt]() ### AI overview This Wix engineering article presents a data migration playbook based on lessons from large and complex migrations. It argues that success depends less on changing tooling than on identifying recurring problems before migration begins, especially by auditing inconsistent source data, implementing a read phase, and logging suspicious fields and structures. It also outlines using a V2 API, an API proxy, population-based rollout, change data capture, continued synchronization, and eventual decommissioning of V1. ### Source excerpt By the time you finish reading this, someone at Wix is probably in the middle of a data migration. We've run migrations that lasted anywhere from a few months to two years. More recently, we've completed large and complex migrations in a few weeks. The difference wasn't the tooling, which barely changed. It was that we had finally learned which problems show up in every migration, and started dealing with them before the migration began instead of in the middle of it. Recap: Why We Migrate,... ## OpenTelemetry Go Logs API and SDK reach release candidate status DevFeed: [OpenTelemetry Go Logs API and SDK reach release candidate status]() Original publisher: [Read original article]() Author: OpenTelemetry Authors; Docs CC BY Published: 2026-08-31T15:40:58Z Content type: release Language: en Sources: [Blog on OpenTelemetry]() Topics: [OpenTelemetry](), [Go Language](), [releases](), [SDKs](), [Logging]() Tags: [api](), [beta](), [experimental](), [go](), [opentelemetry](), [release](), [sdk](), [version]() ### AI overview OpenTelemetry Go v1.47.0-rc.1 promotes the Logs API and SDK to release candidate status. The release moves these modules from beta stability toward stable v1 compatibility guarantees, while log exporters and logtest remain experimental and outside the RC scope. ### Source excerpt OpenTelemetry Go v1.47.0-rc.1 is here. This release promotes the Logs API and SDK to release candidate (RC), the final stage before we provide stable v1 compatibility guarantees. We believe the design is ready, and now we need the community to test it in real applications and integrations before those guarantees take effect. What is included in the release candidate? The RC covers these two modules: go.opentelemetry.io/otel/log go.opentelemetry.io/otel/sdk/log These modules move from v0.22.0, with beta stability, to v1.47.0-rc.1. The version aligns them with the other stable OpenTelemetry Go modules, which share a coordinated version number. The log exporters and logtest modules remain experimental and are not covered by this RC's stability scope. ## How Fly.io logging works and how to collect application logs DevFeed: [How Fly.io logging works and how to collect application logs]() Original publisher: [Read original article]() Author: Muhammed Ali Published: 2026-08-13T07:00:00Z Content type: tutorial Language: en Sources: [Honeybadger]() Topics: [fly.io](), [Logging](), [App](), [FastAPI](), [Streams](), [Deployment]() Tags: [app](), [deployment](), [devops-articles](), [fastapi](), [fly-io](), [guide](), [how-to](), [logging](), [streams](), [vector]() ### AI overview This tutorial explains how Fly.io collects and routes application logs, including output from standard output and standard error. It also demonstrates a FastAPI application that generates different log messages and describes handling logs with Honeybadger. ### Source excerpt Logging is an import part of debugging an app. Without a good method of catching errors or logs in general, you would end up with uncaught issues and could also lose valuable customers in the process. Read this article to learn how to effectively handle logs on Fly.io. ## Pulumi v3.254.0 Adds Automatic Encrypted Logging DevFeed: [Pulumi v3.254.0 Adds Automatic Encrypted Logging]() Original publisher: [Read original article]() Author: Thomas Gummerer Published: 2026-08-10T00:00:00Z Content type: release Language: en Sources: [Pulumi]() Topics: [Logging](), [debugging](), [Encryption]() Tags: [debugging](), [encryption](), [environment-variables](), [features](), [github](), [logging](), [logs](), [observability](), [product]() ### AI overview Pulumi v3.254.0 automatically creates encrypted log files for every operation, allowing users to share existing logs with the Pulumi team for debugging. Logs use AES256-GCM encryption, rotate after seven days or when they reach 500 MB, and can be decrypted locally with pulumi logs decrypt. ### Source excerpt Pulumi v3.254.0 introduces automatic logging: every operation is logged in an encrypted log file that can optionally be shared with the Pulumi team for inspection. No more re-running commands just to get logs to the Pulumi team for debugging; instead you can share existing logs securely. You might have been in a situation where pulumi hit an error for an unexpected reason, or did something that was not quite right. Currently the process for trying to resolve that is to try and reproduce the error, ideally now with logging enabled. Sometimes the error doesn't reproduce, or the state pulumi was in at the time of the error doesn't exist anymore. And even if the issue reproduces it's a bit of a hassle to do all this again, just to get logs to Pulumi employees who can do something with them. There's also no great mechanism to send the potentially sensitive log file. How it works From pulumi v3.254.0 onward, we automatically produce log files for every operation and store them in $PULUMI_HOME/logs. These log files are encrypted on disk, using the relevant stack's secret manager, whenever it is available, as they still contain secrets at this point. The final file consists of gzip'd chunks that are encrypted using AES256-GCM. Log files are gzip'd when no secrets manager is available, as no secrets from property values can be in the log at that point. Note that the logs are rotated out after 7 days, or after the log directory has reached 500 MB, removing the oldest logs first. This way logs will never fill up your disk, but will still be available after running pulumi commands. These defaults can be overridden with the PULUMI_LOG_ROTATION_MAX_AGE_DAYS and PULUMI_LOG_ROTATION_MAX_TOTAL_MB environment variables. Locally these logs can be decrypted using pulumi logs decrypt. For this to work the same stack's secret manager as was used for the command needs to be available. Sharing logs Previously there was no good way to securely share the logs with us. Users were always force ## New release of LLM adds support for reasoning traces, OpenAI Responses, server-side tools, and smarter logging DevFeed: [New release of LLM adds support for reasoning traces, OpenAI Responses, server-side tools, and smarter logging]() Original publisher: [Read original article]() Author: Simon Willison Published: 2026-08-04T23:58:24Z Content type: release Language: en Sources: [Simon Willison]() Topics: [Tool](), [Command-line interface](), [API](), [Large Language Model](), [SQLite](), [Logging](), [OpenAI](), [Claude](), [Model Context Protocol](), [gemma4]() Tags: [ai](), [ai-2-235](), [anthropic](), [anthropic-336](), [cli](), [gemma](), [generative-ai](), [generative-ai-1-981](), [llm](), [llm-631](), [llm-reasoning](), [llm-reasoning-103](), [llm-tool-use](), [llm-tool-use-75](), [llms](), [llms-1-947](), [logging](), [mcp](), [model-context-protocol](), [model-context-protocol-35](), [openai](), [openai-463](), [projects](), [projects-553](), [release](), [releases](), [releases-31](), [responses](), [server](), [sqlite]() ### AI overview LLM 0.32 adds visible reasoning traces, server-side provider tools, redesigned content-addressable SQLite logs, support for the GPT-5.6 model family, and features enabled by the OpenAI Responses API. The release also updates the llm-anthropic plugin and adds Python API changes. ### Source excerpt I released LLM 0.32 this morning, the most significant new version of LLM since the initial launch of the project. The new version includes support for visible reasoning traces, server-side provider tools, redesigned content-addressable SQLite logs, new models, and new features enabled by the OpenAI Responses API. I also released a new version of the llm-anthropic plugin with substantial updates of its own. Headline features for LLM CLI users Running LLM against reasoning models now displays their reasoning traces to standard error, so you can see what they are "thinking" without that information being included in the standard output that you might pipe to another tool. Add -R/--hide-reasoning to turn this off. LLM includes support out-of-the-box for the GPT-5.6 model family, and the new default model used with llm "prompt" is now the inexpensive but capable GPT-5.6 Luna. LLM calls can now use server-side tools from various providers. OpenAI provide a code execution environment as a server-side tool; LLM can now run prompts that benefit from that like so: llm --tool CodeInterpreter 'Show current python and SQLite versions' OpenAI also gets a WebSearch tool. The llm-anthropic plugin adds WebSearch, WebFetch, CodeExecution, and AnthropicMCP, which looks like this: llm -m claude-sonnet-5 -T 'AnthropicMCP("https://datasette.simonwillison.net/-/mcp")' \ 'how many rows in the blog_blogmark table?' That causes Anthropic to execute MCP calls against my new datasette-mcp plugin as part of a single request/response interaction with their API. The new llm openai endpoint command provides a tool for executing prompts against any OpenAI compatible endpoint as a one-liner. These aren't logged, which makes this a handy tool for running one-off prompts against anything that speaks the lingua franca of the LLM API world. Here's how I use that to run prompts against Gemma 4 12B running in my localhost LM Studio API, via uvx (no LLM installation required) and mixing in the llm-tools-q ## The state of docs traffic: a 2026 midyear report DevFeed: [The state of docs traffic: a 2026 midyear report]() Original publisher: [Read original article]() Author: Kyan Yang Published: 2026-07-29T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [Model Context Protocol](), [Logging](), [Server]() Tags: [2026](), [agent](), [ai-trends](), [clients](), [docs](), [mcp](), [report](), [retrieval](), [search](), [servers](), [tool]() ### AI overview Mintlify's 2026 midyear report examines how agents access documentation. It reports that agents represented 66% of measured web traffic in July, with direct machine routes becoming more common, and separately analyzes MCP assistant responses and tool calls. ### Source excerpt Agents now account for 66% of measured web-traffic across docs powered by Mintlify, with July logging over 213 million agent web requests and 105 million human page loads as the month comes to a close. ## Proper logging in PHP with PSR-3 DevFeed: [Proper logging in PHP with PSR-3]() Original publisher: [Read original article]() Published: 2026-07-28T00:00:00Z Content type: article Language: en Sources: [Marco Pivetta]() Topics: [PHP](), [Logging](), [Exception](), [log management](), [Monitoring]() Tags: [article](), [code](), [errors](), [exception](), [how-to](), [logging](), [monitoring](), [php]() ### AI overview This article explains practical PHP logging with PSR-3. It focuses on passing exceptions through the logger context, allowing the logger to render exception details, defining exception types for business-specific failures, and logging enough information to understand software behavior in production. It also warns that logging and exceptions can impose CPU, memory, and I/O overhead. ### Source excerpt Who is this article for? This post is for people that do day-by-day busywork coding, and for team leads that want to direct their peers towards better logging practices. Note that this article comes from my regular need to present these exact points to different people, multiple times a year, in multiple teams, in multiple companies. Also, we will not talk about how to configure a PSR-3 logger, but rather how to use one. Handling errors properly Error/exception handling is the main use-case for logging. When logging exceptions, please pass the Throwable instance to the 'exception' context key. try { // logic here } catch (SomeException $failed) { $this->logger->error('Something went wrong', [ 'exception' => $failed, ]); } Avoid cluttering the logger call with data deriving from the exception: it's not the logger call-site's job, and you are just repeating work. I often see unnecessary code like: try { // logic here } catch (SomeException $failed) { $this->logger->error('Something went wrong', [ // first mistake: we forgot 'exception' 'previous' => $failed->getPrevious(), // let the logger do this! 'line' => $failed->getLine(), // already part of the stack trace 'error' => $failed->getMessage(), // also always rendered 'error_type' => $failed::class, // done by the logger, usually ]); } The logger itself must instead be configured (and usually already is configured) to render: the exception ::class the exception message and code (codes are not really relevant any more, in this century) the stack trace previous exceptions additional exception fields Your responsibility is to instead pass context information that the logger can't infer on its own. What if my code fails gracefully, and does not raise an exception? if (is_wrong($something)) { $this->logger->warn('Something went wrong', ['something' => $something]); } For business-specific failures that deserve a type, we can upcast them to a Throwable anyway: if (is_wrong($something)) { $this->logger->warn('Something wen ## How to structure a log DevFeed: [How to structure a log]() Original publisher: [Read original article]() Author: Kyle Tryon Published: 2026-07-21T09:00:00Z Content type: tutorial Language: en Sources: [Sentry Blog]() Topics: [Logging](), [Structured-data](), [TypeScript](), [ESLint](), [SIEM, Security, Observability]() Tags: [code](), [guide](), [lint](), [logs](), [programming](), [schema]() ### AI overview A practical guide to writing structured logs that are consistent, queryable, and useful for debugging in production. It covers event naming, flattened attributes, predictable low-cardinality values, severity levels, primitive-value constraints, and enforcing conventions with an ESLint plugin for TypeScript. ### Source excerpt A practical guide to writing structured, queryable, lint-enforceable logs with consistent event names, attributes, severity, and schema checks. ## Creating an environmental logger - Part 1 DevFeed: [Creating an environmental logger - Part 1]() Original publisher: [Read original article]() Author: John Lee Published: 2026-07-15T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [ESP32](), [ESP-IDF](), [Logging](), [Terminal](), [Internet of things](), [data](), [Library]() Tags: [article](), [blog](), [esp-idf](), [esp32](), [filesystem](), [how-to](), [i2c](), [iot](), [logging](), [sensor](), [vs-code]() ### AI overview This tutorial explains how to build an environmental logger with an ESP32-C61-Devkit-C, a DHT20 temperature and humidity sensor, and ESP-IDF. Part 1 covers reading the sensor over I2C and storing measurements in a little_fs filesystem on the module's flash memory. ### Source excerpt This article shows how to create a simple environmental logger using the DHT20 sensor and store the data on a little_fs filesystem on the module's flash memory. ## Logging Best Practices for Debugging Applications DevFeed: [Logging Best Practices for Debugging Applications]() Original publisher: [Read original article]() Author: Ben Coe Published: 2026-07-09T09:00:00Z Content type: tutorial Language: en Sources: [Sentry Blog]() Topics: [Logging](), [debugging](), [observability](), [audit](), [Instrumentation]() Tags: [audit](), [best-practices](), [debugging](), [how-to](), [instrumentation](), [learn](), [logging](), [observability](), [sentry]() ### AI overview This article presents practical logging best practices for applications. It recommends adding targeted log lines, using temporary instrumentation during investigations, recording runtime decisions and intermediate outcomes, and auditing access and mutating operations to make production software easier to debug and understand. ### Source excerpt Learn logging best practices: what to log, how to structure messages, and what to avoid. Practical tips with Sentry's structured logging. ## Automating Identity and Access for FedRAMP 20x KSIs with Teleport DevFeed: [Automating Identity and Access for FedRAMP 20x KSIs with Teleport]() Original publisher: [Read original article]() Author: info@goteleport.com (Nicolas Morris) Published: 2026-06-17T00:00:00Z Content type: tutorial Language: en Sources: [Teleport]() Topics: [audit trail](), [identity and access management](), [Logging](), [Monitoring](), [Security](), [CI/CD](), [Cloud]() Tags: [audit-trail](), [ci-cd](), [credentials](), [fedramp](), [fedramp-20x](), [hardcoded-credentials](), [identity-and-access-management](), [logging](), [monitoring](), [security]() ### AI overview This article explains how FedRAMP 20x changes identity and access compliance toward persistent validation using machine-readable evidence. It describes how unified identity management and audit trails can help address gaps in machine-to-machine authentication and continuous KSI validation. ### Source excerpt Learn how to automate identity and access for FedRAMP 20x KSIs with a unified audit trail for identities, access, and persistent evidence. ## Why You Should Tune Code Before Your Garbage Collector DevFeed: [Why You Should Tune Code Before Your Garbage Collector]() Original publisher: [Read original article]() Author: Peter Lawrey (noreply@blogger.com) Published: 2026-06-08T11:52:44Z Content type: article Language: en Sources: [Vanilla Java]() Topics: [Benchmark](), [Java](), [Latency](), [Logging](), [Code]() Tags: [benchmark](), [benchmarks](), [io](), [java](), [latency](), [logging](), [low-latency](), [performance]() ### AI overview A Java latency benchmark compares garbage collectors while varying redundant SLF4J logging and log storage. The article reports that removing redundant logging can have a much larger effect on extreme tail latency than changing the garbage collector, and can change which collector performs best. ### Source excerpt Optimising your memory allocations in Java could make far more difference than your choice of Garbage Collector and may even change which is the best garbage collector. In this post I look at a simple event to response latency benchmark, MarketDataSnapshot to NewOrderSingle at 50K/s for 30 minutes using JLBH to test Chronicle-FIX. The goal is to compare a system which is doing redundant work (in this case logging each message using SLF4J), compared with not logging (Chronicle-FIX records every message internally using Chronicle Queue) and how this changes the choice of Garbage Collector For the p99 (worst 1 in 100) the choice of Garbage Collector makes a different on par with optimising how loggin is done However, for the p99.99 (worst 1 in 10,000) optimsing how the logging is done is orders of magnitude more signifciant than the choice of Garbage Collector Unoptimised Benchmark This takes the optimised benchmark and adds one SLF4J log line of just the message to be sent. One log line might not sound like much but ding this on every message makes a big difference esp when the rest of the code is written for low latency. Table 1. RTT latency distribution with slf4j logging GC option p99 p99.99 Parallel large Eden, no large pages 16.86 20,480 ZGC, no large pages 12.21 19,694 G1 + COH, no large pages 12.02 20,349 G1, 2 MiB large pages 13.94 20,021 Shenandoah generational, no large pages 12.30 19,235 Note The p99.99 are thousands of microseconds or 19 to 20 milliseconds. The p99.99 or worst 1 in 10,000 might sound rare, however at 50K/s that is 5 times per second or 300 times per minute Based on these results, you might conclude that Shenandoah is a good option, and avoid Parallel GC. How much difference is the disk IO making IO is often a significant proportion of delays, and we can see that just moving where the logs are written. In this case to a tmpfs filesystem. Table 2. RTT latency distribution with slf4j logging to /dev/shm GC option p99 p99.99 Parallel large Ede ## Errors, traces, logs, metrics: when to reach for what DevFeed: [Errors, traces, logs, metrics: when to reach for what]() Original publisher: [Read original article]() Author: Sergiy Dybskiy Published: 2026-06-05T09:00:00Z Content type: tutorial Language: en Sources: [Sentry Blog]() Topics: [SIEM, Security, Observability](), [telemetry](), [tracing](), [Logging](), [debugging]() Tags: [debugging](), [errors](), [logs](), [metrics](), [sentry](), [telemetry](), [traces]() ### AI overview This developer guide explains when to use errors, traces, logs, and metrics during application instrumentation and debugging. It distinguishes the question each telemetry signal answers and describes how the signals support different workflows. ### Source excerpt Errors, traces, logs, and metrics overlap enough that it's hard to know which to use. Here's when to reach for each signal, with a real debugging walkthrough. ## Audit trails are a feature, not a compliance tax DevFeed: [Audit trails are a feature, not a compliance tax]() Original publisher: [Read original article]() Author: Mohit Bansal Published: 2026-06-04T00:00:00Z Content type: article Language: en Sources: [Webflow Blog]() Topics: [Logging](), [log management](), [SIEM, Security](), [Security]() Tags: [compliance](), [critical-infrastructure](), [logging](), [logs](), [nis2](), [security](), [siem](), [soc-2]() ### AI overview The article argues that audit logging has evolved from an overlooked compliance requirement into a product capability. Queryable, timestamped logs can support sales, vendor evaluations, accountability for AI agents, and more complete breach reconstruction. ### Source excerpt Logging used to satisfy auditors. Now it closes deals, holds AI agents accountable, and decides whether you can reconstruct a breach. ## Multi-Site Data Center Audit and Compliance Best Practices DevFeed: [Multi-Site Data Center Audit and Compliance Best Practices]() Original publisher: [Read original article]() Author: info@goteleport.com (Mayur Pipaliya) Published: 2026-05-11T00:00:00Z Content type: article Language: en Sources: [Teleport]() Topics: [datacenter](), [audit](), [Logging](), [Cybersecurity](), [soc 2](), [ssh](), [Kubernetes]() Tags: [audit](), [compliance](), [cybersecurity](), [data-center](), [data-centers](), [kubernetes](), [logging](), [logs](), [soc](), [ssh]() ### AI overview This article outlines audit and compliance challenges in multi-site data center environments, including fragmented logs, shared credentials, and weak identity attribution. It presents best practices for consistent audit visibility across sites. ### Source excerpt Discover seven best practices for unified audit visibility and compliance across multi-site data centers. ## How Backend Engineering Has Changed in 2026 DevFeed: [How Backend Engineering Has Changed in 2026]() Original publisher: [Read original article]() Author: Eric Roby Published: 2026-05-05T15:12:51Z Content type: opinion Language: en Sources: [Eric Roby]() Topics: [Back end](), [Artificial Intelligence](), [agentic-coding](), [CI/CD](), [Infrastructure as code](), [Docker](), [Terraform](), [Logging](), [observability]() Tags: [agentic-coding](), [ai](), [backend](), [ci-cd](), [docker](), [engineering](), [infrastructure-as-code](), [logging](), [observability]() ### AI overview An opinion article argues that backend engineering has changed as AI-assisted coding raises delivery expectations and broadens the responsibilities expected of backend developers. It says engineers must still make architecture, business-logic, and system-design decisions while also handling areas such as CI/CD, infrastructure as code, cloud environments, observability, logging, and analytics. ### Source excerpt Five reasons the job changed, and what to actually do about it ## EU AI Act Compliance: Requirements, Risks, and What to Document DevFeed: [EU AI Act Compliance: Requirements, Risks, and What to Document]() Original publisher: [Read original article]() Author: info@goteleport.com (Kayne McGladrey, CISSP) Published: 2026-04-15T00:00:00Z Content type: tutorial Language: en Sources: [Teleport]() Topics: [Artificial Intelligence](), [Requirements](), [Documentation](), [audit](), [data-governance](), [Logging](), [Monitoring](), [Deployment](), [data]() Tags: [ai](), [compliance](), [cybersecurity](), [data](), [data-governance](), [dataset](), [deployment](), [development](), [documentation](), [eu](), [iso-27001](), [lifecycle](), [logging](), [monitoring](), [nist](), [real-time](), [reproducibility](), [soc-2](), [versioning]() ### AI overview A practical guide to EU AI Act compliance covering requirements, risks, technical documentation, logging, data governance, lifecycle evidence, traceability, monitoring, and human oversight. It outlines key compliance milestones from August 2025 through August 2027. ### Source excerpt Cut through EU AI Act complexity with practical guidance on requirements, risks, and documentation. ## ESPHome 2026.4.0: Faster ESP32 defaults and signed OTA DevFeed: [ESPHome 2026.4.0: Faster ESP32 defaults and signed OTA]() Original publisher: [Read original article]() Author: Jesse Hills Published: 2026-04-15T00:00:00Z Content type: release Language: en Sources: [ESPHome - Smart Home Made Simple - Blog]() Topics: [ESP32](), [ESP8266](), [Logging](), [benchmarking](), [ESP-IDF](), [Lvgl]() Tags: [2026](), [benchmarking](), [cpu](), [esp-idf](), [esp32](), [esp8266](), [logging](), [lvgl](), [ota](), [release](), [releases](), [security](), [yaml]() ### AI overview ESPHome 2026.4.0 increases ESP32 CPU frequency by default, adds signed OTA verification and custom partition tables, and improves performance across logging, configuration loading, Bluetooth proxying, Ethernet, and GPIO expanders. The release also adds an ESP8266 crash handler, LVGL 9.5.0, new components, and migration requirements for deprecated features. ### Source excerpt ESPHome 2026.4.0 raises ESP32 CPU frequency by default, adds signed OTA and an ESP8266 crash handler, and speeds up state logging and config loading. [Next page]()