# Troubleshooting Published articles for Troubleshooting. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Native Splunk brings real-time insights to Cisco Nexus One DevFeed: [Native Splunk brings real-time insights to Cisco Nexus One]() Original publisher: [Read original article]() Author: David Keith Published: 2026-09-16T15:00:59Z Content type: release Language: en Sources: [Cisco Blogs]() Topics: [Nexus Dashboard](), [observability](), [telemetry](), [datacenter](), [Security](), [sensitive data](), [audit](), [configuration]() Tags: [analytics](), [audit](), [cisco](), [cisco-nexus-dashboard](), [configuration](), [data-center](), [data-center-networking](), [network](), [nexus-one](), [observability](), [real-time](), [sensitive-data](), [splunk](), [troubleshooting]() ### AI overview Cisco describes native Splunk embedded in Cisco Nexus Dashboard as an on-premises analytics and observability capability for data center and AI workloads. It processes telemetry locally, correlates network, security, configuration, and audit data, and provides dashboards, searches, and alerts for troubleshooting, data sovereignty, compliance, and cost efficiency. ### Source excerpt Discover how native Splunk embedded in Cisco Nexus Dashboard delivers real-time analytics, faster troubleshooting, and on-premises data sovereignty for modern data center and AI workloads. ## Troubleshooting row lock contention in Amazon Aurora PostgreSQL: Part 1 - Understanding row lock contention in PostgreSQL DevFeed: [Troubleshooting row lock contention in Amazon Aurora PostgreSQL: Part 1 - Understanding row lock contention in PostgreSQL]() Original publisher: [Read original article]() Author: Sameer Kumar Published: 2026-09-14T16:02:08Z Content type: tutorial Language: en Sources: [AWS Database Blog]() Topics: [Amazon Aurora](), [PostgreSQL](), [Concurrency](), [Monitoring](), [Transactions](), [Amazon CloudWatch](), [Amazon RDS](), [Architecture & Design](), [Extension]() Tags: [advanced-300](), [amazon-aurora](), [amazon-cloudwatch](), [amazon-rds](), [architecture](), [availability](), [concurrency](), [database](), [database-performance](), [extension](), [locks](), [monitoring](), [postgresql](), [production](), [rds-for-postgresql](), [technical-how-to](), [transactions](), [troubleshooting]() ### AI overview This first part of a two-part series explains row lock contention in PostgreSQL and Amazon Aurora PostgreSQL. It covers how concurrent transactions competing for the same rows can reduce throughput and cause timeouts despite healthy CPU and I/O, then introduces PostgreSQL locking internals and monitoring techniques using system views, functions, the pgrowlocks extension, and log_lock_waits. The article notes that the same behavior and investigation approach apply to Amazon RDS for PostgreSQL. ### Source excerpt Row lock contention can collapse database throughput during a flash sale even when CPU and I/O look healthy. In Part 1 of this series, learn how PostgreSQL row locking works and how to monitor lock contention in Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL using system views, the pgrowlocks extension, and the log_lock_waits parameter. ## A visual guide to troubleshooting search performance using Query Insights dashboards DevFeed: [A visual guide to troubleshooting search performance using Query Insights dashboards]() Original publisher: [Read original article]() Author: Chenyang Ji Published: 2026-09-04T20:11:52Z Content type: tutorial Language: en Sources: [OpenSearch]() Topics: [Amazon OpenSearch Service](), [dashboards](), [Monitoring](), [Latency](), [cpu]() Tags: [blog](), [configuration](), [cpu](), [dashboards](), [distribution](), [how-to](), [index](), [latency](), [memory](), [monitoring](), [navigation](), [opensearch](), [performance](), [real-time](), [technical](), [troubleshooting](), [view](), [visualization]() ### AI overview A visual guide to using OpenSearch Query Insights dashboards to investigate slow searches and unexpected resource usage. It covers the Live Queries and Top N Queries views, interactive visualizations, configuration, and metrics such as latency, CPU, and memory. ### Source excerpt OpenSearch Query Insights dashboards provide interactive visualizations for monitoring live queries, analyzing top N query performance, and viewing individual query details. This post explores each visualization and shows how to use visualizations to troubleshoot search performance issues. The post A visual guide to troubleshooting search performance using Query Insights dashboards appeared first on OpenSearch. ## Announcing General Availability of VMware Cloud Foundation 9.1.1 DevFeed: [Announcing General Availability of VMware Cloud Foundation 9.1.1]() Original publisher: [Read original article]() Author: vmwareblogs Published: 2026-09-03T13:47:18Z Content type: release Language: en Sources: [VMware Blogs]() Topics: [Cloud](), [Security](), [AI Platform](), [AI Models](), [MLOps]() Tags: [ai](), [ai-ml](), [ai-models](), [announce](), [apis](), [cloud](), [cloud-infrastructure](), [complexity](), [cost](), [cpu](), [data-privacy](), [evpn](), [governance](), [home-page](), [integrations](), [kubernetes](), [memory](), [nsx](), [private-ai-services](), [release](), [root-cause-analysis](), [security](), [troubleshooting](), [vcf-9-1](), [vcf-operations](), [vmware](), [vmware-cloud-foundation]() ### AI overview VMware announces the general availability of VMware Cloud Foundation 9.1.1. The release adds tougher security, vSAN Object Storage as a tech preview, multi-tenant AI model sharing with tenant-isolated access controls, and an AI Assistant for diagnostics, management-pack creation, and troubleshooting across infrastructure and Kubernetes clusters. ### Source excerpt Coming on the heels of a very successful VMware Explore in Vegas and the VMware Cloud Foundation (VCF) 9.1 launch in May, we're excited to announce the general availability of VCF 9.1.1. This release builds on VCF 9.1 with tougher security, vSAN Object Storage (tech preview, previously announced) and new capabilities designed to make your ... Continued The post Announcing General Availability of VMware Cloud Foundation 9.1.1 appeared first on VMware Blogs. ## 【kube-apiserver】排障五轴：Storage、Watch、Admission、Auth、APF DevFeed: [【kube-apiserver】排障五轴：Storage、Watch、Admission、Auth、APF]() Original publisher: [Read original article]() Author: Liao Tonglang Published: 2026-08-28T00:00:00Z Content type: tutorial Language: zh Sources: [土法炼钢 - 系统与基础设施]() Topics: [Kubernetes](), [API](), [etcd]() Tags: [admission](), [apf](), [apiserver](), [auth](), [authz](), [distributed](), [etcd](), [five-axes](), [kubernetes](), [metrics](), [storage](), [troubleshooting](), [v1-30-3](), [watch]() ### AI overview A troubleshooting guide for kube-apiserver organized around five diagnostic axes: Storage, Watch, Admission, Auth, and API Priority and Fairness. It maps symptoms such as 504, 410 Gone, 401, 403, webhook timeouts, list storms, and OOM to likely axes, explains when to investigate etcd, and emphasizes that commands and metrics were not executed in the author's environment. ### Source excerpt 按 Storage/Watch/Admission/Auth/APF 五轴做症状否证；给出完整五轴命令表与症状->轴映射（504、410、401、403、webhook 超时、List 风暴、OOM）；说明 apiserver_request_duration_seconds 等核心 metrics 语义；并提供决策树：何时穿透到 etcd/15，何时留在 apiserver 轴。 ## 【etcd】排障五轴：Raft/WAL/MVCC/Watch/Lease 口令表 DevFeed: [【etcd】排障五轴：Raft/WAL/MVCC/Watch/Lease 口令表]() Original publisher: [Read original article]() Author: Liao Tonglang Published: 2026-08-26T00:00:00Z Content type: tutorial Language: zh Sources: [土法炼钢 - 系统与基础设施]() Topics: [etcd](), [Kubernetes]() Tags: [apiserver](), [applied-index](), [apply](), [committed-index](), [compaction](), [distributed](), [errcompacted](), [etcd](), [five-axes](), [incident](), [keepalive](), [kubernetes](), [lag](), [lease](), [mvcc](), [node-lease](), [raft](), [restore](), [troubleshooting](), [ttl](), [v3](), [v3-5](), [v3-5-33](), [wal](), [watch]() ### AI overview This troubleshooting article organizes etcd failures into five diagnostic axes: Raft consensus, WAL persistence and recovery, MVCC storage and capacity, Watch client synchronization, and Lease TTL semantics. It maps symptoms to axes, explains relevant etcdctl health and status fields, and notes Kubernetes control-plane relationships, including apiserver and Node Lease behavior. The article is anchored to etcd v3.5.33. ### Source excerpt 按 Raft、WAL、MVCC、Watch、Lease 五轴做症状否证；解释 etcdctl endpoint status/health 字段语义；并对照 K8s 控制面 apiserver 超时与 Node Lease 漂移。 ## Troubleshooting Tarana Wireless Customer Connections DevFeed: [Troubleshooting Tarana Wireless Customer Connections]() Original publisher: [Read original article]() Author: j2sw Published: 2026-08-04T18:18:31Z Content type: tutorial Language: en Sources: [Justin Wilson (j2sw)]() Topics: [Network]() Tags: [access-point](), [isp](), [latency](), [network-operations](), [network-troubleshooting](), [rf](), [rf-troubleshooting](), [signal](), [tarana](), [transmission](), [troubleshooting](), [wireless](), [wireless-networking](), [wisp]() ### AI overview This troubleshooting guide explains why a single metric cannot establish the health of a Tarana wireless customer connection. It recommends evaluating RSSI, SNR, modulation rate, retransmissions, latency, sector utilization, and trends together to identify signal limitations, interference, changing RF conditions, and their effects on throughput. ### Source excerpt Troubleshooting Tarana wireless customer connections means looking at RSSI, SNR, modulation, retransmissions, latency, sector utilization, and trends together. The post Troubleshooting Tarana Wireless Customer Connections appeared first on Justin Wilson (j2sw). ## netcat (nc) Command in Linux, with Examples DevFeed: [netcat (nc) Command in Linux, with Examples]() Original publisher: [Read original article]() Author: Hayden James Published: 2026-08-01T10:42:27Z Content type: tutorial Language: en Sources: [Hayden James]() Topics: [networking](), [Linux](), [Tool]() Tags: [blog](), [commands](), [connectivity](), [debugging](), [examples](), [guide](), [linux](), [networking](), [port](), [security](), [server](), [sysadmins](), [tcp](), [tool](), [troubleshooting](), [udp]() ### AI overview A practical guide to the Linux nc (netcat) command, covering port testing, file transfers, banner grabbing, reverse shells, proxies, and network-service debugging over TCP and UDP. It also explains implementation differences across OpenBSD netcat, Ncat, BusyBox, and traditional netcat. ### Source excerpt The nc command (netcat) is a lightweight but surprisingly powerful networking tool for port testing, file transfers, banner grabbing, and connectivity debugging. This practical guide covers the flags and real-world usage patterns that Linux users and sysadmins actually reach for. Continue reading... ## How DNS Works for DevOps Engineers DevFeed: [How DNS Works for DevOps Engineers]() Original publisher: [Read original article]() Author: Pramodh Kumar M Published: 2026-07-31T17:00:06Z Content type: tutorial Language: en Sources: [Kubernetes - KodeKloud Blog | DevOps, Cloud, Kubernetes, AI Tutorials & More]() Topics: [DevOps](), [Internet](), [Kubernetes](), [Security]() Tags: [1-1-1-1](), [authoritative-name-server](), [cloudflare](), [cname-vs-a-record](), [coredns-kubernetes](), [devops](), [dig-command-examples](), [dns](), [dns-for-devops-engineers](), [dns-record-types](), [dns-resolution-process](), [dns-troubleshooting](), [guide](), [health-checks](), [how-dns-works](), [infrastructure](), [kubernetes](), [linux](), [lookup](), [networking](), [outage](), [production](), [recursive-resolver](), [security](), [troubleshooting](), [ttl-in-dns](), [web]() ### AI overview A practical guide to DNS for DevOps engineers, tracing a lookup from a laptop through recursive, root, TLD, and authoritative servers. It explains TTL, caching, Kubernetes DNS and ndots, troubleshooting with command-line tools, and the security risk of dangling records. ### Source excerpt Almost every engineer uses DNS a hundred times a day and has never been taught how it works. This guide follows a single lookup from your laptop to the answer, then shows you exactly where it breaks in production. ## How to Build a Kubernetes Troubleshooting AI Agent with LangChain and kubectl DevFeed: [How to Build a Kubernetes Troubleshooting AI Agent with LangChain and kubectl]() Original publisher: [Read original article]() Author: Pramodh Kumar M Published: 2026-07-27T17:26:08Z Content type: tutorial Language: en Sources: [Kubernetes - KodeKloud Blog | DevOps, Cloud, Kubernetes, AI Tutorials & More]() Topics: [AI Agent](), [Kubernetes](), [kubectl](), [LangChain](), [Tutorial]() Tags: [ai](), [ai-agent](), [ai-agent-for-kubernetes](), [ai-agents](), [aiops-for-kubernetes](), [automation](), [configuration](), [crashloopbackoff-troubleshooting](), [devops](), [human-in-the-loop-agent](), [kubectl](), [kubectl-ai-agent](), [kubernetes](), [kubernetes-rbac-for-ai-agents](), [kubernetes-troubleshooting-ai-agent](), [kubernetes-troubleshooting-automation](), [langchain](), [langchain-kubernetes-agent](), [langgraph](), [langgraph-agent-tutorial](), [python](), [react-agent-python](), [security](), [tool](), [troubleshooting](), [tutorial]() ### AI overview A tutorial on building a Kubernetes troubleshooting AI agent with LangChain v1 and kubectl. It describes a diagnostic ladder for investigating pod failures, read-only tools, approval requirements for write operations, separate identities for remediation, and a golden trace suite for evaluating results. ### Source excerpt Most pod failures resolve into six root causes, and the investigation is identical every time. Here is how to build an agent that runs that investigation for you, with a hard boundary between reading a cluster and changing one. ## Using AI to Troubleshoot Kubernetes Clusters DevFeed: [Using AI to Troubleshoot Kubernetes Clusters]() Original publisher: [Read original article]() Author: Nimesha Jinarajadasa Published: 2026-07-18T08:34:19Z Content type: tutorial Language: en Sources: [Kubernetes - KodeKloud Blog | DevOps, Cloud, Kubernetes, AI Tutorials & More]() Topics: [Kubernetes](), [Artificial Intelligence]() Tags: [ai](), [clusters](), [errors](), [guide](), [how-to](), [kubernetes](), [recovery](), [troubleshooting](), [verify]() ### AI overview A practical tutorial on using k8sgpt to troubleshoot deliberately broken Kubernetes clusters. It covers diagnosing ImagePullBackOff and CrashLoopBackOff errors, generating AI-assisted explanations and fix steps, applying a suggested fix, and verifying recovery while a human remains responsible for the decision. ### Source excerpt Use AI to troubleshoot Kubernetes with k8sgpt: diagnose real ImagePullBackOff and CrashLoopBackOff errors, get fix steps, and verify recovery. ## How to Troubleshoot and Debug Ansible Playbooks DevFeed: [How to Troubleshoot and Debug Ansible Playbooks]() Original publisher: [Read original article]() Author: Mrinalini Sugosh Published: 2026-07-15T00:00:00Z Content type: tutorial Language: en Sources: [Harness Blog]() Topics: [Ansible](), [debugging](), [Infrastructure as code](), [YAML]() Tags: [ansible](), [debugging](), [how-to](), [iac](), [infrastructure-as-code](), [troubleshooting](), [yaml]() ### AI overview This tutorial explains how to troubleshoot and debug Ansible playbooks. It covers structured and conditional debugging, verbosity controls, targeted variable inspection, reusable debugging roles, failure taxonomies, and CI/CD-friendly logging. It also describes common problems such as syntax errors, variable conflicts, connection errors, and inconsistent execution across hosts. ### Source excerpt Master how to debug Ansible with expert tips for troubleshooting playbooks. Learn structured debugging, reduce errors, and streamline Infrastructure Deployments | Blog ## A 15-Second Health Check for Your Heroku Connect Data Pipeline DevFeed: [A 15-Second Health Check for Your Heroku Connect Data Pipeline]() Original publisher: [Read original article]() Author: Nick Prey Published: 2026-06-24T15:35:14Z Content type: tutorial Language: en Sources: [Heroku]() Topics: [Heroku](), [Command-line interface](), [Data Management](), [SQL](), [Databases]() Tags: [cli](), [data-pipeline](), [engineering](), [heroku](), [heroku-connect](), [migrations](), [salesforce](), [schema](), [synchronization](), [troubleshooting]() ### AI overview This tutorial explains how the Heroku Connect CLI plugin's diagnostic command checks connection health, schema alignment, and field configurations in a Salesforce-to-Heroku Postgres data pipeline. It highlights how the command can expose configuration mismatches and provide actionable warnings before schema updates or migrations. ### Source excerpt Heroku Connect is a fully managed, bidirectional data sync service between Salesforce and Heroku Postgres that lets developers read and write Salesforce data using standard SQL. The sync is straightforward to set up and operates smoothly in the background, but when a field does not update as expected or data seems to lag, you do not need to guess what went wrong. The post A 15-Second Health Check for Your Heroku Connect Data Pipeline appeared first on Heroku. ## Linux Troubleshooting: A Four-Step Systematic Approach DevFeed: [Linux Troubleshooting: A Four-Step Systematic Approach]() Original publisher: [Read original article]() Author: Hayden James Published: 2026-06-11T07:11:37Z Content type: tutorial Language: en Sources: [Hayden James]() Topics: [Linux](), [systems]() Tags: [blog](), [commands](), [desktop](), [errors](), [guide](), [how-to](), [linux](), [server](), [sysadmins](), [troubleshooting]() ### AI overview A tutorial presents a systematic four-step process for troubleshooting Linux problems on servers and desktop systems. The visible guidance emphasizes identifying the precise symptom, recording relevant context, and investigating or reproducing the issue when possible. ### Source excerpt I'll admit, I hesitated a bit before writing this post. The whole point of this linuxblog.io and linuxcommunity.io forum is to bring together like-minded Linux users and professionals so we can troubleshoot, share ideas, and learn from one another. Continue reading... ## OpenAI Uses Isovalent for a Common Networking for AI Infrastructure DevFeed: [OpenAI Uses Isovalent for a Common Networking for AI Infrastructure]() Original publisher: [Read original article]() Author: Dean Lewis Published: 2026-06-03T10:42:00Z Content type: article Language: en Sources: [Isovalent - The latest articles covering eBPF-based Networking, Observability, and Security]() Topics: [Cilium](), [OpenAI](), [AI Infrastructure](), [Kubernetes](), [networking]() Tags: [ai](), [ai-infrastructure](), [cilium](), [ebpf](), [hubble](), [infrastructure](), [isovalent](), [kubernetes](), [kubernetes-networking](), [load-balancer](), [mesh-networking](), [networking](), [openai](), [policy](), [runtime-security](), [tetragon](), [troubleshooting](), [uses](), [website]() ### AI overview The article reports that OpenAI uses Isovalent Networking for Kubernetes, built on Cilium, to provide consistent networking, policy, and troubleshooting across its AI infrastructure. ### Source excerpt OpenAI uses Isovalent Networking for Kubernetes, built on Cilium, for consistent networking, policy, and troubleshooting across AI infrastructure. ## The Hidden Cost of Complex AI Platforms: Why Developer Experience Matters DevFeed: [The Hidden Cost of Complex AI Platforms: Why Developer Experience Matters]() Original publisher: [Read original article]() Author: Shaoni Mukherjee Published: 2026-04-03T15:44:39Z Content type: article Language: en Sources: [DigitalOcean]() Topics: [AI Platform](), [Developer experience](), [Cloud](), [Inference](), [Deployment]() Tags: [ai](), [ai-ml](), [ai-platform](), [cloud](), [deployment](), [developer-experience](), [engineering](), [inference](), [pipelines](), [scalability](), [troubleshooting]() ### AI overview The article argues that complex AI platforms impose hidden costs through setup friction, unclear documentation, credential configuration, dependency installation, troubleshooting, and fragmented workflows. These issues increase the time required to achieve a working result and can slow team iteration and complicate scaling. ### Source excerpt The cloud AI platform ecosystem today looks more powerful than ever, with access to powerful GPUs like NVIDIA H100 and H200, massive libraries of pre-trained models, and full pipelines for fine-tuning and inference. I recently tried deploying a simple inference endpoint for a model. Ideally, it should have taken a few minutes: provision compute load the model send a request Instead, it took closer to two hours before I got a successful response. Not because the model was difficult to run, but because of everything around it: Figuring out where to start No clear documentation Generating and configuring the right credentials Troubleshooting why the instance wasn't accessible Installing dependencies that weren't preconfigured Retrying after unclear or failed setup steps None of these steps was particularly complex on its own. But together, they created enough friction to delay even a basic task. This pattern shows up often when working with AI platforms today. Most discussions focus on visible costs like: Compute pricing Storage usage API costs But in practice, the higher cost is harder to measure. It's the time spent navigating setup, resolving infrastructure issues, and figuring out how different parts of a platform fit together before any real work begins. Key Takeaways Developer experience is a real cost, not a soft metric: Time lost in setup, debugging, and switching tools directly slows down how fast teams can build and iterate. Most friction comes from fragmented workflows: When model hosting, compute, and deployment live in different places, even simple tasks become multi-step processes. Time-to-First-Value (TTFV) is a critical signal: The longer it takes to get a working output, the more likely teams are to lose momentum or abandon ideas early. Scaling introduces a hidden breaking point: Moving from a simple API to dedicated infrastructure often forces teams to relearn workflows and rebuild systems. This is a systems problem, not a feature gap: Many platform ## Apple Magic Trackpad on Linux: How I Made It Work on Ubuntu XFCE DevFeed: [Apple Magic Trackpad on Linux: How I Made It Work on Ubuntu XFCE]() Original publisher: [Read original article]() Author: Ivan Morgillo Published: 2026-01-17T10:53:57Z Content type: tutorial Language: en Sources: [Ivan Morgillo]() Topics: [Linux](), [Ubuntu](), [xfce](), [Bluetooth](), [configuration]() Tags: [apple](), [apple-magic-trackpad](), [bluez](), [ergonomics](), [guide](), [kernel](), [libinput](), [linux](), [macos](), [troubleshooting](), [ubuntu](), [xfce]() ### AI overview A practical guide to using Apple's Magic Trackpad as the main pointing device on Ubuntu XFCE. It covers BlueZ configuration, libinput tuning, persistent settings, scrolling and right-click behavior, battery monitoring, and troubleshooting, including a kernel 6.17 battery regression. ### Source excerpt Get the Apple Magic Trackpad working on Linux: a guide for Ubuntu XFCE with BlueZ fixes, libinput tuning, autostart, battery indicator, and troubleshooting. ## DAST without disruption: Burp Suite DAST winter update 2025 DevFeed: [DAST without disruption: Burp Suite DAST winter update 2025]() Original publisher: [Read original article]() Author: Rob Samuels Published: 2025-12-11T13:09:30Z Content type: release Language: en Sources: [PortSwigger Blog]() Topics: [Application Security](), [Security](), [CI/CD](), [Authentication](), [Deployment](), [API](), [OpenAPI Specification](), [Postman](), [JavaScript](), [CSS](), [selectors](), [Single-page application (SPA)]() Tags: [2025](), [authentication](), [automation](), [ci-cd](), [deployment](), [environment-variables](), [javascript](), [openapi](), [real-time](), [responses](), [security](), [selectors](), [troubleshooting](), [ui](), [update]() ### AI overview A winter 2025 update to Burp Suite DAST adds scan freeze windows, improved site and folder management, editable recorded login flows, real-time authentication diagnostics, XPath and CSS session checks, and imports for Postman collections with environment variables. The changes aim to make automated application and API security scanning more reliable and easier to manage at scale. ### Source excerpt AppSec teams are under constant pressure to secure fast-moving applications without slowing anything down. But scanning windows, fragile authentication, and sprawling API estates often get in the way ## Multi-Pod EVPN Troubleshooting: Extended BGP Communities DevFeed: [Multi-Pod EVPN Troubleshooting: Extended BGP Communities]() Original publisher: [Read original article]() Published: 2025-12-02T05:47:00Z Content type: tutorial Language: en Sources: [ipSpace.net blog]() Topics: [evpn](), [BGP](), [Network]() Tags: [bgp](), [blog](), [evpn](), [netlab](), [troubleshooting]() ### AI overview This fifth post in a multi-pod EVPN series troubleshoots a fabric where Site-B did not recognize a remote VTEP. The issue was missing extended BGP communities on remote EVPN routes; enabling extended BGP community propagation for the EBGP EVPN address family on Arista EOS resolved the problem, allowing the affected devices to ping each other. ### Source excerpt Last week, we fixed the mismatched route targets in our sample multi-pod EVPN fabric. With that fixed, every PE device should see every other PE device as a remote VTEP for ingress replication purposes. We got that to work on Site-A (AS 65001), but not on Site-B (AS 65002); let's see what else is broken. Note: This is the fifth blog post in the Multi-Pod EVPN series. If you stumbled upon it, start with the design overview and troubleshooting overview posts. More importantly, familiarize yourself with the topology we'll be using; it's described in the Multi-Pod EVPN Troubleshooting: Fixing Next Hops. Ready? Let's go. Here's our network topology: Read more ... ## Multi-Pod EVPN Troubleshooting: Route Targets DevFeed: [Multi-Pod EVPN Troubleshooting: Route Targets]() Original publisher: [Read original article]() Published: 2025-11-25T05:49:00Z Content type: article Language: en Sources: [ipSpace.net blog]() Topics: [evpn](), [BGP](), [Network](), [Network design]() Tags: [bgp](), [evpn](), [netlab](), [network](), [route](), [troubleshooting]() ### AI overview This fourth post in a Multi-Pod EVPN troubleshooting series explains why LA does not recognize LB as a remote VTEP after BGP next hops are corrected. The cause is a mismatch between the route target exported by LB and the route target imported by LA. The post presents adding remote import route targets or configuring consistent import and export route targets across autonomous systems as fixes. ### Source excerpt Last week, we fixed the incorrect BGP next hops in our sample multi-pod EVPN fabric. With that fixed, every PE device should see every other PE device as a remote VTEP for ingress replication purposes. However, that's not the case; let's see why and fix it. Note: This is the fourth blog post in the Multi-Pod EVPN series. If you stumbled upon it, start with the design overview and troubleshooting overview posts. More importantly, familiarize yourself with the topology we'll be using; it's described in the Multi-Pod EVPN Troubleshooting: Fixing Next Hops. Ready? Let's go. Here's our network topology: Read more ... ## Multi-Pod EVPN Troubleshooting: Fixing Next Hops DevFeed: [Multi-Pod EVPN Troubleshooting: Fixing Next Hops]() Original publisher: [Read original article]() Published: 2025-11-18T06:27:00Z Content type: tutorial Language: en Sources: [ipSpace.net blog]() Topics: [evpn](), [BGP](), [Network](), [configuration]() Tags: [bgp](), [configuration](), [evpn](), [evpn-designs](), [netlab](), [network](), [route](), [troubleshooting]() ### AI overview This tutorial demonstrates troubleshooting a multi-pod EVPN network by checking BGP route propagation and inclusive multicast routes. It identifies an incorrect EVPN next-hop change across an EBGP session and explains how to trace the responsible configuration. ### Source excerpt Last month, I wrote about the specifics of troubleshooting multi-pod EVPN designs. Today, I'd like to start a journey through an example in which (channeling my inner CCIE preparation lab instructor) I broke as many things as I could think of. Here's the lab topology we'll use (and as usual, the corresponding netlab topology file and device configurations are on GitHub). Our network has two sites (pods), each with a spine switch, a leaf switch, and a host attached to the leaf switch. The inter-pod link is connected to the spine switches to minimize the number of devices. Read more ... ## Book Review - Troubleshooting Java DevFeed: [Book Review - Troubleshooting Java]() Original publisher: [Read original article]() Author: vladmihalcea Published: 2025-10-15T08:28:01Z Content type: opinion Language: en Sources: [Vlad Mihalcea]() Topics: [Java](), [debugging](), [Optimization](), [ide](), [Logging](), [Query (disambiguation)](), [Databases]() Tags: [book](), [book-review](), [code-analysis](), [debugger](), [debugging](), [developer](), [ide](), [java](), [logging](), [optimization](), [performance](), [performance-tuning](), [review](), [sql](), [troubleshooting]() ### AI overview A review of the second edition of Troubleshooting Java by Laurentiu Spilca. The book covers code analysis, logging, debugging, profiling, SQL query investigation, lock monitoring, and deadlock troubleshooting for Java developers. ### Source excerpt Introduction My friend, Laurentiu Spilca, has been working on the second edition of his Troubleshooting Java book, and when I was asked to review it, I was more than happy to do it since the book features a lot of topics that I'm also very interested in, such as performance tuning and query optimization. Audience This book is useful for any Java developer because it teaches you how to get the best out of your IDE debugger, as well as showing you how to profile Java applications and fix very complex issues,... Read More The post Book Review - Troubleshooting Java appeared first on Vlad Mihalcea. ## Troubleshooting Multi-Pod EVPN: Overview DevFeed: [Troubleshooting Multi-Pod EVPN: Overview]() Original publisher: [Read original article]() Published: 2025-10-09T06:27:00Z Content type: tutorial Language: en Sources: [ipSpace.net blog]() Topics: [evpn](), [VXLAN](), [BGP](), [Network]() Tags: [bgp](), [evpn](), [network](), [overview](), [troubleshooting](), [vxlan]() ### AI overview This troubleshooting guide explains how to isolate multi-pod EVPN connectivity problems by first testing IP reachability between VTEPs, including packet sizes needed for VXLAN encapsulation. It then separates underlay, firewall, EVPN route propagation, next-hop processing, and implementation or compatibility issues. ### Source excerpt An engineer reading my multi-pod EVPN article asked an interesting question: How do you handle troubleshooting when VTEPs cannot reach each other across pods? The ancient Romans already knew the rough answer: divide and conquer. In this particular case, the "divide" part starts with a simple realization: VXLAN/EVPN is just another application running on top of IP. Read more ... ## Ansible 12.0 breaks netlab Jinja2 templates; netlab 25.09-post1 pins Ansible to 11.10 or lower DevFeed: [Ansible 12.0 breaks netlab Jinja2 templates; netlab 25.09-post1 pins Ansible to 11.10 or lower]() Original publisher: [Read original article]() Published: 2025-09-14T17:25:00Z Content type: release Language: en Sources: [ipSpace.net blog]() Topics: [Ansible](), [configuration](), [Containerlab topology]() Tags: [ansible](), [configuration](), [core](), [dependency](), [installation](), [netlab](), [pypi](), [release](), [troubleshooting]() ### AI overview Ansible 12.0 requires ansible-core 2.19, whose Jinja2 templating changes broke netlab's Containerlab configuration file template. netlab 25.09-post1 checks the Ansible core version and pins installations to Ansible 11.10 or lower, with the install command available for downgrading. ### Source excerpt On September 9th, the ansible release 12.0 appeared on PyPi. It requires ansible-core release 2.19, which includes breaking changes to Jinja2 templating. netlab Jinja2 templates rely on a few Ansible Jinja2 filters; netlab thus imports and uses those filters, and it looks like those imports pulled in the breaking changes that consequently broke the netlab containerlab configuration file template (details). netlab did not check the Ansible core version (we never had a similar problem in the past), and the installation scripts did not pin the Ansible version (feel free to blame me for this one), which means that any new netlab installation created after September 9th crashed miserably on the simplest lab topologies. This is the workaround we implemented in netlab release 25.09-post1 (released earlier today): Read more ... [Next page]()