# Failover Published articles for Failover. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Architecting resilient authentication with Amazon Cognito multi-Region replication DevFeed: [Architecting resilient authentication with Amazon Cognito multi-Region replication]() Original publisher: [Read original article]() Author: Abrom Douglas Published: 2026-09-15T19:00:52Z Content type: tutorial Language: en Sources: [AWS Security Blog]() Topics: [Amazon Cognito](), [Replication](), [Authentication](), [identity and access management](), [Amazon Web Services](), [real-time](), [JSON Web Tokens]() Tags: [advanced-300](), [amazon-cognito](), [authentication](), [aws](), [failover](), [identity-and-access-management](), [real-time](), [replication](), [security-blog](), [security-identity-compliance](), [technical-how-to](), [token]() ### AI overview This AWS article explains how Amazon Cognito multi-Region replication supports resilient authentication by replicating user pools across AWS Regions, with eventual consistency, failover, and interoperable sessions and JSON web tokens. It also covers preparation, architecture decisions, and failover strategies for B2C, B2B, and M2M use cases. ### Source excerpt Your consumer identity and access management (CIAM) system is the foundation of your customer experience. It's how users sign in, access services, and engage with your applications. As your business scales across geographies, ensuring authentication is always available becomes a core architectural requirement. However, building multi-Region authentication has traditionally required complex custom replication solutions that [...] ## Gemini 3.8 Live models now available on AI Gateway DevFeed: [Gemini 3.8 Live models now available on AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-09-15T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [real-time](), [Artificial Intelligence](), [API](), [Google](), [WebSocket](), [SDKs]() Tags: [ai](), [api](), [cost](), [failover](), [gemini](), [google](), [real-time](), [realtime](), [sdk](), [websocket]() ### AI overview Vercel announces that Google's Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking models are available on AI Gateway. The models support real-time spoken interactions, audio and visual grounding, multilingual switching, background tool calls, and parallel reasoning through the AI SDK's realtime API. ### Source excerpt Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking from Google are now available on AI Gateway. Both models support real-time spoken interactions for voice assistants, conversational experiences, and applications that respond through audio. google/gemini-3.8-live supports real-time audio, visual grounding, automatic switching across 97 languages, and background tool calls while the conversation continues. google/gemini-3.8-live-extended-thinking adds multi-step reasoning that runs in parallel with speech, allowing it to acknowledge requests and narrate progress without interrupting the conversation. Use either model through the AI SDK's realtime API. Install the Gateway provider and a WebSocket client: Mint a short-lived token, open the WebSocket, and use the model adapter to serialize and parse realtime events: See the realtime quickstart for more details on realtime events and WebSocket connections. Try Gemini 3.8 Live or Gemini 3.8 Live Extended Thinking in the model playground. AI Gateway provides a unified API for calling models, tracking usage and cost, and configuring retries, failover, and performance optimizations for higher-than-provider uptime. Read more ## PayZephyr: One Payment API for Stripe, Paystack, and PayPal DevFeed: [PayZephyr: One Payment API for Stripe, Paystack, and PayPal]() Original publisher: [Read original article]() Author: Paul Redmond Published: 2026-09-11T01:46:25Z Content type: tutorial Language: en Sources: [Laravel]() Topics: [Laravel](), [API](), [stripe]() Tags: [api](), [checkout](), [failover](), [installation](), [integration](), [laravel](), [laravel-packages](), [payment](), [payments](), [production](), [protection](), [providers](), [stripe](), [subscription](), [webhooks]() ### AI overview PayZephyr is a Laravel payments package that provides one API for eight payment providers. It supports automatic failover, double-charge protection, signed webhooks, subscriptions, refunds, Composer installation, custom drivers, queue integration, and a playground. ### Source excerpt PayZephyr gives Laravel one payment API across Stripe, PayPal, Paystack, Flutterwave, and four more, with failover and double-charge protection. The post PayZephyr: One Payment API for Stripe, Paystack, and PayPal appeared first on Laravel News. Join the Laravel Newsletter to get Laravel articles like this directly in your inbox. ## Redesigning Kubernetes Workqueues and Resyncs to Reduce Thundering Herd Effects DevFeed: [Redesigning Kubernetes Workqueues and Resyncs to Reduce Thundering Herd Effects]() Original publisher: [Read original article]() Published: 2026-09-02T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [Kubernetes](), [systems](), [Concurrent Programming](), [Latency](), [Maintainers]() Tags: [architecture](), [concurrent](), [defense-in-depth](), [failover](), [goroutines](), [kubernetes](), [latency](), [maintainers](), [reconciliation](), [thundering-herd]() ### AI overview This article explains how Kubernetes controllers can experience thundering herd effects when restarts, leader failovers, or periodic resyncs cause many keys to enter an in-memory workqueue at once. It describes the queue and informer behavior behind the problem and introduces Chainguard's redesign of workqueues and resyncs to improve reconciliation under these conditions. ### Source excerpt The thundering herd is an architecture problem. See how Chainguard redesigned workqueues and resyncs to keep reconciliation running smoothly. ## Highly Available PostgreSQL on Kubernetes in 10 Minutes DevFeed: [Highly Available PostgreSQL on Kubernetes in 10 Minutes]() Original publisher: [Read original article]() Author: Hans-Jürgen Schönig Published: 2026-08-18T05:07:31Z Content type: tutorial Language: en Sources: [CYBERTEC PostgreSQL | Services & Support]() Topics: [PostgreSQL](), [Kubernetes](), [postgresql clusters](), [Database](), [Replication]() Tags: [failover](), [health-checks](), [how-to](), [kubernetes](), [operator](), [patroni](), [pg-operator](), [postgresql](), [postgresql-on-cloud](), [replication](), [tutorial](), [yaml]() ### AI overview This tutorial demonstrates how to deploy a highly available PostgreSQL cluster on Kubernetes with the CYBERTEC PG Operator. Using a 14-line YAML configuration on minikube, it shows leader election, streaming replication, health checks, automatic failover, and read-only replica behavior. It also explains how anti-affinity must be disabled for the single-node minikube setup but should remain enabled on multi-node production clusters. ### Source excerpt This is a detailed blog post about PostgreSQL in Kubernetes, using PG Operator. The post Highly Available PostgreSQL on Kubernetes in 10 Minutes appeared first on CYBERTEC PostgreSQL | Services & Support. ## Understanding Load Balancing for Beginners DevFeed: [Understanding Load Balancing for Beginners]() Original publisher: [Read original article]() Author: Pramodh Kumar M Published: 2026-08-17T17:00:34Z Content type: tutorial Language: en Sources: [Kubernetes - KodeKloud Blog | DevOps, Cloud, Kubernetes, AI Tutorials & More]() Topics: [backends](), [networking](), [Algorithms]() Tags: [backend](), [beginners](), [cloud](), [connection-draining](), [devops](), [failover](), [health-checks](), [high-availability](), [kubernetes](), [layer-4-vs-layer-7](), [least-connections](), [load-balancer](), [load-balancer-for-beginners](), [load-balancing](), [load-balancing-algorithms](), [networking](), [nginx](), [round-robin](), [session-affinity](), [sre](), [sticky-sessions](), [thundering-herd](), [traffic-management]() ### AI overview This beginner-oriented article explains load balancing as both traffic distribution and backend failure detection. It compares round robin and least-connections algorithms, distinguishes Layer 4 from Layer 7 routing, and discusses health checks, failover, draining, sticky sessions, and the risks of overly aggressive checks. ### Source excerpt Spreading traffic is the easy half of load balancing. The half that decides whether an outage lasts ten seconds or ten minutes is noticing that a backend has stopped working, and most health checks cannot. ## Introducing the CYBERTEC PG Operator DevFeed: [Introducing the CYBERTEC PG Operator]() Original publisher: [Read original article]() Author: Hans-Jürgen Schönig Published: 2026-08-12T09:05:41Z Content type: release Language: en Sources: [CYBERTEC PostgreSQL | Services & Support]() Topics: [Kubernetes](), [PostgreSQL](), [Replication](), [Open Source]() Tags: [clusters](), [failover](), [kubernetes](), [news](), [open](), [open-source](), [operator](), [pg-operator](), [postgresql](), [postgresql-on-cloud](), [replication]() ### AI overview CYBERTEC introduces an open-source Kubernetes operator for PostgreSQL. The CYBERTEC PG Operator provides PostgreSQL lifecycle management and supports Multi-site Clusters, including cross-site replication and automated failover across multiple Kubernetes locations. ### Source excerpt CYBERTEC PG Operator is an open-source Kubernetes operator for PostgreSQL, with Multi-site Clusters for cross-site replication and automated failover. The post Introducing the CYBERTEC PG Operator appeared first on CYBERTEC PostgreSQL | Services & Support. ## Multi-Region PostgreSQL Disaster Recovery and Failback with Crunchy PGO DevFeed: [Multi-Region PostgreSQL Disaster Recovery and Failback with Crunchy PGO]() Original publisher: [Read original article]() Author: Wellingtone Luvonga Published: 2026-08-11T05:00:00Z Content type: tutorial Language: en Sources: [CYBERTEC PostgreSQL | Services & Support]() Topics: [PostgreSQL](), [Disaster Recovery](), [Kubernetes](), [MinIO](), [nginx](), [TLS (Transport Layer Security)](), [Amazon S3](), [Availability]() Tags: [availability](), [backup](), [data-recovery](), [disaster-recovery](), [failover](), [high-availability](), [how-to](), [kubernetes](), [minio](), [nginx](), [postgresql](), [recovery](), [s3](), [tls](), [tutorials]() ### AI overview A tutorial on using Crunchy PostgreSQL Operator on Kubernetes to implement multi-region PostgreSQL disaster recovery and failback. It covers secure MinIO-backed WAL storage through an NGINX TLS reverse proxy, regional failover, and reversing roles without timeline conflicts or archive poisoning. ### Source excerpt This blog talks about multiregion PostgreSQL disaster recovery using Crunchy PGO. It has some detailed steps to understand better. The post Multi-Region PostgreSQL Disaster Recovery and Failback with Crunchy PGO appeared first on CYBERTEC PostgreSQL | Services & Support. ## Multipath en Linux: failover y HA con cabinas SAN DevFeed: [Multipath en Linux: failover y HA con cabinas SAN]() Original publisher: [Read original article]() Author: Antonio Pérez Published: 2026-08-01T14:00:00Z Content type: tutorial Language: es Sources: [tengoping.com]() Topics: [Linux](), [RAID](), [LVM](), [Kernel](), [Mdadm](), [Debian](), [rhel](), [Ubuntu]() Tags: [debian](), [failover](), [ha](), [kernel](), [linux](), [lvm](), [mdadm](), [raid](), [rhel](), [ubuntu](), [wwid]() ### AI overview A Spanish tutorial explains how DM-Multipath on Linux provides redundant paths to SAN storage. It distinguishes path failover from RAID-based disk protection, describes active-active load balancing, and explains how WWIDs identify the same LUN across multiple paths. ### Source excerpt Configura DM-Multipath en Linux para eliminar puntos únicos de fallo hacia la cabina SAN: instalación, multipath.conf y failover. ## Multi-Cluster v2 and Stateless Mode now in Preview DevFeed: [Multi-Cluster v2 and Stateless Mode now in Preview]() Original publisher: [Read original article]() Author: Alexander Schwartz Published: 2026-07-17T00:00:00Z Content type: release Language: en Sources: [Keycloak Blog]() Topics: [Keycloak](), [Authentication](), [Database](), [Availability](), [Replication](), [Kubernetes](), [Amazon Web Services]() Tags: [authentication](), [availability](), [clustering](), [database](), [distributed](), [failover](), [idm](), [kerberos](), [ldap](), [monitoring](), [openid-connect](), [preview](), [replication](), [saml](), [sso]() ### AI overview Keycloak 26.7 introduces Stateless Mode as a preview. It moves volatile data, including authentication sessions, action tokens, and brute-force counters, from Infinispan caches to the database, supporting multi-cluster deployments without an external Infinispan cluster. ### Source excerpt Starting with Keycloak 26.7, the stateless feature is available as a preview. It fundamentally simplifies how Keycloak handles volatile data -- authentication sessions, action tokens, and brute-force counters move from embedded or external Infinispan caches to the database. The result: Keycloak deployments that are easier to operate, more resilient, and ready for multi-cluster setups without an external Infinispan cluster. Read on to learn more, and ask questions in our upcoming live Q&A event on Jul 21! The problem with the current approach A multi-cluster setup becomes necessary when no transparent networking between two sites is available for Keycloak's embedded Infinispan to form a single cluster -- for example, when sites are in different availability zones or data centers without a shared network layer. Running Keycloak in such a multi-cluster setup today requires significant infrastructure beyond Keycloak itself. Without the stateless feature, the architecture depends on an external Infinispan cluster with cross-datacenter replication channels, dedicated monitoring to detect and handle Infinispan failover, and operational procedures for failback. It was tied to specific environments like Kubernetes and AWS, and using it in other environments would require significant work to adapt it. Even in single-cluster deployments, Infinispan clustering introduces operational overhead: rebalancing data in distributed caches when a node is lost or restarted, and transient failures in login flows if a node unexpectedly disappears. In large installations, the login failure cache can grow significantly, consuming substantial memory and causing long rebalancing times when nodes join or leave the cluster. While distributed caches replicate data across at least two nodes -- so individual node failures do not lose data -- a full cluster restart during minor upgrades resets volatile state such as in-progress authentication sessions and brute-force counters. What changes with stateles ## Essential Non Functional Requirements DevFeed: [Essential Non Functional Requirements]() Original publisher: [Read original article]() Author: Saurabh Dashora Published: 2026-07-07T08:33:34Z Content type: tutorial Language: en Sources: [System Design Codex]() Topics: [Requirements](), [Architecture & Design](), [Scalability](), [Availability](), [Latency](), [reliability](), [Replication](), [Users]() Tags: [availability](), [data-replication](), [failover](), [haproxy](), [kubernetes](), [latency](), [nginx](), [requirements]() ### AI overview This tutorial explains non-functional requirements as quality attributes that determine how software systems behave under real-world conditions. It covers availability, latency, scalability, and durability, with implementation approaches including load balancers, health checks, failover, CDNs, data replication, horizontal scaling, Kubernetes, and concurrent API design. ### Source excerpt Don't miss them ## How CockroachDB and IBM LinuxONE Rockhopper 5 Power Resilient AI Infrastructure DevFeed: [How CockroachDB and IBM LinuxONE Rockhopper 5 Power Resilient AI Infrastructure]() Original publisher: [Read original article]() Author: Kyle Basile Published: 2026-07-07T00:00:00Z Content type: article Language: en Sources: [Cockroach Labs]() Topics: [AI Infrastructure](), [NVIDIA DGX](), [CockroachDB](), [ibm](), [Databases](), [AI Development]() Tags: [ai](), [ai-infrastructure](), [availability](), [cockroachdb](), [concurrency](), [consistency](), [customers](), [data](), [digital](), [distributed](), [engineering](), [enterprise](), [failover](), [financial](), [ibm](), [identity](), [identity-and-access](), [identity-and-access-management](), [infrastructure](), [security]() ### AI overview The article explains how enterprise AI workloads increase requirements for continuous data availability, high concurrency, real-time decision-making, and elastic scaling. It presents IBM LinuxONE Rockhopper 5 and CockroachDB as infrastructure and data-platform components for resilient AI applications, including semantic retrieval, embeddings, agent memory, and transactional consistency. ### Source excerpt Why does AI require a new approach to infrastructure? ## How I Chose the Best Managed Network Switch for My Home Lab DevFeed: [How I Chose the Best Managed Network Switch for My Home Lab]() Original publisher: [Read original article]() Author: Hayden James Published: 2026-06-29T07:25:47Z Content type: opinion Language: en Sources: [Hayden James]() Topics: [Homelab](), [Network](), [Firewall](), [Ubiquiti]() Tags: [blog](), [cybersecurity](), [failover](), [firewall](), [home-lab](), [homelab](), [linux](), [load-balancing](), [network](), [sysadmins](), [ubiquiti]() ### AI overview A home-lab network upgrade motivates the author's search for a managed switch with 10G SFP+ uplinks and at least 2.5G LAN ports. The article discusses the author's existing Ubiquiti and Peplink setup, network-security goals, and future expansion plans. A later update says the author chose the TP-Link SG2210XMP-M2, which had run for a year without reported issues. ### Source excerpt Update (one year later): The verdict is in. I went with the TP-Link SG2210XMP-M2, and after a full year in the rack it's been running flawlessly: fanless, multigig, VLANs and not a single issue. Continue reading... ## How to Migrate from SQL Server to PostgreSQL HA for Dockerized Apps DevFeed: [How to Migrate from SQL Server to PostgreSQL HA for Dockerized Apps]() Original publisher: [Read original article]() Author: Jessie Baynas Published: 2026-05-28T07:18:00Z Content type: tutorial Language: en Sources: [SeveralNines]() Topics: [PostgreSQL](), [sql-server](), [migration](), [Database Migration](), [Replication](), [Docker Compose](), [Architecture & Design](), [DevOps](), [Monitoring]() Tags: [cloud-native](), [database-general](), [database-migration](), [deployment](), [devops](), [failover](), [migration](), [monitoring](), [open-source](), [postgresql](), [replication](), [sql-server](), [validation]() ### AI overview This tutorial explains how to migrate a database from Microsoft SQL Server to PostgreSQL for Dockerized applications. It separates schema migration with pgloader from bulk data export using BCP and import with PostgreSQL COPY, and describes a setup involving streaming replication and ClusterControl for deployment, monitoring, and failover. ### Source excerpt For many organizations, migrating from Microsoft SQL Server to PostgreSQL is no longer only about reducing licensing costs. The transition is often part of a broader modernization initiative focused on improving flexibility, scalability, and operational efficiency. PostgreSQL has evolved into one of the most mature open-source database platforms available today. It is widely adopted across [...] The post How to Migrate from SQL Server to PostgreSQL HA for Dockerized Apps appeared first on Severalnines. ## Building High Availability PostgreSQL Clusters with Patroni and Other Integrated Approaches DevFeed: [Building High Availability PostgreSQL Clusters with Patroni and Other Integrated Approaches]() Original publisher: [Read original article]() Author: Agus Syafaat Published: 2026-05-21T07:20:00Z Content type: tutorial Language: en Sources: [SeveralNines]() Topics: [postgresql clusters](), [PostgreSQL](), [Availability](), [Replication](), [Resilience](), [Automation](), [configuration](), [Open Source]() Tags: [automation](), [availability](), [configuration](), [consensus](), [database](), [distributed](), [failover](), [ha](), [high-availability](), [open-source](), [patroni](), [postgresql](), [postgresql-clusters](), [recovery-repair](), [replication]() ### AI overview This article explains how to build highly available PostgreSQL clusters with Patroni and related tools. It describes Patroni's use of replication, distributed consensus, a distributed configuration store, leader election, health checks, and YAML configuration to support automated failover. It also discusses operational challenges and the possible use of ClusterControl in the workflow. ### Source excerpt In modern application stacks, downtime is a direct threat to business continuity, customer trust, and revenue. Regardless of whether it is an e-commerce platform, a fintech application, or a critical internal system, the expectation is 24/7 availability, underscoring the critical importance of High Availability (HA) and automated failover mechanisms within PostgreSQL clusters. HA ensures that [...] The post Building High Availability PostgreSQL Clusters with Patroni and Other Integrated Approaches appeared first on Severalnines. ## Me and my shadow (link!): Disaster recovery replication made easy DevFeed: [Me and my shadow (link!): Disaster recovery replication made easy]() Original publisher: [Read original article]() Author: Paul Wilkinson Published: 2026-04-21T00:00:00Z Content type: article Language: en Sources: [Redpanda]() Topics: [Disaster Recovery](), [Replication](), [Streaming](), [systems](), [API](), [Kafka]() Tags: [disaster-recovery](), [enterprise](), [failover](), [kafka](), [operational](), [outage](), [real-time](), [replication](), [streaming]() ### AI overview This article explains Redpanda Shadow Linking as a built-in disaster recovery feature for continuous replication between streaming clusters. It describes an active-passive architecture in which a read-only shadow cluster receives topics, schemas, offsets, ACLs, commits, and messages, then becomes writable after failover. ### Source excerpt Shadow Linking made simple. Get started with real-time replication. ## Walking Through an Unplanned Failover: SQL Server Availability Groups on Kubernetes DevFeed: [Walking Through an Unplanned Failover: SQL Server Availability Groups on Kubernetes]() Original publisher: [Read original article]() Author: Anthony Nocentino Published: 2026-04-19T15:00:00Z Content type: tutorial Language: en Sources: [Kubernetes on Anthony Nocentino's Blog]() Topics: [sql-server](), [Availability](), [Kubernetes](), [Databases]() Tags: [automatic](), [availability-groups](), [container](), [containers](), [crash](), [database](), [failover](), [kubernetes](), [load](), [open-source](), [operator](), [recovery](), [sql-server](), [test]() ### AI overview This walkthrough tests unplanned SQL Server Availability Group failover on Kubernetes by force-deleting the current primary pod under idle and sustained HammerDB TPC-C load. Across six force-deletes, the operator automatically promoted new primaries and restored all three replicas, with the article examining detection, recovery behavior, logs, and timing. ### Source excerpt In my planned failover walkthrough, I showed what happens when you deliberately move the primary role to another replica. That's the easy case. Now I want to show what happens when the primary pod just disappears unexpectedly, like during a node failure or a container crash. No graceful shutdown, no demotion, just gone. I ran two test scenarios, each cycling the primary role across all three pods by force-deleting the current primary three times in a row. First, a 5GB TPC-C database idle. Then, that same 5GB database under sustained HammerDB TPC-C load. Six force-deletes total, six successful automatic failovers. I'll walk through the error log from the promoted replica, the operator's detection and recovery behavior, and the full timing data. ## Walking Through a Planned Failover: SQL Server Always On Availability Groups on Kubernetes DevFeed: [Walking Through a Planned Failover: SQL Server Always On Availability Groups on Kubernetes]() Original publisher: [Read original article]() Author: Anthony Nocentino Published: 2026-04-19T05:00:00Z Content type: tutorial Language: en Sources: [Kubernetes on Anthony Nocentino's Blog]() Topics: [sql-server](), [Kubernetes](), [Availability]() Tags: [availability-groups](), [containers](), [failover](), [kubernetes](), [open-source](), [operator](), [sql-server]() ### AI overview A walkthrough of planned failover rotation for a three-replica SQL Server Availability Group managed by sql-on-k8s-operator on Kubernetes. It examines SQL Server error logs, operator reconciliation behavior, and timing under both an idle database and a sustained TPC-C workload. ### Source excerpt When building the sql-on-k8s-operator, I wanted to make sure it could handle both planned and unplanned failovers. The easy case is a planned failover, where you deliberately move the primary role to another replica. The harder case is an unplanned failover, where the primary pod just disappears. The operator needs to handle both. I recently ran a full planned failover rotation on a three-replica SQL Server Availability Group managed by sql-on-k8s-operator, and I want to show you exactly what happens inside SQL Server and the operator during each hop. If you've been following my Introducing the SQL Server on Kubernetes Operator post, this is the logical next step: what does the error log actually look like during a planned failover, what does the operator do in response, and how long does the whole thing take? ## Introducing the SQL Server on Kubernetes Operator DevFeed: [Introducing the SQL Server on Kubernetes Operator]() Original publisher: [Read original article]() Author: Anthony Nocentino Published: 2026-04-12T05:00:00Z Content type: tutorial Language: en Sources: [Kubernetes on Anthony Nocentino's Blog]() Topics: [Kubernetes](), [sql-server](), [Availability](), [Disaster Recovery](), [Open Source]() Tags: [automated](), [automatic](), [availability](), [availability-groups](), [containers](), [disaster-recovery](), [failover](), [high-availability](), [kubernetes](), [open-source](), [operator](), [sql-server]() ### AI overview This tutorial introduces sql-on-k8s-operator, an open-source Kubernetes operator for managing SQL Server workloads. It addresses high availability and disaster recovery by automating lifecycle management, failover, and Always On Availability Group setup, and demonstrates deployment with custom resources. ### Source excerpt Are you considering replatforming your SQL Server workload due to recent vendor changes, but still need high availability and disaster recovery? You're not alone. One of the challenges with running SQL Server on Kubernetes is that there's no Kubernetes operator available. That means no automated lifecycle management, no automatic failover, and no standard way to bootstrap an Always On Availability Group on Kubernetes. I'm excited to share it today as an open-source project: sql-on-k8s-operator. Let's go. ## Test Database Resilience with the CockroachDB Fault Tolerance Demo DevFeed: [Test Database Resilience with the CockroachDB Fault Tolerance Demo]() Original publisher: [Read original article]() Author: David Bressler,Ayushi Jain Published: 2026-04-08T00:00:00Z Content type: tutorial Language: en Sources: [Cockroach Labs]() Topics: [CockroachDB](), [Resilience](), [Availability](), [Demo](), [distributed-systems](), [consistency](), [Cloud]() Tags: [availability](), [cloud](), [cockroachdb](), [consistency](), [demo](), [failover](), [how-to](), [production](), [resilience](), [verify]() ### AI overview This article explains how to use CockroachDB's Fault Tolerance Demo to trigger a real availability zone failure and observe availability, performance, consistency, failover, and replica rebalancing. The Public Preview demo is available to CockroachDB Cloud Advanced customers through the Cloud Console and should be run on a dedicated test or staging cluster. ### Source excerpt The CockroachDB database fault tolerance demo lets you trigger a real availability zone (AZ) failure within your cluster. ## From Single Instance to Split-Brain: A Database Scaling Journey DevFeed: [From Single Instance to Split-Brain: A Database Scaling Journey]() Original publisher: [Read original article]() Author: Alok Mishra Published: 2026-03-31T18:40:52Z Content type: tutorial Language: en Sources: [Walmart Global Tech]() Topics: [Databases](), [Replication](), [MySQL](), [PostgreSQL](), [Self-hosted](), [backups](), [Cloud](), [Monitoring](), [Amazon EC2](), [Kubernetes]() Tags: [architecture](), [backups](), [bare-metal](), [cloud](), [cloud-services](), [cloud-sql](), [cockroachdb](), [database](), [ec2](), [failover](), [google](), [google-cloud](), [google-cloud-sql](), [kubernetes](), [monitoring](), [mysql](), [postgresql](), [production](), [read-replica](), [recovery](), [software-architecture](), [software-development](), [software-engineering]() ### AI overview This article explains how database scaling commonly uses a single-leader architecture with asynchronous read replicas. It discusses replication lag, stale reads, split-brain risks, read/write traffic separation, and the operational responsibilities of self-managed versus fully managed database services. ### Source excerpt I used to think adding a 'Read Replica' was a magic button for scaling applications. I was wrong. While splitting read and write traffic is a standard system design pattern, implementing it introduces a world of pain - from stale reads to the dreaded Split-Brain problem. Here is how database replication actually works, and how to survive the transition. When people talk about "scaling databases" or "adding read replicas", they are almost always thinking about one specific architecture: Single-leader (Primary-Replica) architecture with asynchronous replication This is the architecture used by: MySQL + replicas PostgreSQL + streaming replication Google Cloud SQL PlanetScale, Neon, Supabase, etc. There is exactly one node that accepts writes -> called the Primary (or Leader/Master). All other nodes are Read Replicas -> they apply changes from the primary as fast as they can, but always with some delay (replication lag). This is the default and dominant model in 99% of applications today. Alternative architectures exist (multi-primary, leaderless, CRDTs, etc.), but they are rare and come with their own very different trade-offs. The second axis that actually matters in practice is: Who manages the replicas and failover for you?1. Self-hosted / Self-managed You run MySQL or PostgreSQL yourself (on EC2, Kubernetes, bare metal, etc.). You are 100% responsible for: Setting up replication Promoting a new primary when the old one dies Routing traffic correctly Handling replication lag Monitoring, backups, point-in-time recovery, etc. 2. Fully-managed cloud services RDS, Aurora, PlanetScale, Neon, Supabase, CockroachDB, Spanner, YugabyteDB, etc. The provider gives you a single connection string (or two: one for writes, one for reads) and magically keeps it pointing to healthy nodes, handles failover in seconds, and often hides (or eliminates) replication lag headaches. This second axis is the one that determines how much pain you will actually feel in production. Now, suppose yo ## How Gremlin makes disaster recovery testing easier and faster DevFeed: [How Gremlin makes disaster recovery testing easier and faster]() Original publisher: [Read original article]() Author: Gavin Cahill Published: 2026-03-04T00:00:00Z Content type: tutorial Language: en Sources: [Gremlin Blog]() Topics: [Disaster Recovery](), [Resilience](), [Testing](), [Cloud]() Tags: [backup](), [cloud](), [disaster-recovery](), [failover](), [gremlin](), [resilience](), [testing](), [use-cases]() ### AI overview The article explains how Gremlin's Disaster Recovery Testing helps teams test disaster recovery plans by simulating failures such as zone evacuations, region failovers, and cloud-provider outages. It recommends establishing service baselines with test suites, running tests regularly, and repeating them to verify fixes. ### Source excerpt Gremlin's Disaster Recovery Testing makes it easy to run zone evacuations, region failovers, and more for a fraction of the lift of traditional disaster recovery testing. ## What Database Modernization Means in the Cloud Era DevFeed: [What Database Modernization Means in the Cloud Era]() Original publisher: [Read original article]() Author: David Weiss Published: 2026-02-09T00:00:00Z Content type: article Language: en Sources: [Cockroach Labs]() Topics: [Databases](), [Cloud](), [cloud-infrastructure](), [Resilience](), [legacy](), [SQL](), [consistency]() Tags: [2026](), [cloud](), [cloud-infrastructure](), [cloud-native](), [consistency](), [databases](), [distributed](), [failover](), [infrastructure](), [legacy](), [modernization](), [operational](), [outages](), [patterns](), [performance](), [resilience](), [scale](), [schema](), [sql](), [systems]() ### AI overview This article explains database modernization in cloud environments, emphasizing architectures that scale horizontally, tolerate infrastructure failures, support global access, preserve transactional consistency, and reduce operational risk. It presents distributed SQL as an approach for incremental modernization. ### Source excerpt Database modernization is a priority for many enterprises in 2026, as pressure builds for applications to grow more distributed, failure-tolerant, and globally accessible. Increasing cloud deployments may seem like a quick cure... ## Announcing Disaster Recovery Testing DevFeed: [Announcing Disaster Recovery Testing]() Original publisher: [Read original article]() Author: Andre Newman Published: 2026-02-03T00:00:00Z Content type: release Language: en Sources: [Gremlin Blog]() Topics: [Disaster Recovery](), [Testing](), [Incident response](), [Resilience](), [Availability](), [Cloud](), [datacenter](), [Amazon Web Services](), [Azure]() Tags: [announcements](), [availability](), [aws](), [azure](), [disaster-recovery](), [failover](), [gremlin](), [health-checks](), [incident-response](), [infrastructure](), [metrics](), [resilience](), [systems](), [testing]() ### AI overview Gremlin announces Disaster Recovery Testing, a feature for running organization-wide zone, region, and datacenter-scale experiments. It helps teams validate failover, disaster recovery, and incident response processes, with health checks that can automatically halt tests when key metrics exceed defined SLA limits. ### Source excerpt Gremlin announces Disaster Recovery Testing for validating region failover processes, disaster recovery plans, incident response procedures, and more. [Next page]()