# health checks Published articles for health checks. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## How We Built Automated Capacity Testing for Kafka Consumers DevFeed: [How We Built Automated Capacity Testing for Kafka Consumers]() Original publisher: [Read original article]() Author: Kaan Karakaya Published: 2026-09-14T09:46:34Z Content type: tutorial Language: en Sources: [Booking.com Development - Medium]() Topics: [Kafka](), [Testing](), [HTTP]() Tags: [automated](), [capacity](), [health-checks](), [kafka](), [load](), [load-balancer](), [parallelism](), [partition](), [recovery](), [scale](), [site-reliability-engineer](), [sre](), [testing]() ### AI overview This article describes Booking.com's extension of an existing capacity-testing platform for Kafka consumers. It explains how changing partition assignment can provide a controlled, measurable way to test consumer throughput and whether remaining consumers can absorb reassigned work after an instance or failure domain disappears. ### Source excerpt Photo by GuerrillaBuzz on Unsplash Kafka makes it easy to distribute work across consumer instances. It is much harder to prove, safely and repeatedly, how those instances behave when the distribution changes and one of them has to carry more than its usual share. For teams that run Kafka at scale, this is a practical reliability question: how much load can a consumer instance actually handle? We had automated capacity testing for HTTP services, but Kafka consumers were still tested with manual drills. Those drills could tell us something, but they were disruptive, difficult to reproduce, and risky precisely when the system was close to its limit. We wanted a controlled way to answer three questions: What is the maximum sustainable throughput of a consumer instance? If an instance or failure domain disappears, can the remaining consumers absorb the reassigned work? Are we overprovisioning resources because we do not know the real limit? The result was an extension to our capacity-testing platform that turns Kafka partition assignment into a safe, measurable load-control mechanism. Why HTTP capacity testing did not translate Our existing platform was designed for request-response services behind a load balancer. A scheduled test selects one instance, routes an increasing share of traffic to it, runs health checks after each step, and records the highest ratio the instance can sustain. After the test, traffic returns to its normal distribution and the result is reported to the service owner. Kafka has no equivalent traffic knob. Consumers pull records, and the unit of parallelism is the partition. Within a consumer group, each partition is owned by one consumer at a time. If a topic has 12 partitions and four equally loaded instances, each instance owns about three. When one instance disappears, a rebalance gives the survivors more partitions -- and the extra work arrives as a step change, not as a smooth increase from a load balancer. The key translation: for an HTTP ## 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. ## Incident Report: July 22, 2026 DevFeed: [Incident Report: July 22, 2026]() Original publisher: [Read original article]() Author: Karina Devadoss Published: 2026-08-14T17:06:07Z Content type: news Language: en Sources: [HubSpot]() Topics: [incident](), [configuration](), [bug](), [health checks](), [client]() Tags: [2026](), [bug](), [change](), [configuration](), [customers](), [engineering](), [errors](), [europe](), [health-checks](), [hubspot](), [incident](), [memory](), [network](), [performance](), [report](), [services]() ### AI overview HubSpot reports that a configuration change triggered a latent defect in a core CRM service, causing European customers to experience CRM access disruptions for approximately 55 minutes on July 22, 2026. No data was lost, and non-European regions operated without interruption. ### Source excerpt Customers in Europe faced CRM access issues on July 22 due to a configuration change. Learn about the incident, its impact, and our commitment to improved reliability. ## 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. ## GraphOS MCP Server Connects AI Agents to Graph Health Checks DevFeed: [GraphOS MCP Server Connects AI Agents to Graph Health Checks]() Original publisher: [Read original article]() Author: Dale Seo Published: 2026-07-21T12:03:01Z Content type: release Language: en Sources: [Apollo Blog]() Topics: [GraphOS](), [MCP Server](), [Artificial Intelligence](), [health checks]() Tags: [ai](), [ai-agents](), [announcement](), [graphos](), [health-checks](), [mcp-server](), [metrics]() ### AI overview Apollo announces GraphOS MCP Server, a hosted MCP server that connects AI agents to GraphOS. Agents can access graph health information including launch status, lint results, router configuration, and traffic metrics. ### Source excerpt GraphOS MCP Server connects AI agents to GraphOS, so agents can run graph health checks: launch status, lint results, router config, and traffic metrics. ## Top System Design Performance Metrics DevFeed: [Top System Design Performance Metrics]() Original publisher: [Read original article]() Author: Saurabh Dashora Published: 2026-07-14T08:36:41Z Content type: tutorial Language: en Sources: [System Design Codex]() Topics: [benchmarking](), [Availability](), [Architecture & Design](), [Scalability](), [Load Balancing](), [health checks](), [Concurrency](), [Disaster Recovery](), [Database](), [sharding](), [IO](), [API]() Tags: [api](), [availability](), [blocking](), [concurrency](), [database](), [disaster-recovery](), [health-checks](), [load-balancing](), [performance](), [performance-metrics](), [scalability](), [sharding](), [system-design]() ### AI overview A tutorial on system design performance metrics, focusing on availability and throughput. It explains how these metrics are measured and outlines techniques such as load balancing, health checks, failover, redundancy, disaster recovery, query optimization, sharding, and asynchronous processing. ### Source excerpt Must Know Metrics ## What running Kubernetes across millions of clusters taught AWS about zonal failures DevFeed: [What running Kubernetes across millions of clusters taught AWS about zonal failures]() Original publisher: [Read original article]() Author: Raghav Tripathi Published: 2026-07-10T15:00:00Z Content type: article Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack]() Topics: [Amazon EKS](), [Kubernetes](), [Amazon Web Services](), [Resilience](), [Availability]() Tags: [amazon-eks](), [api](), [availability](), [aws](), [aws-marketplace](), [cloud-services](), [health-checks](), [kubectl](), [kubernetes](), [networking](), [operations](), [outage](), [post-contributed](), [resilience](), [sponsor-aws-marketplace](), [sponsored-post-contributed]() ### AI overview AWS describes how years of engineering on Amazon EKS addressed zonal failures, including gray failures where a zone is degraded but still passes some health checks. The approach emphasizes static stability, preserving capacity, and routing around the impaired Availability Zone. ### Source excerpt Handling the obvious failures is the easy part: a server goes down, you spin up another. The failures that actually The post What running Kubernetes across millions of clusters taught AWS about zonal failures appeared first on The New Stack. ## Linux Server Health Checks: 10 Metrics Every Sysadmin Should Monitor DevFeed: [Linux Server Health Checks: 10 Metrics Every Sysadmin Should Monitor]() Original publisher: [Read original article]() Author: Sujitha Paduchuri, ManageEngine Published: 2026-07-06T12:13:41Z Content type: tutorial Language: en Sources: [Hayden James]() Topics: [Linux](), [Monitoring](), [Linux performance](), [health checks]() Tags: [blog](), [cpu](), [disk-space](), [guests](), [health-checks](), [linux](), [linux-performance](), [load](), [memory](), [metrics](), [monitoring](), [observability](), [performance](), [performance-monitoring](), [server](), [sysadmins]() ### AI overview A practical guide to monitoring Linux server health through metrics that can reveal resource problems earlier than broad CPU, memory, or disk-usage figures. It discusses iowait, load average, active swap activity, and inode exhaustion, along with warning signs and follow-up investigations. ### Source excerpt Servers give you warnings before they fail. Most sysadmins performing Linux server monitoring miss them because they're watching the wrong numbers. The metrics that actually matter are one level deeper: iowait instead of CPU percentage, active swap paging instead of memory usage, inode counts instead of just disk space. Continue reading... ## pproxy: a forward proxy that load-balances a pool of upstream proxies DevFeed: [pproxy: a forward proxy that load-balances a pool of upstream proxies]() Original publisher: [Read original article]() Published: 2026-06-22T00:00:00Z Content type: article Language: en Sources: [Andika Ahmad Ramadhan -- Blog]() Topics: [proxy](), [client](), [health checks](), [HTTP]() Tags: [client](), [health](), [health-checks](), [http](), [prometheus](), [proxy](), [reload](), [round-robin](), [socks5](), [tls]() ### AI overview This article presents pproxy, a forward proxy that distributes client traffic across upstream proxies. It describes active health checks, round-robin selection, failover within requests, hot configuration reloads, per-user authentication, and Prometheus metrics. ### Source excerpt pproxy is a forward proxy that load-balances client traffic across a pool of upstream proxies with active health checks and hot config reload, so switching proxy providers means editing one config file instead of every client. ## Announcing no-code application fault injection DevFeed: [Announcing no-code application fault injection]() Original publisher: [Read original article]() Author: Andre Newman Published: 2026-06-02T00:00:00Z Content type: release Language: en Sources: [Gremlin Blog]() Topics: [Failure Flags](), [Serverless](), [Chaos Engineering](), [Testing](), [Availability](), [Latency](), [observability]() Tags: [availability](), [failure-flags](), [gremlin](), [health-checks](), [infrastructure](), [latency](), [no-code](), [observability](), [performance](), [serverless](), [testing](), [uptime]() ### AI overview Gremlin announces Failure Flags by proxy, a no-code application fault injection solution for serverless and managed applications. The sidecar proxy enables reliability tests such as simulating outages, adding latency, and generating exceptions without code changes. Intelligent Health Checks automatically monitor network throughput, latency, and error rate during tests. ### Source excerpt Gremlin announces Failure Flags by proxy, a no-code application fault injection solution for serverless and managed applications. Learn more in our latest blog post. ## Securely connect Claude Code to Postgres via MCP DevFeed: [Securely connect Claude Code to Postgres via MCP]() Original publisher: [Read original article]() Published: 2026-04-13T13:24:20Z Content type: tutorial Language: en Sources: [Learn on Tailscale]() Topics: [Model Context Protocol](), [Claude Code](), [Database](), [Access Control](), [audit]() Tags: [access-control](), [audit](), [claude-code](), [codex](), [cursor](), [health-checks](), [mcp](), [oauth](), [postgres](), [rate-limiting]() ### AI overview A practical guide to connecting Claude Code, Cursor, and Codex to Postgres through MCP. It covers quick local setup, comparing Postgres MCP servers, and securing team or production deployments with least-privilege credentials, environment variables, access controls, audit trails, and related governance features. ### Source excerpt Set up Postgres MCP for Claude Code, Cursor, Codex fast, and see how to handle credentials, access control, and audit trails. ## Deploying Temporal Workers to Amazon ECS DevFeed: [Deploying Temporal Workers to Amazon ECS]() Original publisher: [Read original article]() Author: Ebenezer Ankrah Published: 2026-04-02T00:00:00Z Content type: tutorial Language: en Sources: [Temporal Blog]() Topics: [Amazon Elastic Container Service](), [Deployment](), [AWS IAM](), [Dockerfile](), [container](), [health checks](), [Amazon Web Services]() Tags: [amazon](), [deployment](), [docker](), [docker-image](), [ecs](), [environment-variables](), [health-checks](), [how-to](), [iam]() ### AI overview A guide to deploying Temporal Workers on Amazon ECS with Fargate. It explains container configuration, health checks, graceful shutdown, task definitions, IAM roles, secret injection through SSM Parameter Store, and outbound connectivity requirements. ### Source excerpt A comprehensive guide to deploying Temporal Workers on Amazon ECS with Fargate. Covers container config, IAM roles, scaling, and cost-saving with Fargate Spot. ## HubSpot Incident Report: February 25, 2026 DevFeed: [HubSpot Incident Report: February 25, 2026]() Original publisher: [Read original article]() Author: Shilpa Varma Published: 2026-03-20T17:48:30Z Content type: article Language: en Sources: [HubSpot]() Topics: [incident](), [ui](), [Access Control](), [Authorization](), [configuration]() Tags: [access-control](), [analysis](), [configuration](), [deployment](), [engineering](), [errors](), [health-checks](), [http](), [hubspot](), [incident](), [issue](), [monitoring](), [report](), [user-interface]() ### AI overview HubSpot reports a February 25, 2026 service disruption that blocked access to certain contact, company, order, and project-based workflows in the user interface. Backend workflow automations continued to run normally, and no customer data was lost. The incident resulted from permission scopes being deployed without corresponding production role assignments. ### Source excerpt On February 25, 2026, HubSpot experienced a service disruption affecting user access to specific types of workflows within our user interface. All backend workflow automations continued to execute normally without interruption - no automations were delayed, missed, or lost. We have completed a thorough analysis of this incident and are implementing targeted safeguards to prevent this class of failure from recurring. ## 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. ## From Bash to Bliss: Scaling Vespa Operations with Temporal DevFeed: [From Bash to Bliss: Scaling Vespa Operations with Temporal]() Original publisher: [Read original article]() Author: Martynas Jakimčikas Published: 2026-01-21T00:00:00Z Content type: article Language: en Sources: [Vinted]() Topics: [Platform Engineering](), [Orchestration](), [Scripting, bash](), [Automation](), [health checks](), [upgrade]() Tags: [automation](), [commands](), [complexity](), [health-checks](), [maintenance](), [orchestration](), [platform](), [scheduled](), [script](), [self-service](), [upgrade]() ### AI overview This article describes how Vinted's platform team handled growing maintenance demands for its Vespa search infrastructure. As the environment expanded from hundreds to more than a thousand nodes and included many deployments, Bash scripts and Knife commands became difficult to manage. The team moved toward durable orchestration with Temporal, automated health checks, scheduled upgrades, and self-service guardrails. ### Source excerpt Growing platform - Growing maintenance Keeping the Lights On (KTLO) is an essential, yet often taxing, part of a platform engineer's role. It represents the routine operational work required to keep the business running and the platform stable. For our team, this primarily involves maintenance on our search engine, Vespa - ranging from version upgrades and service restarts to draining traffic from nodes for hardware replacements. ## Three practices for improving service availability toward 99.999% uptime DevFeed: [Three practices for improving service availability toward 99.999% uptime]() Original publisher: [Read original article]() Author: Andre Newman Published: 2025-10-02T00:00:00Z Content type: tutorial Language: en Sources: [Gremlin Blog]() Topics: [Testing](), [Availability](), [Resilience](), [observability](), [Software as a service]() Tags: [automated](), [availability](), [gremlin](), [health-checks](), [observability](), [resilience](), [sre](), [testing]() ### AI overview The article presents three practices for improving service availability toward 99.999% uptime: regular reliability testing, on-call rotations, and better visibility. It describes Gremlin's approach, including weekly tests, Health Checks, and observability metrics. ### Source excerpt 3 proven practices to achieve 99.999% uptime. Learn how teams reach five nines through weekly testing, on-call rotations, and visibility. ## How to choose a business VPN DevFeed: [How to choose a business VPN]() Original publisher: [Read original article]() Published: 2025-09-23T17:52:03Z Content type: tutorial Language: en Sources: [Learn on Tailscale]() Topics: [Virtual Private Network](), [tailscale](), [networking](), [Encryption](), [MFA](), [Single sign-on (SSO)](), [Logging](), [health checks](), [remote access]() Tags: [authentication](), [encryption](), [health-checks](), [how-to](), [logging](), [mfa](), [networking](), [remote-access](), [vpn]() ### AI overview This guide explains how to evaluate a business VPN, covering remote-access and site-to-site models, protocol support, identity integration, logging, encryption, SSO, MFA, device posture checks, and least-privilege policies. It presents Tailscale's peer-to-peer, identity-based approach as a way to avoid VPN backhaul bottlenecks and overly broad network access. ### Source excerpt Learn how to choose a business VPN that actually works for real teams. Cut through the noise and find secure, simple solutions that won't create headaches six months later. ## Keycloak 25.0.2 released DevFeed: [Keycloak 25.0.2 released]() Original publisher: [Read original article]() Author: Keycloak Team Published: 2024-07-18T00:00:00Z Content type: release Language: en Sources: [Keycloak Blog]() Topics: [Keycloak](), [migration](), [LDAP](), [REST API](), [Quarkus]() Tags: [health-checks](), [idm](), [kerberos](), [keycloak](), [keycloak-release](), [ldap](), [migration](), [migration-guide](), [openid-connect](), [release](), [rest-api](), [saml](), [secret-rotation](), [sso](), [translation]() ### AI overview Keycloak 25.0.2 was released on July 18, 2024. The release includes enhancements to management-interface configuration, Admin REST API documentation, and documentation language, along with fixes across the user interface, LDAP synchronization, authorization, migration, operators, and other components. ### Source excerpt To download the release go to Keycloak downloads. Upgrading Before upgrading refer to the migration guide for a complete list of changes. All resolved issues Enhancements #30094 Do not inherit 'https-client-auth' property for the management interface #30537 Document how Admin REST API endpoints work with Hostname config docs #30856 Remove inclusive language foreword docs Bugs #19070 authBaseUrl error on different hostname-admin-url, hostname-url admin/ui #26042 Issue when start-dev in 23.0.1 dist/quarkus #28489 Missing help text on tokens tab admin/ui #29407 Need refresh attributes group translations on Users > Details tab admin/ui #29566 User Profile attributes/groups in Admin UI are not translated using Localization for non-master realm when signed in the master realm account/ui #29761 bug: disabling all default features no longer works core #29784 Exception while trying to run a LDAP sync with a group importer and a batch size less then the actual number of groups ldap #30329 Client secret rotation UI shows wrong rotated secret admin/ui #30355 New operator failing on health checks operator #30383 Account Console (v3) no longer highlights the current page in the nav bar account/ui #30436 Client Roles are not shown when clientId property is set admin/ui #30440 UI theme bug in KC 25.0.0 admin/ui #30444 Failed to evaluate permissions when fetchRoles is enabled on role policies authorization-services #30449 Migration stuck if versions incompatible operator #30521 "Client Offline Session Max" no longer available admin/ui #30541 Account UI resources try to load from admin path instead of frontend path account/ui #30552 After migrating from 24 to 25, the signature algorithms names do not display in drop down menu admin/ui #30591 Invalid character in spanish translation file for Identity Provider Link Template translations #30652 Default server port is used instead of the management interface port in the guide about running Keycloak in a container #30662 User policy -> se ## How Deep Kubernetes Readiness Checks Can Cause Cascading Failures DevFeed: [How Deep Kubernetes Readiness Checks Can Cause Cascading Failures]() Original publisher: [Read original article]() Author: Matt Boyle Published: 2024-01-10T00:00:00Z Content type: article Language: en Sources: [Encore Updates]() Topics: [Kubernetes](), [distributed-systems](), [Chaos Engineering](), [Microservice](), [Back end](), [web applications]() Tags: [backend](), [distributed](), [distributed-systems](), [health-check](), [health-checks](), [json](), [kubernetes](), [load-balancer](), [microservices](), [mobile](), [payment](), [systems]() ### AI overview This article examines how deep HTTP readiness probes in Kubernetes can create cascading failures. It uses a payment application and its dependencies to explain how marking a pod unready when any dependency fails can remove it from the service load balancer, undermining microservice failure isolation. ### Source excerpt Distributed Systems Horror Stories: Part One ## What AI Tools Mean for Deployment, Operations and Security (AI for DevEx, Part 5) DevFeed: [What AI Tools Mean for Deployment, Operations and Security (AI for DevEx, Part 5)]() Original publisher: [Read original article]() Author: tobi@techunicorn.builders (Tobias Mende) Published: 2023-12-16T05:00:00Z Content type: article Language: en Sources: [Tobias Mende]() Topics: [Deployment](), [Monitoring](), [DevOps](), [Security](), [DevSecOps](), [AIOps](), [SIEM, Security, Observability]() Tags: [ai](), [ai-for-devex-artificial-intelligence-developer-experience-developer-productivity](), [ai-tools](), [aiops](), [datadog](), [deployment](), [deployments](), [devops](), [devsecops](), [errors](), [health-checks](), [http](), [monitoring](), [operations](), [production](), [recovery](), [security](), [software](), [software-engineering](), [tools]() ### AI overview This article examines how AI tools may reduce cognitive load for software and platform teams responsible for deployment, operations, monitoring, and security. It discusses automated log and trace monitoring, anomaly detection, alerting, health checks, HTTP 500 errors, and tools that help identify root causes and speed recovery. ### Source excerpt What AI Tools Mean for Deployment, Operations and Security (AI for DevEx, Part 5) Welcome back to AI for DevEx, Part 5. In the last part, we explored how AI tools can help us to improve our collaboration and communication. Today, we're focusing on an often ignored aspect of software engineering: the importance of deployment, operation, monitoring, and security for teams that manage their software from creation to running it in production. Terms like DevOps, DevSecOps, and DevOps have been created to emphasize the need for teams to own their software completely. ## Temporal v0.28.0 changelog DevFeed: [Temporal v0.28.0 changelog]() Original publisher: [Read original article]() Author: Cully Wakelin Published: 2020-07-31T04:00:00Z Content type: release Language: en Sources: [Temporal Blog]() Topics: [changelog](), [version](), [API](), [gRPC](), [TLS (Transport Layer Security)](), [Helm charts](), [Kubernetes](), [retry](), [Command-line interface](), [health checks](), [Go]() Tags: [changelog](), [cli](), [grpc](), [health-checks](), [helm-charts](), [kubernetes](), [product-news](), [release](), [retries](), [tls](), [version]() ### AI overview Temporal v0.28.0 is a release changelog covering changes since the project forked from Cadence. It describes the move from Thrift/TChannel to Protobuf/gRPC, TLS-encrypted communication, standardized errors and health checks, Kubernetes Helm deployment, workflow and activity retry and timeout refactors, and new CLI administration commands. ### Source excerpt Today is an exciting day for us! Temporal is releasing its newest version, v0.28.0, bringing us one step closer to a stable production ready release. ## What's Coming To Keycloak DevFeed: [What's Coming To Keycloak]() Original publisher: [Read original article]() Author: Stian Thorgersen Published: 2019-09-03T00:00:00Z Content type: opinion Language: en Sources: [Keycloak Blog]() Topics: [Keycloak](), [account](), [React](), [WebAuthn](), [Kubernetes](), [Operator Lifecycle Manager](), [API](), [Encryption](), [LDAP](), [health checks](), [Testing]() Tags: [account](), [api](), [authentication](), [automated](), [console](), [encryption](), [health-checks](), [idm](), [kerberos](), [keycloak](), [kubernetes](), [kubernetes-secrets](), [ldap](), [openid-connect](), [operator](), [password](), [rest-api](), [saml](), [software](), [sso](), [usability](), [user-experience](), [vault]() ### AI overview Keycloak's 2019 roadmap outlines planned work on a new React-based account console, WebAuthn authentication, a Kubernetes operator, external vault integration, user profiles, metrics and health checks, and improved automated testing and builds. ### Source excerpt New Account Console and Account REST API The current account console is getting dated. It is also having issues around usability and being hard to extend. For this reason we had the UXD team at Red Hat develop wireframes for a new account console. The new console is being implemented with React.js providing a better user experience as well as making it easier to extend and customise. JIRA - Account Console JIRA - Account REST API WebAuthn We are working towards adding WebAuthn support both for two factor authentication and passwordless experience. This task is not as simple as adding an authenticator for WebAuth, but will also require work on improving authentication flows and the account console. Design proposal - Authentication flow improvements Design proposal - WebAuthn Authenticator Design proposal - WebAuthn Two factor JIRA - Two factor JIRA - Passwordless Operator Operators are becoming an important way to manage software running on Kubernetes and we are working on an operator for Keycloak. The aim is to have an operator published on OperatorHub.io soon which provides basic install and seamless upgrade capabilities. This will be based on the awesome work done by the Red Hat Integreatly team. JIRA Integreatly Keycloak Operator Vault At the moment to keep credentials such as LDAP bind credentials more secure it is required to encrypt the whole database. This can be complex and can also have a performance overhead. We are working towards enabling loading credentials, such as LDAP bind credential and SMTP password, from an external vault. We're providing a built-in integration with Kubernetes secrets as well as an SPI allowing integrating with any vault provider. In the future we will also provide the option to encrypt other more dynamic credentials at rest in the database. JIRA - Vault JIRA - Encryption at rest User Profile Currently there's no single place to define user profiles for a realm. To resolve this we are planning to introduce the Profile SPI, which w ## Stack Overflow: How We Do Monitoring - 2018 Edition DevFeed: [Stack Overflow: How We Do Monitoring - 2018 Edition]() Original publisher: [Read original article]() Published: 2018-11-29T00:00:00Z Content type: article Language: en Sources: [Nick Craver]() Topics: [Monitoring](), [Stack Overflow](), [Automation](), [data](), [telemetry](), [Architecture & Design](), [health checks]() Tags: [architecture](), [automation](), [blog](), [data](), [health-checks](), [logs](), [metrics](), [monitoring](), [telemetry]() ### AI overview This article explains how Stack Overflow approaches application monitoring. It discusses monitoring concepts, automation and alert thresholds, trade-offs in operational decisions, and data types including logs, metrics, and health checks. ### Source excerpt This is #4 in a very long series of posts on Stack Overflow's architecture. Previous post (#3): Stack Overflow: How We Do Deployment - 2016 Edition What is monitoring? As far as I can tell, it means different things to different people. But we more or less agree on the concept. I think. Maybe. Let's find out! When someone says monitoring, I think of: ...but evidently some people think of other things. Those people are obviously wrong, but let's continue. When I'm not a walking zombie after reading a 10,000 word blog post some idiot wrote, I see monitoring as the process of keeping an eye on your stuff, like a security guard sitting at a desk full of cameras somewhere. Sometimes they fall asleep-that's monitoring going down. Sometimes they're distracted with a doughnut delivery-that's an upgrade outage. Sometimes the camera is on a loop-I don't know where I was going with that one, but someone's probably robbing you. And then you have the fire alarm. You don't need a human to trigger that. The same applies when a door gets opened, maybe that's wired to a siren. Or maybe it's not. Or maybe the siren broke in 1984. I know what you're thinking: Nick, what the hell? My point is only that monitoring any application isn't that much different from monitoring anything else. Some things you can automate. Some things you can't. Some things have thresholds for which alarms are valid. Sometimes you'll get those thresholds wrong (especially on holidays). And sometimes, when setting up further automation isn't quite worth it, you just make using human eyes easier. What I'll discuss here is what we do. It's not the same for everyone. What's important and "worth it" will be different for almost everyone. As with everything else in life, it's full of trade-off decisions. Below are the ones we've made so far. They're not perfect. They are evolving. And when new data or priorities arise, we will change earlier decisions when it warrants doing so. That's how brains are supposed to work. 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