# Site Reliability Published articles for Site Reliability. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## The 2-Second Rule: How to make your website feel like magic in 2026 DevFeed: [The 2-Second Rule: How to make your website feel like magic in 2026]() Original publisher: [Read original article]() Author: Louise North Published: 2026-08-04T11:43:00Z Content type: article Language: en Sources: [Web Designer Depot]() Topics: [Web](), [Latency](), [browser](), [Workers](), [Compression](), [Artificial Intelligence](), [Edge]() Tags: [architecture](), [avif-images](), [browser](), [compression](), [core-web-vitals](), [developers](), [digital-hospitality](), [edge](), [edge-computing](), [frontend-development](), [guide](), [http3](), [inclusive-design](), [interaction-to-next-paint](), [javascript-optimization](), [mobile-optimization](), [page-speed-optimization](), [performance](), [predictive-ai](), [site-reliability](), [speed](), [technical-seo](), [user-experience](), [ux-design-2026](), [web-development](), [web-development-trends](), [web-performance](), [website-usability](), [workers](), [zero-latency-ux]() ### AI overview A guide to making websites feel faster and more responsive by focusing on interaction performance, Web Workers, AVIF images, and responsive image delivery. It presents speed as an important part of user experience in 2026. ### Source excerpt In 2026, a "pretty" website is no longer enough--if it doesn't feel instant, it's invisible. This guide reveals how the world's top developers are using predictive AI and "Edge" architecture to kill the loading bar for good. ## Operating AI/ML Workloads on Kubernetes: A Headlamp Plugin for Kubeflow DevFeed: [Operating AI/ML Workloads on Kubernetes: A Headlamp Plugin for Kubeflow]() Original publisher: [Read original article]() Author: Alok Dangre Published: 2026-07-13T20:00:00Z Content type: article Language: en Sources: [Kubernetes Blog]() Topics: [Kubernetes](), [dashboards](), [AI Development](), [API](), [Web](), [data]() Tags: [ai-ml](), [apache](), [api](), [dashboards](), [kubernetes](), [site-reliability]() ### AI overview This article introduces a Headlamp plugin for Kubeflow that surfaces Kubeflow custom resources and Kubernetes-level workload information in a general-purpose Kubernetes UI. It helps operators troubleshoot notebooks, training jobs, experiments, pipelines, Pods, and related resources through the Kubernetes API. ### Source excerpt Kubernetes has quietly become the default platform for AI and machine learning. Whether you run notebook servers for data scientists, schedule distributed training jobs, tune hyperparameters, or orchestrate multi-step ML pipelines, those workloads increasingly land on a Kubernetes cluster. Kubeflow is one of the most popular ways to assemble that stack, and it does so the Kubernetes-native way: every capability is exposed as a Custom Resource Definition (CRD). That design is a gift to cluster operators, because it means ML workloads can be observed and managed with the same primitives as everything else in the cluster. But in practice the specialized ML dashboards that ship with these platforms hide the Kubernetes layer underneath. When a notebook is stuck or a training run fails, the operator is often left dropping back to kubectl to find out what actually happened at the Pod level. This post introduces the Headlamp Kubeflow plugin, which closes that gap by surfacing Kubeflow's custom resources directly inside a general-purpose Kubernetes UI. It is a worked example of a pattern any CRD-heavy platform can follow: meet operators where they already work, and show them the cluster-level truth. Headlamp itself is an extensible Kubernetes web UI maintained under Kubernetes SIG UI and licensed under Apache 2.0. It runs as a desktop app or in-cluster, and its plugin system lets anyone add first-class views for custom resources. Why operators need a different view Purpose-built ML dashboards help data scientists submit experiments, pipelines, and notebooks. Cluster operators and site reliability engineers (SREs) troubleshoot the Kubernetes resources underneath, and they ask different questions: Why is a notebook stuck? Is it ImagePullBackOff, OOMKilled, or a Pod waiting on a PersistentVolumeClaim? Which Run resources failed recently across namespaces? Which parameter set does a Katib Experiment report as optimal? Do TrainJob resources reference the expected TrainingRuntime ## How the D. E. Shaw group powers high-cardinality observability at scale with ClickHouse DevFeed: [How the D. E. Shaw group powers high-cardinality observability at scale with ClickHouse]() Original publisher: [Read original article]() Author: ClickHouse Published: 2026-05-15T00:00:00Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [observability](), [High-Performance Computing](), [Prometheus](), [Time Series](), [benchmarking](), [Compression](), [tracing]() Tags: [clickhouse](), [compression](), [compute](), [high-performance-computing](), [infrastructure](), [metrics](), [observability](), [performance](), [production](), [prometheus](), [scale](), [site-reliability](), [systems](), [time-series](), [tracing]() ### AI overview The D. E. Shaw group uses ClickHouse for high-cardinality observability across millions of compute workloads on its internal grid. The article describes evaluation results showing approximately 7x better performance than alternatives, production ingestion exceeding 500,000 records per second, and improved long-term capacity planning and tracing analysis. ### Source excerpt How the D. E. Shaw group replaced its previous observability platform with ClickHouse to handle high-cardinality metrics at scale, achieving 7x better query performance and enabling multi-year capacity planning across millions of compute workloads. ## A Q&A on Site Reliability Engineering and Observability at Thumbtack DevFeed: [A Q&A on Site Reliability Engineering and Observability at Thumbtack]() Original publisher: [Read original article]() Author: Thumbtack People Team Published: 2026-02-05T18:01:47Z Content type: article Language: en Sources: [Thumbtack Engineering - Medium]() Topics: [site-reliability-engineering](), [observability](), [Software as a service](), [Self-hosted](), [Incident response](), [telemetry]() Tags: [careers](), [company](), [culture](), [employee-experience](), [engineering](), [growth](), [incident-response](), [observability](), [saas](), [scale](), [self-hosted](), [site-reliability](), [software-engineer](), [software-engineering](), [systems](), [technical](), [technology](), [work]() ### AI overview In this Q&A, Thumbtack Senior Software Engineer Brett Shouse discusses his site reliability engineering work, including migrating self-hosted observability services to a unified SaaS platform. He also describes addressing technical debt, improving incident response, and unifying logs, traces, and metrics. ### Source excerpt A Q&A with Brett Shouse, Senior Software Engineer.As an engineer, what drew you to Thumbtack? I joined Thumbtack in March of 2025, and from day one it's felt like the right place to grow, build, and make a real impact. I was ready for a fresh challenge and wanted to help evolve a business that truly aligned with my values. I took a very intentional approach to my search. I reviewed the career sites of 106 companies to deeply understand their cultures, and from that process I applied and interviewed with four outstanding organizations. Each had strong teams and compelling missions, but Thumbtack stood out immediately. The values resonated with me, the opportunities for growth were clear, and I could see countless ways to meaningfully contribute -- not just within site reliability engineering, but across engineering as a whole. Choosing Thumbtack felt both exciting and obvious. What work are you currently focused on? I'm currently leading work to migrate a collection of self-hosted observability services into a unified SaaS platform. This effort is reducing the ongoing burden of systems administration, application support, and alert fatigue, while also lowering costs. Most importantly, it frees up engineering time and energy so teams can focus on the projects that directly support Thumbtack's customers. It's deeply satisfying work because the benefits compound across the entire organization. How would you describe the culture of your team? Supportive, driven, and genuinely fun. My teammates are endlessly curious, highly skilled, and always learning. We love automating toil away so we can focus on meaningful, high-impact work. It's a team that pushes for excellence while lifting each other up along the way. What are some of the unique technical challenges you're solving? Tackling technical debt that naturally accumulates when a company leans in early and then grows rapidly. Defining what effective incident response means for the business and enabling fast, confident res ## Your AI SRE needs better observability, not bigger models. DevFeed: [Your AI SRE needs better observability, not bigger models.]() Original publisher: [Read original article]() Author: Manveer Chawla Published: 2026-01-01T00:00:00Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [Artificial Intelligence](), [observability](), [SRE](), [observability ai agents](), [telemetry](), [clickhouse](), [incident](), [SQL]() Tags: [ai](), [dashboards](), [data](), [incident](), [logs](), [metrics](), [models](), [observability](), [site-reliability](), [sql](), [sre](), [telemetry]() ### AI overview The article argues that effective AI SRE copilots depend on rich, long-retention, high-cardinality observability data and fast queries rather than larger language models. It presents an architecture combining an LLM, SQL, an observability and context layer, and a scalable OLAP database such as ClickHouse to support incident investigation and root-cause analysis. ### Source excerpt Most AI SRE tools fail because the observability stack underneath can't keep up. Learn how to build an SRE observability architecture with the retention, cardinality, and query speed that AI copilots actually need. ## How Faster Screen Loading Affected Product Metrics in the hh.ru Mobile App DevFeed: [How Faster Screen Loading Affected Product Metrics in the hh.ru Mobile App]() Original publisher: [Read original article]() Author: alektas (hh.ru) Published: 2025-12-17T05:50:44Z Content type: article Language: ru Sources: [HeadHunter RU]() Topics: [SRE](), [Android](), [iOS]() Tags: [ab-d64cb2e3f30f](), [android](), [engineering](), [hh-ru](), [ios](), [site-reliability](), [site-reliability-engineering](), [sre](), [tag-b92bf5906bbd](), [tag-d1a8ff602d37](), [tag-f538878e20ff](), [tag-fa773991fb10](), [ux]() ### AI overview An hh.ru development team shares the preparation and interpretation of an A/B experiment that optimized one mobile-app screen, accelerated content loading, and examined the effect on product metrics. The article also discusses applying SRE practices to mobile development. ### Source excerpt Привет! Меня зовут Саша Тотилас и я руковожу командой разработки в hh.ru. Хочу поделиться с Хабром результатами A/B-эксперимента: при оптимизации одного из экранов нашего приложения мы ускорили загрузку контента и выяснили, как это влияет на продуктовые метрики, а также собрали интересные инсайты. Я не буду глубоко погружаться в технические детали, а сосредоточусь на подготовке эксперимента и интерпретации результатов. Статья будет полезна не только для мобильных разработчиков, но и для аналитиков и продактов. Читать далее ## Gremlin's unofficial reliability track for Gartner IOCS 2025 DevFeed: [Gremlin's unofficial reliability track for Gartner IOCS 2025]() Original publisher: [Read original article]() Author: Gavin Cahill Published: 2025-12-01T00:00:00Z Content type: article Language: en Sources: [Gremlin Blog]() Topics: [SRE](), [incident](), [Critical Infrastructure](), [AI Agent](), [genai]() Tags: [2025](), [agentic-ai](), [analysts](), [critical-infrastructure](), [gartner](), [incident](), [site-reliability](), [talks](), [team-topologies]() ### AI overview Gremlin presents an unofficial reliability-focused track for Gartner IOCS 2025, highlighting sessions on software-update risks, critical dependencies, SRE team structures, and the future of reliability in an AI agent world. ### Source excerpt Check out the Gremlin-curated unofficial track of reliability talks at Gartner IOCS 2025. ## Accelerating Platform Adoption with Developer Trust DevFeed: [Accelerating Platform Adoption with Developer Trust]() Original publisher: [Read original article]() Published: 2025-11-06T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [Developer Platform](), [code productivity](), [cloud-infrastructure](), [developer-productivity](), [software-development]() Tags: [chainguard-adoption-story](), [chainguard-containers](), [chainguard-images](), [chainguard-libraries](), [cloud-native](), [container](), [container-images](), [developer](), [golden-images](), [governance](), [internal-developer-platform](), [platform](), [site-reliability](), [velocity]() ### AI overview The article argues that internal development platforms need developer trust to achieve adoption. Platform teams should provide secure, standardized, and customizable paved paths that support diverse developer needs, including different programming languages and versions. It highlights the limitations of one-size-fits-most golden container images and the importance of balancing flexibility, governance, productivity, engineering velocity, and operational reliability. ### Source excerpt Chainguard helps Platform teams drive adoption with zero-CVE, customizable container images that make internal development platforms secure, fast, and trusted. ## incident.io raises $62M to build AI agents that resolve incidents with you DevFeed: [incident.io raises $62M to build AI agents that resolve incidents with you]() Original publisher: [Read original article]() Author: Stephen Whitworth Published: 2025-04-10T13:00:00Z Content type: news Language: en Sources: [The incident.io Blog]() Topics: [incident management](), [Artificial Intelligence](), [incident](), [Slack](), [Netflix](), [OpenAI]() Tags: [ai](), [ai-agents](), [engineering](), [incident](), [incident-channel](), [incident-management](), [incident-response](), [netflix](), [openai](), [outage](), [post-mortem](), [series-b](), [site-reliability](), [slack](), [slack-incident]() ### AI overview incident.io announces $62 million in Series B funding, bringing total funding above $96 million, to advance AI-powered incident management. The company describes its software reliability platform, Slack-based user experience, customer growth, weekly product updates, and migration from legacy paging tools. ### Source excerpt Today, we've raised $62M in Series B funding with over $96M in total to pioneer a new era of AI-powered incident management. ## Mastering incident routing: a critical component in incident management DevFeed: [Mastering incident routing: a critical component in incident management]() Original publisher: [Read original article]() Author: Tom Wentworth Published: 2025-03-10T16:22:00Z Content type: article Language: en Sources: [The incident.io Blog]() Topics: [Routing (disambiguation)](), [incident management](), [incident](), [Automation]() Tags: [automation](), [central](), [dependencies](), [how-to](), [incident](), [incident-channel](), [incident-management](), [incident-response](), [infrastructure](), [outage](), [post](), [post-mortem](), [real-time](), [routing](), [site-reliability](), [slack-incident](), [systems]() ### AI overview This article explains how effective incident routing sends alerts to the right people at the right time, reducing response delays, confusion, alert fatigue, and incident impact. It recommends using service ownership and dependency context, including data from the incident.io Catalog, to enable automated routing and support incident response communication. ### Source excerpt Mastering incident routing is key to reducing response times and ensuring alerts reach the right people, fast. This post breaks down how to build a smarter routing strategy using real-time service ownership data from incident.io Catalog. ## Behind the streams: how Netflix drives reliability across their organization DevFeed: [Behind the streams: how Netflix drives reliability across their organization]() Original publisher: [Read original article]() Published: 2024-07-02T09:04:13Z Content type: article Language: en Sources: [The incident.io Blog]() Topics: [Netflix](), [Deployment](), [incident management](), [User experience (UX)]() Tags: [case-study](), [deployment](), [incident](), [incident-channel](), [incident-management](), [incident-response](), [netflix](), [outage](), [post-mortem](), [site-reliability](), [slack-incident]() ### AI overview An episode discusses how Netflix deployed incident.io across its organization, using strong UX to roll it out to hundreds of teams within months. It also highlights Netflix's extensive Catalog and its partnership with incident.io. ### Source excerpt This week we sit down with Hank Jacobs, Staff Site Reliability Engineer at Netflix to discuss their deployment of incident.io across their organization. ## Practical guidance for getting started as a Site Reliability Engineer DevFeed: [Practical guidance for getting started as a Site Reliability Engineer]() Original publisher: [Read original article]() Author: Ben Wheatley Published: 2023-09-08T16:48:21Z Content type: opinion Language: en Sources: [The incident.io Blog]() Topics: [SRE](), [site-reliability-engineering](), [systems](), [telemetry]() Tags: [availability](), [getting-started](), [incident](), [incident-channel](), [incident-management](), [incident-response](), [infrastructure](), [observability](), [outage](), [post-mortem](), [site-reliability](), [slack-incident](), [sre](), [systems](), [tooling]() ### AI overview A first-time site reliability engineer at incident.io shares practical advice for creating an infrastructure roadmap with little initial context. The guidance emphasizes understanding the product and codebase, learning from experienced colleagues, and focusing on availability, reliability, deployments, observability, and data stores. ### Source excerpt Here are a few strategies that might help you build up context, find the problems that really matter and turn these into a plan of action. ## What is an SRE? Understanding the responsibilities of this crucial function DevFeed: [What is an SRE? Understanding the responsibilities of this crucial function]() Original publisher: [Read original article]() Author: incident.io Published: 2023-07-14T17:54:40Z Content type: article Language: en Sources: [The incident.io Blog]() Topics: [site-reliability-engineering](), [SRE](), [Software Engineering](), [systems](), [Google]() Tags: [administration](), [article](), [development](), [engineering](), [incident](), [incident-channel](), [incident-management](), [incident-response](), [operations](), [outage](), [performance](), [post-mortem](), [scalability](), [site-reliability](), [slack-incident](), [software](), [software-engineering](), [sre](), [systems]() ### AI overview This article explains site reliability engineering (SRE) as a discipline that combines software engineering and systems administration. It describes SRE's focus on reliability, scalability, and efficiency, along with responsibilities such as investigating performance issues, automating toil, and supporting engineering teams. It also introduces SLOs, SLAs, SLIs, and error budgets. ### Source excerpt Site reliability engineers are responsible for quite a bit, but one thing is clear--their role is critical. In this article, we break down everything you need to know about SREs and what they focus on. ## incident.fm is coming soon DevFeed: [incident.fm is coming soon]() Original publisher: [Read original article]() Author: Charlie Kingston Published: 2022-10-24T00:00:00Z Content type: article Language: en Sources: [The incident.io Blog]() Topics: [incident management](), [site-reliability-engineering](), [SRE](), [Netflix](), [Deployment]() Tags: [deployment](), [incident](), [incident-channel](), [incident-management](), [incident-response](), [netflix](), [outage](), [podcast](), [post-mortem](), [site-reliability](), [slack-incident](), [sre]() ### AI overview The article announces incident.fm, a podcast launching on YouTube and podcast apps. It previews conversations about team building, a zero-bugs policy, deploying incident.io at Netflix, and scaling a company without a clear roadmap. ### Source excerpt We've made a podcast, and we're excited to share it with you later this week... ## SRE: On-Call Procedure at trivago DevFeed: [SRE: On-Call Procedure at trivago]() Original publisher: [Read original article]() Author: Kenechukwu Nnamani Kene is an SRE engineer; An Avid Learner Follow Published: 2022-07-18T00:00:00Z Content type: tutorial Language: en Sources: [Trivago]() Topics: [site-reliability-engineering](), [incident](), [Availability](), [Microservice](), [Kubernetes]() Tags: [availability](), [devops](), [engineering](), [engineering-culture](), [incident](), [kubernetes](), [microservices](), [on-call](), [onboarding](), [shadowing](), [site-reliability](), [sre](), [uptime](), [zoom]() ### AI overview This article describes trivago's SRE on-call procedure, including onboarding, shadowing, scheduling, and rules for detecting, communicating, and resolving incidents. It also explains the company's microservices and Kubernetes-based infrastructure. ### Source excerpt One of the many responsibilities of a Site Reliability Engineer (SRE), is to ensure uptime, availability and in some cases, consistency of the product. In this context, the product refers to the... ## Sponsored Post: G-Core Labs, Close, Wynter, Pinecone, Kinsta, Bridgecrew, IP2Location, StackHawk, InterviewCamp.io, Educative, Stream, Fauna, Triplebyte DevFeed: [Sponsored Post: G-Core Labs, Close, Wynter, Pinecone, Kinsta, Bridgecrew, IP2Location, StackHawk, InterviewCamp.io, Educative, Stream, Fauna, Triplebyte]() Original publisher: [Read original article]() Author: High Scalability Published: 2022-06-10T14:39:03Z Content type: article Language: en Sources: [High Scalability]() Topics: [site-reliability-engineering](), [Databases](), [Monitoring](), [cloud-infrastructure](), [NoSQL](), [Back end](), [Linux](), [Ansible](), [hosting](), [PHP](), [WordPress]() Tags: [ansible](), [backend](), [databases](), [hosting](), [important](), [infrastructure](), [linux](), [monitoring](), [nosql](), [php](), [site-reliability](), [sponsored](), [sponsored-post]() ### AI overview A sponsored post listing hiring and recruitment opportunities from Close, Wynter, Kinsta, InterviewCamp.io, and Triplebyte. The listings seek site reliability, system administration, DevOps, SysOps, JavaScript, and related technology candidates, mentioning databases, infrastructure, Linux, PHP, Ansible, LXC, hosting, and WordPress. ### Source excerpt Who's Hiring? Close is building the sales communication platform of the future and we're looking for a Site Reliability Engineer to help us accomplish that goal. If you have a passion for databases (both SQL and NoSQL), significant experience building, managing, and monitoring infrastructure, databases, and