# resiliency Resiliency is an engineering property describing a system's ability to continue functioning, degrade gracefully, and recover rapidly from disruptions, faults, attacks, or failures. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Roadmap decisions rather than dates. DevFeed: [Roadmap decisions rather than dates.]() Original publisher: [Read original article]() Published: 2026-08-11T14:00:00Z Content type: opinion Language: en Sources: [Will Larson - Irrational Exuberance]() Topics: [Development](), [Passkeys](), [resiliency](), [User Experience](), [Mobile](), [Web]() Tags: [development](), [experience](), [implementation](), [mobile](), [phishing](), [resiliency](), [web]() ### AI overview The article argues that product roadmaps should prioritize decisions and execution constraints rather than fixed dates. It uses the development and rollout of passkey support at Imprint as an example, describing implementation behind a feature flag, staged web release, feedback iteration, and expansion to native mobile experiences. ### Source excerpt One thing that bothered me about Imprint's product after joining was our lack of passkey support. Passkey support is a rare opportunity to increase resiliency to phishing attacks while simultaneously reducing login friction. If it's good for our members, our partners, and our product, it felt like something we should have already shipped. Nonetheless, it was hard to get it onto the roadmap alongside everything else we were working on. To dig into passkeys, I started sketching out the implementation as a side quest. Some iterations later, I had something implemented behind a disabled feature flag for team review. At that point, most problems had a concrete solution implemented, and the remaining issues were messy intersections between passkey implementation and user experience. Issues remained, but the tangible implementation made tradeoffs explicit, and we were able to work through them. Soon thereafter, we launched passkeys to a small group in our web experience, iterated on feedback, finalized the details, and brought those details forward to our native mobile experiences as well. It never got onto the roadmap, but it did ship. Our passkey release planted a seed for me, but it required another experience to fully germinate. We had a discussion about hitting a date for a product extension we're developing. Our conversation kept anchoring on the idea that pulling in a date was dependent on pushing out dates for other projects. Presenting two conflicting projects as requiring timeline tradeoffs wouldn't have caused me to blink an eye five years ago, but in this conversation it inspired a sort of instinctual revolt: with modern development techniques, I believe very few projects are essentially constrained by execution bandwidth. Some are constrained by approvals, others are constrained by cross-team and cross-functional handoffs, and many are constrained by missing decisions, but almost none should be constrained purely on time. Shifting blocks of time across project ## Cyber resiliency in practice: Lessons from recent supply chain attacks DevFeed: [Cyber resiliency in practice: Lessons from recent supply chain attacks]() Original publisher: [Read original article]() Published: 2026-05-08T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [resiliency](), [supply chain attacks](), [supply-chain-security](), [axios](), [GitHub Actions](), [litellm](), [trivy](), [npm](), [PyPI](), [Python](), [Large Language Model]() Tags: [axios](), [chainguard-libraries](), [cyber-resiliency](), [cybersecurity](), [github-actions](), [litellm](), [malware](), [npm](), [pypi](), [python](), [security](), [security-attacks](), [social-engineering](), [software-supply-chain-security](), [supply-chain-attacks](), [trivy](), [worm]() ### AI overview The article defines cyber resiliency as an integrated ability to anticipate, withstand, recover from, and adapt to attacks across the full Protect, Detect, Respond, and Recover lifecycle. It examines recent supply chain attacks involving Trivy, Axios, and LiteLLM, highlighting risks such as GitHub Actions misconfiguration, long-lived tokens, incomplete credential rotation, mutable Git tags, maintainer-account compromise, and malicious package releases. ### Source excerpt Learn how modern cyber resiliency helps organizations prevent, detect, and recover from supply chain attacks like Trivy, Axios, and LiteLLM. ## Top Resiliency Patterns for Developers DevFeed: [Top Resiliency Patterns for Developers]() Original publisher: [Read original article]() Author: Saurabh Dashora Published: 2026-04-21T06:08:56Z Content type: tutorial Language: en Sources: [System Design Codex]() Topics: [resiliency](), [distributed-systems](), [circuit](), [Availability](), [Latency](), [Scalability](), [Architecture & Design]() Tags: [availability](), [circuit](), [distributed-systems](), [latency](), [monitoring](), [resiliency](), [scalability](), [timeout]() ### AI overview A quick guide to resiliency patterns for distributed systems. It introduces downstream and upstream patterns, then explains timeouts, circuit breakers, and retries with exponential backoff as ways to limit cascading failures and help downstream services recover. ### Source excerpt Quick Guide ## What is the BFF Pattern? DevFeed: [What is the BFF Pattern?]() Original publisher: [Read original article]() Author: Saurabh Dashora Published: 2026-04-07T08:41:56Z Content type: tutorial Language: en Sources: [System Design Codex]() Topics: [BFF](), [Amazon API Gateway](), [backends](), [client](), [interface](), [resiliency](), [Orchestration](), [rate-limiting]() Tags: [api-gateway](), [authentication](), [backends](), [bff](), [cache-control](), [client](), [decoupling](), [mobile](), [rate-limiting](), [resiliency]() ### AI overview The article explains the Backends-for-Frontends (BFF) pattern, in which dedicated API gateways serve different client types such as web browsers, mobile apps, and public or partner APIs. It describes how BFFs tailor APIs, isolate client-specific logic, and support functions including rate limiting, authentication, header sanitization, and cache control. It also discusses benefits such as resiliency, client-specific optimization, and faster development, along with drawbacks including code duplication and increasing complexity. ### Source excerpt And when do you need it? ## How We Migrated Millions of UGC Records to Aurora MySQL DevFeed: [How We Migrated Millions of UGC Records to Aurora MySQL]() Original publisher: [Read original article]() Author: Kovi Published: 2025-08-25T10:42:12Z Content type: article Language: en Sources: [Bazaarvoice]() Topics: [MySQL](), [DSQL](), [migration](), [Amazon RDS](), [Amazon Web Services](), [Scalability](), [Architecture & Design](), [reliability](), [resiliency]() Tags: [amazon-aurora](), [amazon-rds](), [aws](), [cost](), [database](), [devops](), [efficiency](), [migration](), [mysql](), [mysql-5-7](), [performance](), [reliability]() ### AI overview Bazaarvoice describes migrating millions of user-generated content records from Amazon RDS for MySQL to Amazon Aurora MySQL. The article explains the operational limits, performance and scaling challenges, and a two-phase modernization that first standardized on MySQL 8.0 before the Aurora migration. ### Source excerpt Discover how Bazaarvoice migrated millions of UGC records from RDS MySQL to AWS Aurora - at scale and with minimal user impact. Learn about the technical challenges, strategies, and outcomes that enabled this ambitious transformation in reliability, performance, and cost efficiency Bazaarvoice ingests and serves millions of user-generated content (UGC) items--reviews, ratings, questions, answers, and [...] ## How Teleport Simplifies Just-in-Time Access DevFeed: [How Teleport Simplifies Just-in-Time Access]() Original publisher: [Read original article]() Author: jack@goteleport.com (Jack Pitts) Published: 2025-04-23T00:00:00Z Content type: tutorial Language: en Sources: [Teleport]() Topics: [JIT](), [Access Control](), [resiliency](), [API](), [Single sign-on (SSO)](), [Command-line interface]() Tags: [access-control](), [api](), [authorization](), [cli](), [condition](), [jit](), [least-privilege](), [policy](), [regex](), [resiliency](), [sso]() ### AI overview This article explains how Teleport integrates just-in-time access with identity, policy, and workflows. It describes role-based access controls, request restrictions, automated approvals, and requirements such as reasons, approval thresholds, regex validation, session moderation, and dual authorization. ### Source excerpt Just-in-time access isn't always easy. Explore how Teleport tackles JIT challenges by simplifying least privilege, streamlining requests, and strengthening resiliency. ## The Missing Link Between Infrastructure Resiliency and High-Velocity Engineering DevFeed: [The Missing Link Between Infrastructure Resiliency and High-Velocity Engineering]() Original publisher: [Read original article]() Author: info@goteleport.com (Jack Pitts) Published: 2025-04-10T00:00:00Z Content type: opinion Language: en Sources: [Teleport]() Topics: [resiliency](), [Security](), [API keys](), [Cloud](), [Social engineering](), [Microservices](), [systems](), [Kubernetes clusters]() Tags: [api-keys](), [cloud-services](), [kubernetes-clusters](), [microservices](), [resiliency](), [security](), [social-engineering](), [systems]() ### AI overview Teleport CEO Ev Kontsevoy and analyst Jack Poller argue that modern infrastructure resiliency depends on rethinking identity and access. The article links credential-based identity attacks and exposed API keys with the growing complexity of hybrid and multi-cloud systems, microservices, Kubernetes clusters, ephemeral workloads, and machine identities. ### Source excerpt Teleport CEO Ev Kontsevoy and analyst Jack Poller explore why traditional identity approaches fail--and how Infrastructure Identity unlocks resiliency. ## Temporal Nexus is now generally available DevFeed: [Temporal Nexus is now generally available]() Original publisher: [Read original article]() Author: Phil Prasek Published: 2025-03-06T00:00:00Z Content type: release Language: en Sources: [Temporal Blog]() Topics: [Programming](), [Architecture & Design](), [resiliency](), [Security](), [observability](), [SDKs](), [Go Language](), [Java](), [Cloud]() Tags: [announce](), [connectivity](), [go](), [java](), [migration](), [netflix](), [network](), [observability](), [product-news](), [resiliency](), [reverse-proxy](), [sdk](), [security]() ### AI overview Temporal announces the general availability of Temporal Nexus, a feature for connecting Temporal Applications across isolated Namespaces. It provides service contracts for cross-namespace Workflow calls, with support for observability, debugging, security, fault isolation, and multi-region connectivity in Temporal Cloud. ### Source excerpt Temporal Nexus is now generally available! Nexus allows you to connect your Temporal Applications across isolated Namespaces. ## Durable RAG with Temporal and Chainlit DevFeed: [Durable RAG with Temporal and Chainlit]() Original publisher: [Read original article]() Author: Sergey Ustimenko Published: 2024-09-14T09:00:00Z Content type: tutorial Language: en Sources: [Temporal Blog]() Topics: [Retrieval Augmented Generation (RAG)](), [Orchestration](), [Conversational AI](), [reliability](), [resiliency](), [Framework](), [Scalability](), [Open Source]() Tags: [agents](), [ai](), [applications](), [business](), [business-intelligence](), [how-to](), [rag](), [resiliency](), [workflows]() ### AI overview This tutorial explains how Retrieval-Augmented Generation combines large language models with external knowledge sources, and how Temporal and Chainlit can help build durable, reliable, scalable conversational AI workflows. ### Source excerpt Learn about how Temporal's durable execution framework can help solve this problem by bringing durability and resiliency into multi-step RAG workflows. ## Securing Infrastructure in Healthcare: Reducing Breaches and Building Resiliency DevFeed: [Securing Infrastructure in Healthcare: Reducing Breaches and Building Resiliency]() Original publisher: [Read original article]() Author: jack.pitts@goteleport.com (Jack Pitts) Published: 2024-09-03T00:00:00Z Content type: article Language: en Sources: [Teleport]() Topics: [Security, Privacy and Abuse Prevention](), [Security](), [Access Control](), [audit](), [resiliency](), [Databases](), [Network](), [Server]() Tags: [access-control](), [audit](), [data](), [data-privacy](), [healthcare](), [healthtech](), [hipaa](), [infrastructure](), [network](), [resiliency](), [security]() ### AI overview This article examines infrastructure, security, privacy, and compliance challenges faced by digital healthcare companies operating telehealth and remote patient monitoring systems. It uses a fictional company to discuss remote device access, data transmission, role-based access control, databases, and audit logging for HIPAA compliance, and describes how Teleport is presented as a solution. ### Source excerpt Ensure HIPAA compliance, protect patient data, and streamline telehealth access. Learn how HealthTech Innovations uses Teleport to overcome infrastructure challenges. ## Increasing Resiliency in a Banking Sweep System DevFeed: [Increasing Resiliency in a Banking Sweep System]() Original publisher: [Read original article]() Author: James Heller Published: 2024-06-27T20:00:00Z Content type: article Language: en Sources: [Apartment 304]() Topics: [resiliency](), [Networks](), [Processes]() Tags: [apartment-304](), [banking](), [custom-software-solutions](), [devops](), [devops-engineer](), [financial](), [insurance](), [integration](), [network](), [operational](), [resiliency](), [software-architecture](), [software-development](), [software-engineer](), [workflows]() ### AI overview The article describes incrementally migrating a banking sweep network system to Temporal Workflow. It explains how the approach addressed stability and operational issues while avoiding the risk of a full rewrite and its single cut-over event. ### Source excerpt Incrementally migrate a banking sweep network system to a Temporal Workflow ## Enhancing sweep networks with Temporal Workflows for greater resiliency DevFeed: [Enhancing sweep networks with Temporal Workflows for greater resiliency]() Original publisher: [Read original article]() Author: James Heller Published: 2024-06-27T07:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [resiliency](), [Scalability](), [Networks]() Tags: [how-to](), [network](), [operations](), [resiliency](), [scalability]() ### AI overview This article describes how Apartment 304 incrementally migrated a banking sweep network system to Temporal workflows. The approach addressed stability and operational issues without requiring a full rewrite, while Temporal's message passing supported piece-by-piece workflow migration and faster stability improvements. ### Source excerpt Improve the resiliency and scalability of your banking sweep network by migrating to Temporal workflows, ensuring seamless and efficient operations. ## High availability in Keycloak 24 DevFeed: [High availability in Keycloak 24]() Original publisher: [Read original article]() Author: Alexander Schwartz, Ryan Emerson Published: 2024-05-07T00:00:00Z Content type: article Language: en Sources: [Keycloak Blog]() Topics: [Keycloak](), [Availability](), [resiliency](), [Deployment](), [private cloud]() Tags: [availability](), [configuration](), [deployment](), [documentation](), [high-availability](), [idm](), [kerberos](), [keycloak](), [ldap](), [openid-connect](), [private-cloud](), [release](), [resiliency](), [saml](), [sso]() ### AI overview The article recaps a Devoxx France 2024 presentation on Keycloak's high-availability architecture. It explains Keycloak's multi-site capabilities for public and private clouds and notes that Keycloak 24 fully supports active/passive deployments with simpler configuration. ### Source excerpt A single sign on solution for your customers and employees shouldn't be a single-point-of-failure in your architecture. At Devoxx France 2024, Ryan Emerson and Alexander Schwartz presented, from an architects and developer perspective, how Keycloak approached the problem. They describe which architecture the Keycloak team chose, the challenges they faced and which tools helped along the way. The slides and the recorded video are linked below. Scroll down for additional links and details of the tasks we're currently working on to further enhance the architecture. A clustered Keycloak deployment in a single site or datacenter provides sufficient availability for many. However, an increasing number of organizations need to utilize multiple sites for improved resiliency or to meet legal requirements. In 2023, Keycloak overhauled its multi-site capabilities for public and private cloud infrastructures, tested them thoroughly and provided deployment blueprints to the community. As part of the release of Keycloak 24, an active/passive setup is now fully supported. Read more about it in the new high availability guide published as part of Keycloak's documentation, and get more tools and background information in the Keycloak Benchmark Project. Since the previous blog post which covered Keycloak 23, we have made the configuration of such a setup simpler, with fewer options required by Keycloak and the Keycloak Operator. Thank you to everyone who provided feedback along the way, and those who participated in our survey in early 2023 which guided us in the implementation of this setup. Still, the journey doesn't stop here: The team is now working on durable sessions across restarts and upgrades, and a simpler Infinispan architecture which aims to eventually support active/active. Follow these issues and discussions to stay up-to-date with the latest developments, and provide feedback on Keycloak's nightly builds. ## Avoiding Kubernetes Pod Topology Spread Constraint Pitfalls DevFeed: [Avoiding Kubernetes Pod Topology Spread Constraint Pitfalls]() Original publisher: [Read original article]() Author: Matthew Kennedy Published: 2023-03-28T09:12:41Z Content type: tutorial Language: en Sources: [Wise Engineering - Medium]() Topics: [Kubernetes](), [configuration](), [Availability](), [resiliency](), [Amazon Web Services](), [Cloud]() Tags: [availability](), [aws](), [cloud](), [configuration](), [devops](), [kubernetes](), [kubernetes-clusters](), [pitfalls](), [platform-engineering](), [resiliency](), [software-engineering]() ### AI overview This article explains how Kubernetes Pod Topology Spread Constraints distribute workloads across Availability Zones or nodes. It examines how naive configurations can create unexpected pod skew and potentially cause the loss of two-thirds of pods if one Availability Zone fails. ### Source excerpt In the Wise Cloud Platform squad we take resiliency, capacity planning and costs seriously. We are always looking for ways to improve how services running on our self-managed Kubernetes clusters in AWS can be made more resistant to system failures without significantly increasing cost. One of the mechanisms we use are Pod Topology Spread Constraints. This is a built-in Kubernetes feature used to distribute workloads across a topology domain, such as Availability Zones or Nodes. In this blog post, we consider Availability Zones to be our topology domain. We discuss how to configure Pod Topology Spread Constraints correctly and how a naive configuration creates unexpected Pod skew. If Pod Topology Spread Constraints are misconfigured and an Availability Zone were to go down, you could lose 2/3rds of your Pods instead of the expected 1/3rd. This will likely negatively impact your customers' ability to use your product. What is wrong with Kubernetes Pod Topology Spread Constraints? Skew is the difference in the number of pods between the most populated and least populated Availability Zone. If we have 3 Availability Zones and 3 Pods, ideally we want a skew of 0, as seen in the diagram below. Diagram showing skew of 0 If we were to add another pod, it could be placed in any of the Availability Zones and our pods would still be distributed as evenly as possible. Our skew would then be 1. If the pods are not evenly distributed, the skew will always be greater than 1. In the case of the diagram below, Availability Zone 1 contains 2 pods and Availability Zone 3 contains zero pods, so the skew is 2. Diagram showing skew of 2 You can configure the Pod Topology Spread Constraints through the topologySpreadConstraints section of a Pods' spec. The Pods to which the configuration is applied is determined through LabelSelectors and what you deem an acceptable distribution is determined by the maxSkew field. Below is an example of a naive topologySpreadConstraints configuration: api ## How an Expired Let's Encrypt Root Certificate Nearly Caused a Shopify Platform Outage DevFeed: [How an Expired Let's Encrypt Root Certificate Nearly Caused a Shopify Platform Outage]() Original publisher: [Read original article]() Author: Raphaël Beamonte Published: 2022-01-12T15:30:02Z Content type: article Language: en Sources: [Shopify Engineering](), [Shopify Engineering - Shopify Engineering]() Topics: [certificates](), [distributed-systems](), [incident](), [resiliency](), [Incident response](), [Shopify](), [Containers]() Tags: [certificates](), [containers](), [distributed](), [distributed-systems](), [incident](), [incident-response](), [outage](), [resiliency](), [shopify]() ### AI overview Shopify describes how the expiration of an old Let's Encrypt root certificate led to certificate errors between services on September 30, 2021. The incident response included locking monolith deployments and investigating containers while the team worked to understand the problem. ### Source excerpt In distributed systems, there's plenty of occasions for things to go wrong. This is why resiliency and redundancy are important. But no matter the systems you put in place, no matter whether you did or didn't touch your deployments, issues might arise. It makes it critical to acknowledge the near misses: the situations where something could have gone wrong and the situations where something did, but it could have been worse. When was the last time it happened to you? ## Apache Airflow 2.0 is here! DevFeed: [Apache Airflow 2.0 is here!]() Original publisher: [Read original article]() Author: Apache Airflow Published: 2020-12-17T00:00:00Z Content type: release Language: en Sources: [Apache Airflow Blog]() Topics: [airflow](), [API](), [REST API](), [OpenAPI Specification](), [resiliency]() Tags: [airflow](), [announce](), [apache-airflow](), [api](), [api-documentation](), [ha](), [improvements](), [openapi](), [release](), [rest-api](), [scheduler]() ### AI overview Apache Airflow 2.0.0 has been released with the TaskFlow API for authoring DAGs, a fully supported REST API with an OpenAPI specification, scheduler performance improvements, support for multiple highly available schedulers, and Task Groups for organizing tasks. ### Source excerpt I am proud to announce that Apache Airflow 2.0.0 has been released. The full changelog is about 3,000 lines long (already excluding everything backported to 1.10), so for now I'll simply share some of the major features in 2.0.0 compared to 1.10.14: A new way of writing dags: the TaskFlow API (AIP-31) (Known in 2.0.0alphas as Functional DAGs.) DAGs are now much much nicer to author especially when using PythonOperator. Dependencies are handled more clearly and XCom is nicer to use Read more here: TaskFlow API Tutorial TaskFlow API Documentation A quick teaser of what DAGs can now look like: from airflow.decorators import dag, task from airflow.utils.dates import days_ago @dag(default_args={'owner': 'airflow'}, schedule_interval=None, start_date=days_ago(2)) def tutorial_taskflow_api_etl(): @task def extract(): return {"1001": 301.27, "1002": 433.21, "1003": 502.22} @task def transform(order_data_dict: dict) -> dict: total_order_value = 0 for value in order_data_dict.values(): total_order_value += value return {"total_order_value": total_order_value} @task() def load(total_order_value: float): print("Total order value is: %.2f" % total_order_value) order_data = extract() order_summary = transform(order_data) load(order_summary["total_order_value"]) tutorial_etl_dag = tutorial_taskflow_api_etl() Fully specified REST API (AIP-32) We now have a fully supported, no-longer-experimental API with a comprehensive OpenAPI specification Read more here: REST API Documentation. Massive Scheduler performance improvements As part of AIP-15 (Scheduler HA+performance) and other work Kamil did, we significantly improved the performance of the Airflow Scheduler. It now starts tasks much, MUCH quicker. Over at Astronomer.io we've benchmarked the scheduler--it's fast (we had to triple check the numbers as we don't quite believe them at first!) Scheduler is now HA compatible (AIP-15) It's now possible and supported to run more than a single scheduler instance. This is super useful for bot ## From Project Oslo to AWS Simple Workflow and Azure Service Bus DevFeed: [From Project Oslo to AWS Simple Workflow and Azure Service Bus]() Original publisher: [Read original article]() Author: Samar Abbas Published: 2020-10-21T04:00:00Z Content type: opinion Language: en Sources: [Temporal Blog]() Topics: [distributed-systems](), [resiliency](), [Amazon Web Services](), [Microsoft](), [Messaging](), [Microservice](), [Azure](), [Open Source]() Tags: [announcements](), [aws](), [distributed-systems](), [messaging](), [microservices](), [microservices-architecture](), [microsoft](), [open-source](), [resiliency]() ### AI overview A personal account of a developer's career path from Microsoft's Project Oslo to AWS Simple Workflow and Microsoft Azure Service Bus. It describes how developers used low-level primitives to build resiliency and how managed services helped reduce that effort. ### Source excerpt In 2010, I was contemplating my next move after working on Microsoft's Project Oslo. This inspired me to set the criteria for my next job. Read more here. ## V1 release premortem DevFeed: [V1 release premortem]() Original publisher: [Read original article]() Author: Samar Abbas Published: 2020-07-10T04:00:00Z Content type: opinion Language: en Sources: [Temporal Blog]() Topics: [SDKs](), [Go Language](), [gRPC](), [Java](), [migration](), [Persistence](), [resiliency]() Tags: [grpc](), [migration](), [persistence](), [product-news](), [release](), [resiliency](), [sdks](), [security]() ### AI overview Temporal explains the delay to its production-ready V1 release, citing uncertainty, an insufficient engineering plan behind communicated dates, and a commitment to simplify the product and preserve quality. It outlines focus areas including Go and Java SDKs, gRPC migration, and persistence improvements. ### Source excerpt We know that the recent delay caused some concern in the community. We empathize entirely and are seriously dedicated to correcting this going forward. ## Dealing With Murphy's Law at upday. DevFeed: [Dealing With Murphy's Law at upday.]() Original publisher: [Read original article]() Author: Nicola Miotto (nicola@upday.com) Published: 2017-07-24T04:39:55Z Content type: article Language: en Sources: [Upday]() Topics: [resiliency](), [Android](), [App](), [Back end](), [Front end](), [samsung](), [User experience (UX)](), [Users]() Tags: [android](), [app](), [architecture](), [backend](), [behaviour](), [collaboration](), [devices](), [errors](), [frontend](), [outage](), [resiliency](), [samsung](), [service](), [settings]() ### AI overview The article discusses the architecture of upday's Android news app, focusing on resiliency and robustness around the personalized My News feature. It also explains the app's news streams and the service-level agreement severity levels used to respond to incidents. ### Source excerpt In this blog post we will provide a few insights on the architecture of the upday news app (both backend and frontend), focusing on the work that has been put on the resiliency and robustness of the components around the My News feature. upday & Samsung Before digging into the technicalities, it's worth to spend a few words on what upday is and which responsabilities we have towards our stake holders. The App upday is a fruit of a collaboration between Axel Springer and Samsung. The end result is a news application for Android, pre-installed as the default news-app on most of the Samsung devices (S7, S8, A series etc). The one purpose of the application is to deliver relevant news content to the users. The goal is achieved by means of the two news streams that the app provides: Top News: this section is an editorial curated news stream, whose titles and headlines are manually crafted by a team of editors (in each of the available countries). It's supposed to provide the user with all the relevant news of the moment, independently from taste and preferences. My News: this is the "machine curated" news stream, generated by a swarm of super intelligent cyber beings enslaved to our will. Or at least that's how business sometimes likes to sell it. The important thing is that this stream is personalized based on the user explicit feedback and settings and behaviour. SLA With Samsung Collaborations with big players come always at a cost. For the engineering team at upday this cost is the Service Level Agreement that we need to commit to. So, when a problem with the service occurs, it's categorized in a specific severity level that also defines then the actions to take. These are, in Layman's terms, the 4 severity levels of our SLA: Severity 4: An Error affecting non- upday 's Services with little or no Users impact. More concisely: no one cares. It's hit once a single third-party picture wouldn't load, for instance. Severity 3: Errors that causes degradation of the UX. Lik ## Kubernetes Production Patterns and Anti-Patterns DevFeed: [Kubernetes Production Patterns and Anti-Patterns]() Original publisher: [Read original article]() Author: sasha@goteleport.com (Sasha Klizhentas) Published: 2017-06-25T00:00:00Z Content type: tutorial Language: en Sources: [Teleport]() Topics: [Kubernetes](), [Docker](), [resiliency](), [Availability]() Tags: [availability](), [docker](), [high-availability](), [kubernetes](), [mistakes](), [resiliency](), [techniques]() ### AI overview This tutorial presents production patterns and anti-patterns for improving the resiliency and high availability of Kubernetes deployments. It covers separating Docker build and runtime environments to reduce image size and improve security, as well as handling orphaned processes in Linux containers. ### Source excerpt We explore techniques to improve resiliency and high availability of Kubernetes deployments and common mistakes to avoid when working with Docker and Kubernetes.