# Multi-tenancy A software architecture approach in which a solution serves multiple distinct customers or groups, called tenants, while sharing resources to varying degrees. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Lightbits Inferra KV Cache Engine Claims 16x Session Density and 10M-Token Contexts DevFeed: [Lightbits Inferra KV Cache Engine Claims 16x Session Density and 10M-Token Contexts]() Original publisher: [Read original article]() Author: Harold Fritts Published: 2026-09-14T16:23:21Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [Inference](), [Inference Performance](), [Orchestration](), [GPU](), [Multi-tenancy](), [sglang](), [TensorRT](), [vllm](), [Security]() Tags: [ai](), [cache](), [concurrent](), [enterprise](), [gpu](), [inference](), [latency](), [nvme](), [orchestration](), [security]() ### AI overview Lightbits Labs is introducing Inferra, a KV cache orchestration engine for AI inference. It virtualizes GPU memory across DRAM and NVMe storage, preserving attention states for long-context and multi-session workloads. Lightbits claims up to 16 times more concurrent sessions, more than 100 times lower latency than recomputation, and context windows of up to 10 million tokens. Inferra supports vLLM, TensorRT, and SGLang and includes tiering, predictive prefetching, tenant isolation, and encrypted data transfer. ### Source excerpt Lightbits Labs, the company that invented NVMe over TCP, is moving into inference software with Inferra, a KV cache orchestration engine that makes its public debut tomorrow, September 15, at the AI Infra Summit in Santa Clara. The software virtualizes GPU memory across DRAM and NVMe storage tiers and turns the KV cache into a The post Lightbits Inferra KV Cache Engine Claims 16x Session Density and 10M-Token Contexts appeared first on StorageReview.com. ## Data Engineering Weekly #287 DevFeed: [Data Engineering Weekly #287]() Original publisher: [Read original article]() Author: Ananth Packkildurai Published: 2026-09-14T02:52:23Z Content type: article Language: en Sources: [Data Engineering Weekly]() Topics: [data-engineering](), [Kafka](), [data observability](), [Embeddings](), [Multi-tenancy](), [Event-Streaming](), [OpenAI](), [Library](), [Code]() Tags: [architecture](), [architectures](), [data-engineering](), [data-quality](), [embedding](), [engineering](), [kafka](), [multi-tenancy](), [object-storage](), [observability](), [openai](), [streaming](), [vector]() ### AI overview Data Engineering Weekly #287 covers building data platforms from scratch, including composable architectures, data quality, and observability. It also previews talks on governed machine-executable ontologies for marketing activation and fair, order-preserving Kafka consumption for many tenants. The issue links to OpenAI's storage platform scaling for ChatGPT and Pinterest's embedding retrieval platform. ### Source excerpt The Weekly Data Engineering Newsletter ## Red Hat AI 3.5 tackles the GPU queue that can stall AI pilots DevFeed: [Red Hat AI 3.5 tackles the GPU queue that can stall AI pilots]() Original publisher: [Read original article]() Author: Adrian Bridgwater Published: 2026-09-10T17:01:36Z Content type: news Language: en Sources: [The New Stack]() Topics: [Multi-tenancy](), [AI Platform](), [GPU](), [benchmarking]() Tags: [ai](), [ai-operations](), [ai-platform](), [gpu](), [multi-tenancy](), [observability](), [platform-engineering]() ### AI overview Red Hat AI 3.5 adds multi-tenancy, isolation, priority-aware GPU scheduling, safety benchmarking, observability, and GPU resource management for enterprise AI workloads. ### Source excerpt Red Hat released Red Hat AI 3.5 this week, a move designed to let software engineering teams run AI with The post Red Hat AI 3.5 tackles the GPU queue that can stall AI pilots appeared first on The New Stack. ## Fewer lockouts, less manual work: What's new for 1Password EPM admins DevFeed: [Fewer lockouts, less manual work: What's new for 1Password EPM admins]() Original publisher: [Read original article]() Author: info@1password.com (Jairo Camacho) Published: 2026-08-26T00:00:00Z Content type: release Language: en Sources: [Blog on 1Password Blog]() Topics: [Provisioning](), [Multi-tenancy](), [Entra ID](), [releases](), [Single sign-on (SSO)]() Tags: [documentation](), [entra-id](), [identity](), [integration](), [multi-tenancy](), [news](), [outage](), [releases](), [scale](), [security]() ### AI overview 1Password announces releases for EPM admins focused on reducing lockouts and automating provisioning at scale. The updates include Entra ID secret-expiration tracking with reminders and guided rotation, integration between Multi-Tenancy and Automated Provisioning, and Vault Migrations for populating shared vaults in linked accounts. ### Source excerpt As a company grows, more employees join, but the size of the IT team overseeing critical systems often doesn't grow at the same pace. Admins have to be intentional about prioritizing their efforts to meet the needs of a growing organization. That's why we're excited to announce several releases aimed at helping admins optimize their organization's use of 1Password in two important areas: reducing lockouts and automating provisioning at scale. Preventing avoidable lockouts Entra ID Secret Expiration Most 1Password Business accounts sign in via SSO through an identity provider like Microsoft Entra ID. Admins rely on a secret provisioned by Entra to establish connectivity with 1Password. However, it comes with an expiration date. Once it expires, the connection breaks, preventing anyone from signing in. This was one of the most common and disruptive patterns we'd observe with customers. Entra ID Secret Expiration now tracks it for you. Simply record the expiration date, and 1Password will send escalating reminders across in-app banners, emails, and login prompts at a fixed cadence (e.g., 90/60/30 days). Once it's time to rotate the secret, follow the guided flow in the Admin Console, confirm it's working as intended, and the countdown resets automatically. A predictable secret expiration date should never become an outage, and now it doesn't have to. Standing up new parts of the business quickly Multi-Tenancy and Automated Provisioning integration Earlier this year we released Multi-Tenancy and Automated Provisioning, hosted by 1Password, two critical features for admins to manage provisioning, deprovisioning, and parent/child accounts at scale. Now admins can use these features in tandem, so enterprises with multi-tenant setups can take advantage of Automated Provisioning. To get started, check out our detailed documentation for setting up the Multi-Tenancy and Automated Provisioning integration To get started, check out our detailed documentation for setting up the M ## Multi-tenancy at Scale: How to Give Every User Their Own Database DevFeed: [Multi-tenancy at Scale: How to Give Every User Their Own Database]() Original publisher: [Read original article]() Author: Jeff Olson Published: 2026-08-17T00:00:00Z Content type: article Language: en Sources: [Turso Blog]() Topics: [Multi-tenancy](), [Databases](), [SQLite](), [Turso](), [MySQL](), [PostgreSQL]() Tags: [database](), [multi-tenancy](), [mysql](), [platform-api](), [postgresql](), [saas](), [scale](), [software-architecture](), [sqlite](), [turso]() ### AI overview This article argues that database-per-tenant architecture becomes practical at scale when each tenant database is a SQLite file rather than a continuously running PostgreSQL or MySQL server process. It contrasts the cost, connection-pooling, and backup challenges of server-based databases with SQLite's low-cost, file-based model, using Turso as the relevant platform context. ### Source excerpt The warnings against giving every tenant their own database assume a database is a server process. When a database is a file, the tradeoffs look completely different. ## Multi-Tenant AI Agents: Why Data Isolation Starts at the Database DevFeed: [Multi-Tenant AI Agents: Why Data Isolation Starts at the Database]() Original publisher: [Read original article]() Author: Quentin Packard Published: 2026-08-11T00:00:00Z Content type: article Language: en Sources: [Cockroach Labs]() Topics: [AI Agent](), [Multi-tenancy](), [Security](), [Software as a service](), [Database](), [Architecture & Design]() Tags: [agents](), [ai](), [ai-agents](), [architecture](), [database](), [prompt-injection](), [saas](), [security](), [sensitive-data]() ### AI overview The article argues that multi-tenant AI agent security requires database-level tenant isolation in addition to prompt safety and API-layer filtering. It explains that agents can act on improperly accessed data through downstream systems, APIs, and tool calls, expanding the potential impact of a tenant-boundary failure. ### Source excerpt Most SaaS teams shipping agentic features focus on prompt safety and API-layer filtering. But effective AI agent security also depends on... ## The hyperscale blueprint: Why cloud giants prioritize VMs for Kubernetes over bare metal DevFeed: [The hyperscale blueprint: Why cloud giants prioritize VMs for Kubernetes over bare metal]() Original publisher: [Read original article]() Author: Jack Wallen Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [virtualization](), [Kubernetes](), [Containers](), [Scalability](), [Security](), [Amazon Web Services](), [Nitro System](), [Multi-tenancy]() Tags: [aws](), [containers](), [kubernetes](), [multi-tenancy](), [nitro-system](), [scalability](), [security](), [virtual-machines](), [virtualization]() ### AI overview Cloud providers generally run Kubernetes and other containerized workloads on virtual machines rather than bare metal because virtualization offers security, isolation, flexibility, scalability, and near-bare-metal performance. AWS Nitro and Firecracker help reduce virtualization overhead, while bare metal remains reserved for specialized performance or hardware-access requirements. ### Source excerpt Why do cloud giants use VMs for Kubernetes? Learn why AWS, Azure, and Google prioritize Virtual Machines for containerized workloads over bare metal, focusing on security and scalability. ## Isovalent Networking for Virtualization: Enterprise-Grade Network Segmentation and Multi-Tenancy for VMs in Kubernetes DevFeed: [Isovalent Networking for Virtualization: Enterprise-Grade Network Segmentation and Multi-Tenancy for VMs in Kubernetes]() Original publisher: [Read original article]() Author: Marcos Hernandez Published: 2026-06-02T12:59:28Z Content type: release Language: en Sources: [Isovalent - The latest articles covering eBPF-based Networking, Observability, and Security]() Topics: [virtualization](), [Network Segmentation](), [Multi-tenancy](), [Kubernetes]() Tags: [cilium](), [ebpf](), [hubble](), [isovalent](), [kubernetes](), [kubernetes-networking](), [load-balancer](), [mesh-networking](), [migrations](), [multi-tenancy](), [network-segmentation](), [policy](), [product](), [runtime-security](), [tetragon](), [virtualization](), [website]() ### AI overview Isovalent announced the general availability of Isovalent Networking for Virtualization, a product that provides network segmentation, multi-tenancy, and policy enforcement for virtual machine workloads running in Kubernetes. It also streamlines migrations to KubeVirt. ### Source excerpt We're formally announcing the General Availability of Isovalent Networking for Virtualization (INV), a purpose-built product that brings full network segmentation, multi-tenancy, and policy enforcement to virtual machine workloads running in Kubernetes, in addition to streamlining migrations to KubeVirt. ## Scaling Personalized Marketing for Multi-Tenant Commerce Platforms DevFeed: [Scaling Personalized Marketing for Multi-Tenant Commerce Platforms]() Original publisher: [Read original article]() Author: Brent Scheibelhut Published: 2026-05-14T23:53:27Z Content type: article Language: en Sources: [Instacart]() Topics: [Multi-tenancy](), [personalization]() Tags: [architecture](), [multi-tenancy](), [personalization](), [platforms]() ### AI overview Instacart describes how it adapted its marketing automation infrastructure for Storefront Pro, a white-label e-commerce platform serving more than 350 retailers. The architecture adds multi-tenancy and scaling capabilities to support personalized, lifecycle, and self-service marketing while preserving retailer branding, tenant isolation, performance, and operational independence. ### Source excerpt TL;DRBackground: Marketing Across Marketplace and Storefront Instacart operates across two distinct commerce experiences: Instacart Marketplace, our first-party consumer marketplace Storefront Pro, our white-label e-commerce platform for retailers For years, our marketing automation infrastructure was built primarily to support Marketplace use cases. That model worked well in a first-party environment, where the product experience, customer relationship, and brand were all centrally managed by Instacart. Storefront Pro introduced a very different set of requirements. As the platform scaled to more than 350 retailers, we needed to support hundreds of independent brands, each with its own brand identity, customer base, and marketing strategy. Retailers wanted the same level of personalization and lifecycle marketing sophistication that is available on the Instacart Marketplace, but in a way that preserved their own brand and operational independence. That raised a core architectural challenge. How do we deliver Marketplace-grade personalization and lifecycle marketing capabilities to hundreds of retailers without sacrificing tenant isolation, performance, or ease of use? To succeed, the platform needed to let retail marketers: Launch onboarding, winback, and promotional campaigns Customize branding and messaging Target specific customer segments Measure performance and iterate quickly At the same time, we could not simply extend a single-tenant marketing system to a multi-tenant environment without introducing serious risks, including: Cross-retailer data leakage API rate-limit bottlenecks Manual operational overhead Inconsistent brand experiences Tight vendor coupling Solving those constraints required rethinking the architecture so that it could support self-service marketing at scale while preserving the isolation and reliability each retailer expects. Architecture Overview Our solution builds on a third-party marketing automation platform, while adding critical mu ## Table-Per-Tenant vs Shared Table: The Multi-Tenancy Tradeoff in Postgres DevFeed: [Table-Per-Tenant vs Shared Table: The Multi-Tenancy Tradeoff in Postgres]() Original publisher: [Read original article]() Published: 2026-04-15T00:00:00Z Content type: tutorial Language: en Sources: [Gaurav Sarma's Blog]() Topics: [Multi-tenancy](), [Database](), [Software as a service]() Tags: [customers](), [database](), [indexes](), [isolation](), [migration](), [multi-tenancy](), [orders](), [postgres](), [saas](), [table]() ### AI overview This tutorial compares table-per-tenant and shared-table designs for multi-tenant SaaS applications in Postgres. It explains how tenant counts, data size, schema changes, scale, query planning, migrations, monitoring, and data-deletion requirements affect the choice. ### Source excerpt You are building a SaaS product. Every customer has their own orders, invoices, and documents... ## Multi-Tenant Billing Architecture: Design Patterns for SaaS DevFeed: [Multi-Tenant Billing Architecture: Design Patterns for SaaS]() Original publisher: [Read original article]() Author: Ayush Agarwal Published: 2026-04-15T00:00:00Z Content type: tutorial Language: en Sources: [Dodo Payments Blog]() Topics: [Architecture & Design](), [Multi-tenancy](), [Software as a service](), [event driven]() Tags: [architecture](), [design-patterns](), [event-driven](), [multi-tenancy](), [saas](), [saas-billing](), [usage-based-billing]() ### AI overview A guide to designing billing systems for multi-tenant SaaS applications. It compares centralized billing services, event-driven pipelines, and external billing platforms, and discusses product catalogs, subscription management, usage metering, tenant isolation, and build-versus-buy decisions. ### Source excerpt Design patterns for building multi-tenant billing systems in SaaS. Covers tenant isolation, metering, event-driven billing, and when to build vs buy billing infrastructure. ## Automated Provisioning hosted by 1Password: A Simpler, Smarter Way to Manage Access DevFeed: [Automated Provisioning hosted by 1Password: A Simpler, Smarter Way to Manage Access]() Original publisher: [Read original article]() Author: info@1password.com (Allie Dusome) Published: 2026-03-17T00:00:00Z Content type: news Language: en Sources: [Blog on 1Password Blog]() Topics: [Provisioning](), [Security](), [API](), [Multi-tenancy](), [Confidential Computing](), [Single sign-on (SSO)](), [zero-knowledge](), [Software as a service]() Tags: [api](), [building-1password](), [developer](), [enterprise](), [infrastructure](), [multi-tenancy](), [news](), [oauth](), [security](), [zero-knowledge]() ### AI overview 1Password announces Automated Provisioning hosted by 1Password, alongside enterprise multi-tenancy, verified emails, an OAuth-based Users API, and Security Automation integrations for its Enterprise Password Manager. ### Source excerpt Modern enterprises aren't just adding employees; they're adding subsidiaries, multiple teams, contractors, AI builders, temporary projects, and new SaaS tools every week. And every new addition to a company's ecosystem also brings more credentials to manage. Unfortunately, not all of those credentials can be managed by solutions like single-sign-on (SSO) or privileged access management (PAM). Many of them might be stored in shared spreadsheets, developer environments, browser sessions, and automation workflows that traditional identity security systems were never designed to govern. This results in identity sprawl, operational drag, and an overall widening of the Access-Trust Gap. In the face of this ever-expanding attack surface, security leaders are left struggling to deploy credential security across every team and workflow, without having to build more infrastructure just to manage their infrastructure. In light of these issues, today we're introducing a new evolution for 1Password Enterprise Password Manager (EPM): enterprise-grade provisioning, structure, governance, and security automation built directly into the platform. This launch includes: Automated Provisioning hosted by 1Password Enterprise multi-tenancy Verified emails from 1Password OAuth-based Users API and new Security Automation integrations Together, these capabilities make EPM easier to deploy, easier to scale, and easier to operate as the foundational tool of modern identity security. Introducing Automated Provisioning, hosted by 1Password Automated Provisioning hosted by 1Password is our next-generation provisioning solution, built directly into 1Password. Automated Provisioning requires no servers to deploy, no bridge to maintain, and no ongoing infrastructure burden. In early testing, the response from admins was immediate. "We were done in about five minutes. We set everything up from scratch, added the integration in Okta, and it worked immediately. Adding and removing users was seamless. ## Types of Cloud Service Models DevFeed: [Types of Cloud Service Models]() Original publisher: [Read original article]() Author: Sumit Malviya Published: 2026-03-12T07:01:39Z Content type: tutorial Language: en Sources: [Backend Archives | Talent500 blog]() Topics: [cloud-computing](), [paas and iaas](), [Software as a service](), [Architecture & Design](), [Multi-tenancy]() Tags: [advantages-and-disadvantages-of-cloud-service-models](), [architecture](), [backend](), [best-practices-for-implementation-of-cloud-models](), [choosing-the-right-cloud-service-model](), [cloud](), [cloud-computing](), [comparing-saas-paas-and-iaas](), [conclusion](), [container-as-a-service-caas](), [emerging-cloud-service-models](), [function-as-a-service-faas](), [future-trends-in-cloud-service-models](), [infrastructure-as-a-service-iaas](), [paas-and-iaas](), [platform-as-a-service-paas](), [saas](), [scalability](), [software-as-a-service-saas](), [the-three-main-cloud-service-models](), [types-of-cloud-service-models](), [use-cases-for-every-cloud-service-model]() ### AI overview This article explains the main cloud service delivery models: Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). It also introduces emerging models such as FaaS and CaaS and discusses SaaS tenancy choices. ### Source excerpt Cloud computing has fundamentally changed how organizations build, deploy, and scale IT systems. Instead of investing heavily in on-premises hardware [...] The post Types of Cloud Service Models appeared first on Talent500 blog. ## Building transactional voice agents at Nector DevFeed: [Building transactional voice agents at Nector]() Original publisher: [Read original article]() Author: Pranshu Raj Published: 2026-03-07T13:39:58Z Content type: article Language: en Sources: [Pranshu Raj - blog on backend systems, performance and sidequests]() Topics: [Model Context Protocol](), [Latency](), [Multi-tenancy](), [Back end](), [observability](), [Database]() Tags: [agents](), [api](), [backend](), [database-design](), [json-rpc](), [latency](), [latency-optimization](), [mcp](), [multi-tenancy](), [observability](), [pii](), [production](), [proxy](), [rest-api](), [voice]() ### AI overview An engineer describes building customer-facing transactional voice agents for ecommerce at Nector. The article covers a REST-to-JSON-RPC MCP proxy that improved observability, PII control, context reduction, latency, and correctness, plus experiments that reduced one agent's p90 latency from more than 8 seconds to 2 seconds. ### Source excerpt Building production ready voice agents, latency optimization, multi tenancy, MCP proxies - six months of building customer facing voice agents ## Rails Multi-Tenancy DevFeed: [Rails Multi-Tenancy]() Original publisher: [Read original article]() Author: Mike Dalessio, Kimberly Rhodes, Fernando Olivares Published: 2026-02-13T18:00:00Z Content type: article Language: en Sources: [37signals Dev]() Topics: [Multi-tenancy](), [Rails](), [SQLite](), [Databases](), [MySQL](), [Open Source](), [Replication]() Tags: [active-record](), [databases](), [demo](), [developer](), [multi-tenancy](), [mysql](), [open-source](), [rails](), [replication](), [sqlite]() ### AI overview Lead Programmer Mike Dalessio discusses multi-tenancy in Rails, including 37signals' work moving Fizzy toward separate customer databases, the Active Record Tenanted gem, safeguards against accidental data leaks, and challenges involving SQLite replication and failover. ### Source excerpt Lead Programmer Mike Dalessio shares the benefits of multi-tenant databases and how his work with Fizzy led to the the Active Record Tenanted gem. ## Mastering IAM in Ceph: Multi-Tenancy, Access Control, and Why ACLs Must Die DevFeed: [Mastering IAM in Ceph: Multi-Tenancy, Access Control, and Why ACLs Must Die]() Original publisher: [Read original article]() Author: Daniel Alexander Parkes, Anthony D'Atri Published: 2026-01-24T00:00:00Z Content type: article Language: en Sources: [Ceph Blog]() Topics: [IAM](), [Authorization](), [Security](), [Multi-tenancy](), [Amazon S3](), [Amazon Web Services](), [Architecture & Design]() Tags: [access-control](), [aws](), [blog-post](), [ceph](), [defense-in-depth](), [en-article](), [en-blog-post](), [iam](), [identity](), [multi-tenancy](), [operations](), [production](), [rgw](), [s3](), [security]() ### AI overview This article explains why ACLs in Ceph Object Gateway should be disabled in favor of centralized IAM policies. It discusses S3 permission failures, multi-tenant access problems, AWS's ACL-disabled defaults, and defense-in-depth measures such as Block Public Access and explicit denies for ACL operations. ### Source excerpt Introduction ¶ Introduction: When Security Theater Becomes a Real Disaster ¶ In March 2017, a misconfigured S3 bucket at Verizon exposed the personal information of 14 million customers. The root cause wasn't a sophisticated attack; it was a simple oversight in access permissions. The bucket was set to be publicly accessible due to S3 permission misconfiguration, and no one noticed because ACLs were managed separately from the company's centralized IAM policies. The security team had implemented careful, identity-based access controls, but a resource-level ACL silently bypassed them by granting access to "All Users." This scenario repeats constantly across the industry: ACLs creating invisible access paths that security teams don't know exist, buckets accidentally exposed to the public internet, and contractors uploading data that the bucket owner cannot reliably read or administer, while still consuming capacity. Between 2017 and 2019, major companies exposed hundreds of millions of records via misconfigured S3 permissions (ACLs and/or bucket policies): Verizon (2017): 14 million customers - An AWS S3 bucket configured for public access exposed names, addresses, account PINs Facebook (2019): 540 million records - Third-party apps stored user data in publicly accessible S3 buckets Instagram (2019): 49 million records - Marketing firm left influencer database unprotected in AWS S3 The AWS response was clear: since April 2023, all new S3 buckets default to "ACLs disabled" (BucketOwnerEnforced) and Block Public Access enabled. AWS strongly recommends disabling ACLs on existing buckets and migrating to a pure policy-based model with IAM Accounts architecture. If you're running the Ceph Object Gateway (RGW), you have access to the same IAM Accounts model introduced in Ceph Squid 19.2.0. This post explains why ACLs must be disabled immediately and how to implement modern, secure access control with IAM policies. Do This First (Quick Security Wins) Before reading further, ## Technology Short Take 189 DevFeed: [Technology Short Take 189]() Original publisher: [Read original article]() Author: Scott Lowe Published: 2025-10-31T13:00:00Z Content type: article Language: en Sources: [Scott's Weblog]() Topics: [networking](), [Exploit](), [Security](), [Kubernetes](), [Multi-tenancy](), [evpn](), [GitLab](), [VXLAN](), [Cloud](), [Hardware](), [migration]() Tags: [aws](), [cilium](), [cli](), [cloud](), [cni](), [containers](), [cri-o](), [devops](), [digital-ocean](), [docker](), [evpn](), [go](), [iac](), [k8s](), [kubernetes](), [linux](), [migration](), [multi-tenancy](), [networking](), [oci](), [open-source](), [security](), [technology](), [terraform](), [vulnerabilities](), [vxlan]() ### AI overview A collection of links covering data center technologies, including EVPN/VXLAN networking, Xeon 6 server availability, the VMScape exploit, F5 appliance vulnerabilities, a Red Hat GitLab breach, multi-tenant Kubernetes, cloud migration, Pulumi resource hooks, and Terraform-related AWS tag management. ### Source excerpt Welcome to Technology Short Take #189, Halloween Edition! OK, you caught me--this Tech Short Take is not scary. I'll try harder next year. In the meantime, enjoy this collection of links about data center-related technologies. Although this installation is lighter on content than I would prefer, I am publishing anyway in the hopes of trying to get back to a somewhat-regular cadence. Here's hoping you find something useful and informative! Networking Kevin Myers dissects EVPN/VXLAN interoperability with MicroTik and IP Infusion. Ivan Pepelnjak has a new project: open source EVPN/VXLAN labs. I plan to tackle these myself in the near future! Servers/Hardware Kevin Houston takes a look at the availability of Xeon 6 CPUs across blade server vendors. Security Security researchers recently published some research on a new microarchitectural exploit called "VMScape." The TL;DR on VMScape is that it allows hypervisor information to leak from a malicious VM. Oops! Olivier Lambert has a write-up that explains why the Xen hypervisor is not affected by this exploit. (Side note: be sure to read the comments--Olivier shares some useful information there.) The leaking of source code for F5 appliances by a "nation-state affiliated cyber threat actor" has lead the CISA to call on all federal agencies to mitigate vulnerabilities in F5 appliances due to "an imminent threat to federal networks using F5 devices and software." That's not good. In early October of this year, Red Hat confirmed the breach of one of its GitLab instances, leading to the theft of nearly 570GB of data across 28,000 repositories. Oof. Cloud Computing/Cloud Management Iain Smart reviews some common exploit paths when trying to build multi-tenant Kubernetes clusters. As Iain says, multi-tenancy is hard. Digital Society discusses their migration off AWS and Digital Ocean to Hetzner. Just this past week I learned of Pulumi's resource hooks, a feature made available back in June of this year. Hrittik Roy discusses vClus ## Smarter Pod Scheduling with MatchLabelKeys in Pod Affinity DevFeed: [Smarter Pod Scheduling with MatchLabelKeys in Pod Affinity]() Original publisher: [Read original article]() Author: Abhimanyu Saharan Published: 2025-06-20T00:00:00Z Content type: tutorial Language: en Sources: [Abhimanyu Saharan]() Topics: [Kubernetes](), [Multi-tenancy](), [tenant data protection]() Tags: [kubernetes](), [kubernetes-v1-33]() ### AI overview This article explains how Kubernetes matchLabelKeys and mismatchLabelKeys enable dynamic pod affinity for safer rollouts and tenant isolation. ### Source excerpt Enhance Kubernetes pod scheduling with dynamic affinity using matchLabelKeys and mismatchLabelKeys for safer rollouts and tenant isolation. ## The Noisy Neighbor Problem in Multitenant Architectures DevFeed: [The Noisy Neighbor Problem in Multitenant Architectures]() Original publisher: [Read original article]() Author: Carlota Soto Published: 2025-04-03T23:21:00Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Multi-tenancy](), [Cloud Architecture](), [Databases](), [Cloud](), [data]() Tags: [architecture](), [architectures](), [aws](), [cloud](), [cloud-architecture](), [databases](), [infrastructure](), [memory](), [performance](), [postgres](), [product](), [real-time](), [time]() ### AI overview This article explains the noisy neighbor problem in multitenant architectures. It describes how tenants sharing a large AWS RDS instance can compete for finite CPU, memory, and I/O resources, allowing intensive workloads from some customers to degrade performance or cause failures for others. ### Source excerpt Reddit's answer for solving noisy neighbors is simple: Have a talk with them, if you can stay calm, be as straight forward as possible. Don't bend on your position. At least find out what the other neighbors think. Good advice, but it can be difficult to talk to CPUs; they tend n... ## Building durable cloud control systems with Temporal DevFeed: [Building durable cloud control systems with Temporal]() Original publisher: [Read original article]() Author: Sergey Bykov Published: 2025-01-16T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [Cloud](), [Architecture & Design](), [Cloud Architecture](), [Multi-tenancy](), [control-plane](), [Scalability](), [Managed Services](), [reliability](), [Resilience]() Tags: [architecture](), [cell-based-architecture](), [cloud](), [cloud-services](), [database](), [high-availability](), [how-to](), [low-latency](), [managed-services](), [multi-tenancy](), [reliability](), [resilience](), [scalability]() ### AI overview Temporal describes how it built Temporal Cloud as a managed service, emphasizing multi-tenancy, durable execution, and a separation between data-plane and control-plane responsibilities. It also explains using cell-based architecture to isolate resources and limit the impact of failures. ### Source excerpt Explore how Temporal leverages durable execution, multi-tenancy, and cell-based architecture to build scalable, reliable cloud control systems. Learn key lessons and insights for managed cloud services. ## Grafana Mimir Compaction: From Bottleneck to Savings DevFeed: [Grafana Mimir Compaction: From Bottleneck to Savings]() Original publisher: [Read original article]() Author: Milon James Published: 2025-01-15T11:55:57Z Content type: article Language: en Sources: [Wise Engineering - Medium]() Topics: [Grafana](), [observability](), [Scalability](), [Multi-tenancy](), [Architecture & Design](), [Latency](), [Disk image]() Tags: [architecture](), [grafana](), [grafana-mimir](), [metrics](), [multi-tenancy](), [observability](), [performance](), [platform](), [platform-engineering](), [s3](), [scalability]() ### AI overview This technical article describes Wise's migration from Thanos to Grafana Mimir, the compaction bottleneck that emerged in its metrics infrastructure, and the resulting improvements after the issue was resolved. The reported benefits include S3 storage savings, reduced cross-AZ network transfer, and lower query latency. ### Source excerpt Intro This technical blog article dives deep into a compaction bottleneck that was silently impacting our metrics infrastructure after we migrated from Thanos to Grafana Mimir. Follow along as we detail the investigation, solution, and the remarkable performance and cost improvements that transformed our metrics pipeline. To give readers some context on the scale of our operations at Wise, our production Mimir stack is currently ingesting approximately a total of 6 million metric samples per second across different tenants at the time of writing -- a testament to the critical role it plays in our observability infrastructure. Write throughput and latency In the world of observability, managing large-scale metric storage systems can be a challenging endeavour. Recently, Wise made a significant shift from Thanos to Grafana Mimir, a decision driven by our growing need for better scalability, feature richness, and operational simplicity. The switch has already yielded several benefits, but a critical issue with Mimir compaction brought new challenges to light. Once resolved, this fix not only improved system reliability but also delivered substantial cost benefits in terms of S3 storage savings, cross-AZ network transfer reductions, and query latency improvements. Here's an overview of our journey -- from the switch to Mimir to resolving compaction issues and reaping the rewards. Why We Switched from Thanos to Mimir Thanos had served us well as a metrics storage and query system, but as our use case evolved, we began to encounter limitations: Scaling Challenges: Managing Thanos components at scale -- especially with the growth in the volume of metrics data -- became operationally complex. Retention and Compaction Flexibility: Thanos's approach to compaction and retention felt rigid for our growing requirements. Feature Set: Mimir provided robust multi-tenancy capabilities, advanced query performance optimisations, and seamless integration with our existing workflows. Benefi ## A deep look into our new massive multitenant architecture DevFeed: [A deep look into our new massive multitenant architecture]() Original publisher: [Read original article]() Author: Glauber Costa Published: 2024-10-16T00:00:00Z Content type: article Language: en Sources: [Turso Blog]() Topics: [Multi-tenancy](), [Scalability](), [Architecture & Design](), [Turso](), [Serverless](), [SQLite](), [Security](), [bug]() Tags: [architecture](), [company](), [database](), [databases](), [deep-dive](), [developers](), [scalability](), [security](), [server](), [serverless](), [sqlite](), [turso]() ### AI overview Turso describes a new massive multitenant architecture built around a serverless database forked from SQLite. The design provisions a small VM, hosts many SQLite files, supports HTTP access and replication, and scales the VM to zero when inactive to control costs. The article also discusses database isolation, security and resource-allocation limitations, and the role and limits of careful development and automated testing. ### Source excerpt A deep dive into the reasons behind us rewriting our software stack ## Control Planes for Database-Per-User in Neon DevFeed: [Control Planes for Database-Per-User in Neon]() Original publisher: [Read original article]() Author: Dian M Fay Published: 2024-09-11T08:32:29Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Per-user Database](), [Multi-tenancy](), [Serverless](), [Architecture & Design](), [Databases](), [Security](), [Persistence](), [Back end](), [networking]() Tags: [applications](), [architecture](), [database](), [multi-tenancy](), [persistence](), [product](), [routing](), [security](), [serverless](), [serverless-architecture]() ### AI overview This article explains how Neon supports multi-tenant, database-per-user applications in Postgres and why a centralized control plane is needed to manage the growing number of projects. It introduces Neon's hierarchy of projects, branches, and databases, along with the isolation, testing, development, and operational considerations of this architecture. ### Source excerpt Due to its serverless architecture, Neon is a great option for building multi-tenant, database-per-user applications in Postgres. In a previous post, we explored the various approaches to multi-tenancy in Postgres, with a particular focus on the database-per-user architecture and... ## Multi-tenancy and Database-per-User Design in Postgres DevFeed: [Multi-tenancy and Database-per-User Design in Postgres]() Original publisher: [Read original article]() Author: Dian M Fay Published: 2024-08-29T18:00:25Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Per-user Database](), [Multi-tenancy](), [data-architecture](), [Database](), [Cloud](), [Serverless](), [Architecture & Design]() Tags: [architectures](), [cloud](), [data-architecture](), [database](), [development](), [multi-tenancy](), [postgres](), [product](), [schema](), [serverless]() ### AI overview This article introduces a series about building database-per-user applications with Postgres and Neon. It outlines the evolution of multi-tenant architectures--shared schema, schema-per-user, and database-per-user--and explains the tradeoff between stronger data isolation and greater operational complexity. It also describes how Neon's serverless design and hierarchy of projects, branches, and databases may affect data architecture and application design. ### Source excerpt Many Neon users aren't just storing their own information, but host data on behalf of many clients or customers, commonly called tenants. Over the decades, approaches to these multi-tenant data architectures have evolved in three main directions: shared schema, schema-per-user, a... [Next page]()