# on-prem Published articles for on-prem. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## America is building datacenters faster than the grid can power them DevFeed: [America is building datacenters faster than the grid can power them]() Original publisher: [Read original article]() Author: Dan Robinson Published: 2026-09-15T16:37:00Z Content type: news Language: en Sources: [www.theregister.com - Articles]() Topics: [datacenter](), [systems]() Tags: [ai-and-ml](), [datacenters](), [energy](), [generation](), [on-prem](), [report]() ### AI overview Meeting expected energy consumption through 2030 will require $110 billion in new generation resources as America builds datacenters faster than the power grid can support. ### Source excerpt Meeting expected energy consumption through 2030 will require $110 billion in new generation resources ## September's Windows 11 patch needs an emergency patch of its own DevFeed: [September's Windows 11 patch needs an emergency patch of its own]() Original publisher: [Read original article]() Author: Richard Speed Published: 2026-09-15T13:33:55Z Content type: news Language: en Sources: [www.theregister.com - Articles]() Topics: [Windows 11](), [Microsoft](), [USB]() Tags: [audio](), [hyper-v](), [microsoft](), [on-prem](), [patch-tuesday](), [rdp](), [usb](), [windows-11]() ### AI overview Microsoft fixes Windows 11 problems affecting RDP and Hyper-V, but some USB audio devices remain silent. ### Source excerpt Microsoft fixes RDP and Hyper-V fallout, but some USB audio stays silent ## Datacenter developers want your backyard. FAS says negotiate harder DevFeed: [Datacenter developers want your backyard. FAS says negotiate harder]() Original publisher: [Read original article]() Author: Dan Robinson Published: 2026-09-14T17:26:00Z Content type: news Language: en Sources: [www.theregister.com - Articles]() Topics: [datacenter](), [on-prem]() Tags: [ai](), [community-benefits-agreements](), [data-center-policy](), [datacenter](), [datacenters](), [federation-of-american-scientists](), [infrastructure](), [on-prem](), [report]() ### AI overview A report advises local officials to negotiate carefully with datacenter developers before approving projects, focusing on tax breaks, water use, noise, and decommissioning obligations. ### Source excerpt Tax breaks, water, noise, decommissioning - report tells local officials what to nail down before signing ## Nscale swallows lion's share of UK datacenter investment DevFeed: [Nscale swallows lion's share of UK datacenter investment]() Original publisher: [Read original article]() Author: Dan Robinson Published: 2026-09-10T14:08:00Z Content type: news Language: en Sources: [www.theregister.com - Articles]() Topics: [datacenter](), [AI Platform]() Tags: [ai-infrastructure](), [datacenter](), [nscale](), [on-prem](), [united-kingdom]() ### AI overview Tracxn credits Nscale, an AI infrastructure company, with $3.7B of the UK datacenter sector's $5.7B investment haul. ### Source excerpt Tracxn credits one AI infrastructure outfit with $3.7B of sector's $5.7B haul ## Cloudera and Mistral Partner to Bring Specialized, Sovereign Intelligence to Enterprise Data DevFeed: [Cloudera and Mistral Partner to Bring Specialized, Sovereign Intelligence to Enterprise Data]() Original publisher: [Read original article]() Published: 2026-09-10T10:42:55Z Content type: news Language: en Sources: [Mistral AI Blog]() Topics: [model-deployment](), [Inference](), [data](), [datasets]() Tags: [ai](), [ai-models](), [cloud](), [data](), [enterprise](), [inference](), [on-prem](), [partnership](), [train]() ### AI overview Cloudera and Mistral announce a partnership to deploy and train customized AI models on enterprise data across hybrid, on-premises, cloud, and air-gapped environments while retaining data control. ### Source excerpt Cloudera and Mistral join forces to bring specialized, sovereign AI intelligence to enterprise data, helping regulated industries innovate on their own terms. ## Deploying AI You Control Doesn't Need to be So Hard DevFeed: [Deploying AI You Control Doesn't Need to be So Hard]() Original publisher: [Read original article]() Author: Jeetu Patel Published: 2026-09-10T09:00:50Z Content type: news Language: en Sources: [Cisco Blogs]() Topics: [Artificial Intelligence](), [AI Platforms/Deployment](), [AI Factory](), [Nvidia](), [Critical Infrastructure](), [post-training](), [data](), [Nemotron](), [on-prem](), [Fine-tuning](), [Cloud](), [Benchmark]() Tags: [ai](), [ai-factory](), [ai-infrastructure](), [ai-strategy](), [cisco-cloud-control-framework](), [cisco-secure-ai-factory](), [cloud](), [critical-infrastructure](), [data](), [executive-platform](), [fine-tuning](), [infrastructure](), [model](), [models](), [nemotron](), [nvidia](), [on-prem](), [post-training]() ### AI overview Cisco announces a collaboration with Palantir to deliver Palantir's Ontology for Cybersecurity through Cisco's Secure AI Factory, using NVIDIA as a preferred full-stack foundation for Palantir's Sovereign AI OS. The article argues that enterprise AI decisions should balance intelligence, cost, and control, including custom evaluations, post-training with proprietary data, and deployment in the cloud, at the edge, or on-premises. ### Source excerpt Announcing a collaboration with Palantir to deliver Cisco's Secure AI Factory with NVIDIA as a preferred full-stack foundation for Palantir's Sovereign AI OS. ## Google takes the nuclear option for EUR 13B Finland expansion DevFeed: [Google takes the nuclear option for EUR 13B Finland expansion]() Original publisher: [Read original article]() Author: Dan Robinson Published: 2026-09-09T16:00:00Z Content type: news Language: en Sources: [www.theregister.com - Articles]() Topics: [Google]() Tags: [cloud](), [datacenters](), [finland](), [google](), [infrastructure](), [on-prem](), [renewable-energy]() ### AI overview Google's Finland expansion includes a 22-year power deal covering up to half of the Loviisa plant's capacity, alongside wind and battery projects. ### Source excerpt 22-year power deal covers up to half of Loviisa plant's capacity, with wind and battery projects alongside ## Kubernetes access via an identity provider: Public client, not confidential DevFeed: [Kubernetes access via an identity provider: Public client, not confidential]() Original publisher: [Read original article]() Author: Kolawole Olowoporoku | CNCF Ambassador and Senior Platform Engineer Published: 2026-09-08T11:30:00Z Content type: tutorial Language: en Sources: [Cloud Native Computing Foundation]() Topics: [Kubernetes](), [Authorization](), [client]() Tags: [api](), [architecture](), [authentication](), [blog](), [browser](), [iam](), [identity](), [integration](), [kubernetes](), [on-prem](), [operations]() ### AI overview The article explains how to replace static Kubernetes credentials with identity-provider login using a public OIDC client and PKCE. It describes kubectl with kubelogin, Keycloak, kube-apiserver token validation, and RBAC-based access decisions. ### Source excerpt Access control belongs on the same day-zero checklist as networking and storage. On most on-prem clusters, it never makes the list. The Identity Gap Managed cloud Kubernetes ships IAM or SSO integration out of the box.... ## On the Ground at VMware Explore 2026: How Lenovo Is Partnering with VMware for Turnkey AI and Taming the Memory Crunch DevFeed: [On the Ground at VMware Explore 2026: How Lenovo Is Partnering with VMware for Turnkey AI and Taming the Memory Crunch]() Original publisher: [Read original article]() Author: Tom Fenton Published: 2026-09-01T18:28:19Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [Generative AI](), [on-prem](), [cloud-infrastructure](), [datacenter](), [Cloud](), [data]() Tags: [2026](), [ai](), [cloud](), [data-centers](), [enterprise](), [enterprise-storage](), [generative-ai](), [infrastructure](), [on-prem](), [technology]() ### AI overview At VMware Explore 2026, StorageReview discusses Lenovo's partnership with VMware around turnkey generative AI infrastructure, the return to on-premises deployments, and memory supply constraints. The article describes moving memory tiering into the VMware Cloud Foundation hypervisor layer, using NVMe drives to reduce dependence on expensive DRAM without requiring application or operating-system rewrites. ### Source excerpt At VMware Explore 2026, we had the chance to sit down with Stuart McRae, Executive Director of Lenovo's Enterprise Storage, Software, and Solutions Offering Group. Rather than focusing on a specific product or technology, as we often do, this conversation took a broader view. We covered everything from how AI is reshaping buyer options and The post On the Ground at VMware Explore 2026: How Lenovo Is Partnering with VMware for Turnkey AI and Taming the Memory Crunch appeared first on StorageReview.com. ## Core Banking Modernization with Temenos Core and CockroachDB DevFeed: [Core Banking Modernization with Temenos Core and CockroachDB]() Original publisher: [Read original article]() Author: Nanda Badrappan,Muruga Balakrishnan Published: 2026-08-24T00:00:00Z Content type: article Language: en Sources: [Cockroach Labs]() Topics: [CockroachDB](), [Cockroach Labs](), [Data Infrastructure](), [Availability](), [real-time](), [Resilience](), [Transactions](), [legacy](), [SQL](), [Cloud](), [systems](), [on-prem]() Tags: [availability](), [cloud](), [cockroach-labs](), [cockroachdb](), [data-infrastructure](), [legacy](), [on-prem](), [real-time](), [resilience](), [sql](), [transactions]() ### AI overview This article explains why banks are modernizing legacy core banking infrastructure. It describes how Temenos Core and CockroachDB are positioned to support real-time transaction processing, continuous availability, distributed operations, resilience, and regulatory requirements. ### Source excerpt Banking has become an always-on business. Customers expect instant payments, accurate balances, and continuous access to financial services... ## Chaining Activities -- from text to vectors DevFeed: [Chaining Activities -- from text to vectors]() Original publisher: [Read original article]() Author: Houman Kargaran Published: 2026-08-12T00:00:00Z Content type: tutorial Language: en Sources: [Temporal Blog]() Topics: [data](), [Embeddings](), [on-prem](), [pii](), [Redis](), [retry](), [Sequences]() Tags: [article](), [community](), [data-pipeline](), [embeddings](), [on-prem](), [pii](), [redis](), [retries](), [storage]() ### AI overview This guest post explains a Temporal workflow that chains discrete Activities to process complaints while maintaining a PII boundary. It uses an on-premises all-MiniLM-L6-v2 model for embeddings, caches vectors in Redis, stores them externally, and relies on deterministic workflow sequencing and retry policies. ### Source excerpt Learn how to build a durable, PII-conscious data pipeline with Temporal using on-prem embeddings, idempotent Activities, external vector storage, and retries. ## I spent two months screen-sharing to ship one integration. So I rebuilt it on Temporal. DevFeed: [I spent two months screen-sharing to ship one integration. So I rebuilt it on Temporal.]() Original publisher: [Read original article]() Author: Stephen Montague Published: 2026-08-06T00:00:00Z Content type: tutorial Language: en Sources: [Temporal Blog]() Topics: [proxy](), [networking](), [legacy application](), [Messaging](), [on-prem](), [retry](), [Cloud]() Tags: [legacy-application](), [messaging](), [networking](), [on-prem](), [proxy](), [retry](), [software](), [temporal-voices]() ### AI overview The article explains how to connect a cloud application to a firewalled on-premises edge site using an egress-only proxy and a single outbound Temporal connection. It describes the operational difficulties of a legacy, one-way integration and the need for bidirectional messaging, retry handling, and testing. ### Source excerpt How to durably reach a firewalled edge site with no inbound ports: an egress-only proxy that hot-reloads config over a single outbound Temporal connection. ## ClusterControl 2.5.0 brings ClickHouse support to on-prem, cloud and hybrid environments DevFeed: [ClusterControl 2.5.0 brings ClickHouse support to on-prem, cloud and hybrid environments]() Original publisher: [Read original article]() Author: Kyle Buzzell Published: 2026-08-05T08:38:18Z Content type: release Language: en Sources: [SeveralNines]() Topics: [clickhouse](), [Cloud](), [on-prem](), [Databases]() Tags: [analytics](), [clickhouse](), [cloud](), [clustercontrol](), [clustercontrol-releases](), [clustercontrol-v2-5-0](), [database](), [olap](), [on-prem](), [release](), [sovereign-dbaas]() ### AI overview ClusterControl 2.5.0 adds support for ClickHouse across on-premises, cloud, and hybrid environments. The release enables deployment and lifecycle management for standalone or replicated ClickHouse clusters, alongside PostgreSQL backup workflow upgrades, usage metering, and a restored ClusterControl v1 capability. ### Source excerpt ClusterControl 2.5.0 is here, and it marks a milestone for the platform: ClickHouse joins the family of supported database engines -- and with it, a capability no analytics vendor's cloud can offer you. Wherever you run ClusterControl -- on-premises, in any cloud, or hybrid -- you can now deploy ClickHouse either as a standalone OLAP [...] The post ClusterControl 2.5.0 brings ClickHouse support to on-prem, cloud and hybrid environments appeared first on Severalnines. ## Инференс LLM: от KV-кэша до продакшен-деплоя DevFeed: [Инференс LLM: от KV-кэша до продакшен-деплоя]() Original publisher: [Read original article]() Author: a\_ryzhov (hh.ru, Конференции Олега Бунина (Онтико)) Published: 2026-07-27T05:30:45Z Content type: tutorial Language: ru Sources: [HeadHunter RU]() Topics: [Large Language Model](), [Caching](), [on-prem](), [genai](), [MLOps](), [sglang](), [vllm]() Tags: [2026](), [compute](), [genai](), [http](), [inference](), [kv-cache](), [llm](), [mlops](), [on-prem](), [sglang](), [sram](), [vllm]() ### AI overview This Russian-language developer article explains how LLM inference behaves in on-premises production environments in 2026. It argues that GPU memory management is the main efficiency constraint, describes how KV caching shifts decoding from compute-bound to memory-bandwidth-bound work, and introduces vLLM and SGLang as ways to address the problem. ### Source excerpt Привет! Я Саша Рыжов, MLOps-инженер в hh.ru, уже три года занимаюсь развитием инфраструктуры для искусственного интеллекта. Компании, которые развивают GenAI, рано или поздно приходят к задачам по запуску LLM на собственном железе. В статье я расскажу, как обстоят дела с движками инференса в 2026 году и как запустить on-prem-прод и не изобрести при этом велосипед. Читать далее ## How Alien uses Turso to make BYOC deployments reliable DevFeed: [How Alien uses Turso to make BYOC deployments reliable]() Original publisher: [Read original article]() Author: Alon Gubkin Published: 2026-06-22T00:00:00Z Content type: article Language: en Sources: [Turso Blog]() Topics: [Turso](), [Deployment](), [Cloud](), [Databases](), [AWS IAM](), [telemetry](), [on-prem]() Tags: [aws](), [azure](), [database](), [embedded](), [gcp](), [iam](), [infrastructure](), [monitoring](), [on-prem](), [security](), [software](), [telemetry](), [turso]() ### AI overview Alien uses an embedded, encrypted Turso database to support reliable Bring Your Own Cloud deployments across customer-controlled AWS, GCP, Azure, and on-premises environments. The article explains how Alien's centralized control plane and local operator handle deployments, updates, telemetry, and failures without requiring unrestricted access to customer infrastructure. ### Source excerpt How Alien uses an embedded, encrypted Turso database to keep BYOC deployments manageable inside environments it does not control. ## Why we chose Turso to secure AI credentials DevFeed: [Why we chose Turso to secure AI credentials]() Original publisher: [Read original article]() Author: Devon Tietjen Published: 2026-06-16T00:00:00Z Content type: article Language: en Sources: [Turso Blog]() Topics: [Turso](), [Disk image](), [Databases](), [API](), [cloud-infrastructure](), [Deployment](), [Latency](), [Artificial Intelligence]() Tags: [ai](), [api](), [databases](), [deployment](), [embedded](), [embedded-replicas](), [encryption](), [infrastructure](), [latency](), [local](), [on-prem](), [rust](), [security](), [telemetry](), [turso]() ### AI overview Eden uses Turso's encrypted embedded storage to keep sensitive control-plane state while deploying its infrastructure gateway close to the databases, APIs, AI endpoints, and internal tools it governs. This embedded approach reduces latency, network hops, external dependencies, and operational overhead, while supporting private, on-premises, air-gapped, and low-latency environments without requiring a separate Postgres deployment. ### Source excerpt How Eden uses Turso's encrypted embedded storage to hold sensitive control-plane state, so its gateway can run close to the databases, APIs, and AI endpoints it governs without standing up a separate Postgres. ## ScyllaDB Customer Experience Spotlight: Faisal Saeed DevFeed: [ScyllaDB Customer Experience Spotlight: Faisal Saeed]() Original publisher: [Read original article]() Author: Cynthia Dunlop Published: 2026-06-11T12:01:56Z Content type: article Language: en Sources: [ScyllaDB]() Topics: [ScyllaDB Cloud](), [data-architecture](), [migration](), [Automation](), [Database](), [on-prem](), [MariaDB]() Tags: [app](), [automation](), [blog](), [cloud](), [community](), [customer](), [cx-profiles](), [data-modeling](), [database](), [demo](), [india](), [migration](), [on-prem](), [scale](), [scylladb](), [scylladb-cloud](), [testing](), [tool]() ### AI overview Faisal Saeed, Principal Customer Engineer at ScyllaDB, describes his work supporting existing customers, evaluating deployments, data modeling, and migrations to ScyllaDB Enterprise or ScyllaDB Cloud. He also discusses the ScyllaDB Automation Framework, which automates cluster operations, workload execution, and stress testing, and highlights ScyllaDB Cloud and a large-scale customer use case in India. ### Source excerpt Meet Faisal Saeed, Principal Customer Engineer on the Customer Experience team here at ScyllaDB. ## Reliability Engineering for Air-Gapped Systems DevFeed: [Reliability Engineering for Air-Gapped Systems]() Original publisher: [Read original article]() Author: Alex Ewerlöf Published: 2026-04-03T21:03:06Z Content type: article Language: en Sources: [Alex Ewerlof Notes]() Topics: [observability](), [systems](), [Resilience](), [on-prem](), [Security](), [Requirements]() Tags: [observability](), [on-prem](), [reliability-engineering](), [resilience](), [security](), [supply-chain-attacks](), [systems](), [work]() ### AI overview This article discusses reliability engineering for air-gapped systems where software teams cannot access runtime data, metrics, or logs. It describes using SLI and SLO practices, alerting, secure operational processes, and on-premises maintenance to manage reliability in systems isolated from the internet. ### Source excerpt Tips and tricks to work around inaccessible observability ## Virtual machines, virtually everywhere - and with real security gaps DevFeed: [Virtual machines, virtually everywhere - and with real security gaps]() Original publisher: [Read original article]() Author: Tomáš Foltýn Published: 2026-03-25T10:00:00Z Content type: article Language: en Sources: [WeLiveSecurity]() Topics: [Cloud](), [Security](), [cloud-infrastructure](), [Amazon Web Services](), [Azure](), [on-prem](), [Amazon EC2](), [Amazon S3]() Tags: [amazon-web-services-aws](), [apis](), [aws](), [azure](), [breach](), [business-security](), [cloud](), [identity](), [infrastructure](), [ip](), [on-prem](), [operations](), [s3](), [scale](), [security](), [speed](), [storage]() ### AI overview Cloud adoption has created a widespread virtual-machine sprawl problem. Unmanaged or poorly monitored VMs may miss operating-system updates, retain outdated access policies, and evade security operations, creating subtle risks alongside more visible threats such as misconfigured storage buckets and exposed APIs. ### Source excerpt Cloud VMs offer unmatched speed, scale and flexibility - all of which could eventually count for little if they're left to fend for themselves ## Breaking the Loop: How we migrated our backup catalog for 250+ MySQL clusters to AWS DevFeed: [Breaking the Loop: How we migrated our backup catalog for 250+ MySQL clusters to AWS]() Original publisher: [Read original article]() Author: Ioannis Androulidakis Published: 2026-02-19T14:19:52Z Content type: article Language: en Sources: [Booking.com Development - Medium]() Topics: [migration](), [Amazon RDS](), [MySQL](), [Amazon Web Services](), [backups](), [Cloud](), [on-prem]() Tags: [amazon-rds](), [aws](), [backup](), [cloud](), [cloud-migration](), [data-backup](), [database](), [databases](), [migration](), [mysql](), [on-prem](), [relational-databases](), [reliability-engineering]() ### AI overview Booking.com's Database Engineering team describes migrating the backup catalog orchestrator's backend for more than 250 production MySQL clusters from a self-managed on-premises MySQL database to managed Amazon RDS for MySQL in AWS. The article discusses the migration's challenges, implemented solutions, and lessons learned. ### Source excerpt This post was originally published internally on May 9, 2025 and has been reworked for a public audience. Authors: Ioannis Androulidakis, Mohammed Gaafar Intro The Database Engineering team at Booking.com is constantly looking for ways to improve database reliability and support scaling our business. In 2025 we completed a major milestone in our effort to modernize our infrastructure: we seamlessly migrated the backend of the orchestrator that schedules and manages the daily backups of 250+ production MySQL clusters. More specifically, we moved from a self-managed MySQL database running on premises to a managed Amazon RDS MySQL database running in the cloud. This blog post delves into the challenges we faced, the solutions we implemented, and some key lessons we learned along the way. We are moving to the cloud (gradually) Cloud adoption is a journey, not a switch. Over the past few years the adoption of AWS solutions at Booking.com has been growing rapidly across different business units, allowing teams to be more autonomous, run their databases in the cloud and solve known issues with their old on-premise setup. Like customer teams, we are running our own databases to power the core services that we offer and manage databases efficiently at scale. To name a few: automatic failover of writable primaries, auto-scaling of read-only replicas, service discovery, capacity planning, online schema changes, user access management, volume backups, etc. Traditionally, the Database Engineering team has been running databases on-premises. In the emerging era of cloud databases, we wanted to compare our in-house offerings with existing cloud databases and bridge the gap between the two. Knowing that we lacked deep, hands-on experience with the operational realities of running critical infrastructure on AWS, we saw this as a unique opportunity to learn more about cloud databases while also improving the reliability of our systems. Long story short, we decided to prioritize the m ## AI Infrastructure Needs an Agentic Identity Framework -- We're Building It DevFeed: [AI Infrastructure Needs an Agentic Identity Framework -- We're Building It]() Original publisher: [Read original article]() Author: ev@goteleport.com (Ev Kontsevoy) Published: 2026-01-27T00:00:00Z Content type: opinion Language: en Sources: [Teleport]() Topics: [AI Infrastructure](), [Artificial Intelligence](), [AI Strategy]() Tags: [adoption](), [agentic-ai](), [agents](), [ai](), [ai-infrastructure](), [api-keys](), [cloud](), [cryptographic](), [databases](), [mcp](), [on-prem](), [orchestration](), [passwords](), [secrets](), [security](), [servers](), [services](), [standards](), [systems]() ### AI overview The article argues that autonomous AI agents operating across production cloud and on-premises infrastructure do not fit legacy identity models built for humans and simple service accounts. It presents the Teleport Agentic Identity Framework as a standards-driven approach to unified cryptographic identity for securing agentic AI at scale. ### Source excerpt Deploy AI agents securely with the Teleport Agentic Identity Framework, a standards driven approach to cryptographic, unified identity for agentic AI at scale. ## Gremlin Release Roundup 2025: Reliability across AI, on-prem, and applications DevFeed: [Gremlin Release Roundup 2025: Reliability across AI, on-prem, and applications]() Original publisher: [Read original article]() Author: Andre Newman Published: 2025-12-15T00:00:00Z Content type: release Language: en Sources: [Gremlin Blog]() Topics: [on-prem](), [Failure Flags](), [experiments](), [Artificial Intelligence](), [MCP Server](), [telemetry](), [SRE]() Tags: [2025](), [ai](), [analysis](), [experiments](), [failure-flags](), [features](), [gremlin](), [mcp](), [mcp-server](), [no-code](), [on-prem](), [outages](), [release](), [releases](), [sre](), [telemetry]() ### AI overview Gremlin's 2025 release roundup describes improvements aimed at preventing outages and making reliability testing easier. Highlights include Reliability Intelligence for analyzing failures and recommending remediations, a Gremlin MCP server for querying environments through an LLM, new experiments and Failure Flags capabilities, expanded platform support, streamlined onboarding, and web UI refinements. ### Source excerpt This year's release roundup covers our new on-prem offering, new Failure Flags features, intelligent analysis of failed experiments, and much more. ## Introducing: Devstral 2 and Mistral Vibe CLI. DevFeed: [Introducing: Devstral 2 and Mistral Vibe CLI.]() Original publisher: [Read original article]() Published: 2025-12-09T12:00:00Z Content type: news Language: en Sources: [Mistral AI Blog]() Topics: [Artificial Intelligence](), [coding](), [Large Language Model](), [Open Source](), [Automation](), [GitHub Copilot CLI](), [Transformer](), [Command-line interface](), [context window](), [Terminal](), [Fine-tuning](), [on-prem]() Tags: [ai](), [ai-assistants](), [automation](), [autonomous-agents](), [claude](), [cli](), [code](), [coding](), [context-window](), [deepseek](), [fine-tuning](), [hardware](), [models](), [on-prem](), [open-source](), [terminal]() ### AI overview Mistral introduces Devstral 2, Devstral Small 2, and the Mistral Vibe CLI. The open coding models target autonomous software engineering, with deployment options spanning APIs, local consumer hardware, and on-premises environments. Devstral 2 supports a 256K context window, codebase-wide changes, failure recovery, and fine-tuning, while Mistral Vibe provides terminal-based code automation. ### Source excerpt The most powerful AI platform for enterprises. Customize, fine-tune, and deploy AI assistants, autonomous agents, and multimodal AI with open models. ## How Merkle Science fights crypto crime at scale with ClickHouse Cloud DevFeed: [How Merkle Science fights crypto crime at scale with ClickHouse Cloud]() Original publisher: [Read original article]() Author: Akshay Gupta, Lead Data Engineer, and Priyanshu Sehgal, Sr. Data Engineer Published: 2025-11-13T09:30:52Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [Cloud](), [Data Infrastructure](), [Blockchain](), [threat detection](), [real-time](), [on-prem]() Tags: [blockchain](), [clickhouse](), [cloud](), [data-infrastructure](), [infra](), [on-prem](), [real-time](), [threat-detection]() ### AI overview Merkle Science uses ClickHouse as a core part of its blockchain analytics and predictive risk platform for detecting, tracing, and preventing illicit activity. The company ingests about 1.5 terabytes of data weekly and runs more than 18 million queries, relying on ClickHouse for transaction monitoring, wallet attribution, cross-chain forensics, and real-time threat detection. The article describes its migration from self-managed ClickHouse infrastructure to ClickHouse Cloud to simplify operations and support faster scaling. ### Source excerpt "Even if data increases by 4x or 5x in the next year, we literally don't have to worry about it. We've got the architecture right, the stack right, and the right platform at the end of the day." - Akshay Gupta, Lead Data Engineer [Next page]()