2026-06-10 14:27
🚀 At DigitalOcean, we focus on high-performance infrastructure for AI, particularly frontier Large Language Models (LLMs) on AMD GPUs. Our approach emphasizes that peak inference speed is influenced by model architecture and runtime execution, alongside hardware. This "performance alpha" highlights the benefits of specialized inference engineering. Recent collaborations with Wafer demonstrated significant throughput improvements: Kimi 2.5 saw an 11.33x speedup, while DeepSeek V3.2 achieved a...
Source: DigitalOcean Blog
Emilio Andere
2026-06-09 22:58
🚀 Earlier this year, we needed to hire engineers quickly for a product launch. We revamped our interview process to focus on real-world skills instead of outdated methods. 💻 Candidates participated in a hands-on, three-hour build session, utilizing AI tools to prototype solutions. This approach allowed us to evaluate their decision-making and collaboration skills. 🤝 After coding, we engaged in discussions about design choices and real-world challenges, providing a platform for candidates to...
Source: DigitalOcean Blog
Janet Harrah
2026-06-04 19:52
🚀 Teams often struggle not due to a lack of good models, but because their routing policies falter under real conditions. DigitalOcean's Model Evaluations, now in Public Preview, can help assess models and routing strategies effectively. This tool enables evaluations across cost, latency, and output quality. In the guide, you’ll find steps to compare a single frontier model, an Inference Router, and a Bring Your Own Model (BYOM) on a legal assistant use case. Learn how to set up, run, and...
Source: DigitalOcean Blog
Sathish Jothikumar
2026-06-03 19:38
🚀 Deploy 2026 brought together developers, startups, and partners in San Francisco to discuss building and scaling AI products. DigitalOcean unveiled the AI-Native Cloud, featuring over 15 product launches, including the Inference Router. Key sponsors included NVIDIA and MongoDB, while companies like Hippocratic AI showcased their journey. The event highlighted DigitalOcean's culture of ownership, as team members shared insights on customer collaboration and product development. Explore...
Source: DigitalOcean Blog
Sujatha R
2026-06-03 19:23
Unlock the potential of AI-native applications with DigitalOcean's new Data & Learning Layer! 🌐 This platform integrates structured, vector, and retrieval layers, streamlining development for real-time multimodal pipelines and enterprise knowledge bases. Key features include: - Managed PostgreSQL & MySQL for structured data. - Knowledge Bases for seamless unstructured data management. - Managed Weaviate for vector search capabilities. These tools work together, reducing latency and costs...
Source: DigitalOcean Blog
Spoorthi Rao Nimmala
2026-06-02 18:29
NVIDIA and DigitalOcean recently discussed the evolution of open-source AI at the "Open by Design" session. They emphasized the need for commitment to open models, like NVIDIA's Nemotron, to ensure ongoing improvements for developers. Evaluation standards for AI applications remain a challenge, impacting developers’ confidence. The session also highlighted the importance of sub-agent workflows and effective token economics in scaling AI systems. For more insights, watch the full session! 🎥✨...
Source: DigitalOcean Blog
Jess Lulka
2026-06-01 19:30
🌐 Inference demand is rising rapidly, projected to dominate AI compute by 2030. A significant portion of compute costs is avoidable due to redundant work in systems. 🔍 DigitalOcean's prefix-aware routing addresses this inefficiency, significantly reducing unnecessary computations. By optimizing GPU performance and caching, they enhance cost-effectiveness without hardware constraints. 🚀 Upcoming improvements in Serverless Inference will make these benefits accessible to all users, ensuring...
Source: DigitalOcean Blog
Simon Mo, CEO of Inferact
2026-06-01 18:44
🚀 **Introducing DigitalOcean Serverless Inference!** This API-first platform simplifies AI model deployment at scale. It supports 30+ foundation models across various modalities through a single API key. Key features include automatic scaling, intelligent routing, and built-in tools for efficient model management. Get started easily and pay only for what you use! #DigitalOcean #AI #Serverless #MachineLearning #TechInnovation
Source: DigitalOcean Blog
smehta
2026-05-29 21:30
At the Deploy 2026 conference, I moderated a panel with AI founders discussing what differentiates successful AI products from demos. Key insights included the importance of measuring agent performance and ensuring reliability. Founders like Angela Hoover from Andi AI and Hovsep Seraydarian from LawVo emphasized that human oversight is essential in high-stakes fields. They also highlighted the challenges of model selection in a rapidly evolving landscape, noting that execution and...
Source: DigitalOcean Blog
Dinesh Murthy
2026-05-28 21:02
🚀 Exciting news for developers! DigitalOcean's Inference Router is now available in OpenCode, addressing the costly issue of using a single model for all tasks. This dynamic router intelligently directs requests to the most suitable model, optimizing costs and ensuring efficient resource use. To get started, simply connect your DigitalOcean account in OpenCode and select your Inference Routers. Explore the future of cost-effective AI model routing! 🌐💻 #OpenCode #DigitalOcean #AI...
Source: DigitalOcean Blog
Musa Malik
2026-05-27 17:43
🚀 Exciting news from Deploy 2026! DigitalOcean has launched Batch Inference on its AI-Native Cloud, designed for efficient high-volume workloads. This feature allows developers to process up to 100k requests asynchronously at reduced costs, streamlining tasks like data transformation and content generation. With a unified API for OpenAI and Anthropic, managing multiple models is simpler than ever. Batch Inference also helps bypass rate limits, ensuring smoother operations. Explore how this...
Source: DigitalOcean Blog
smehta
2026-05-22 18:02
🚀 Request-based autoscaling is now live on DigitalOcean App Platform! Apps can automatically scale based on live HTTP traffic signals like requests per second and P95 response latency. This ensures your infrastructure reacts promptly to user demand. Now available for both shared and dedicated CPU instances, it allows all users to benefit from responsive scaling without needing a plan upgrade. 🔍 Use the Insights tab to understand traffic patterns and configure your autoscaling rules...
Source: DigitalOcean Blog
Greeshma Pillai
2026-05-20 14:57
🚀 Exciting news from DigitalOcean! They have launched the Inference Router, designed to optimize model selection for AI tasks. Instead of relying on a single model, this router intelligently routes requests to the most suitable model based on cost, latency, or quality. The Inference Router utilizes a 30B Mixture-of-Experts model, achieving impressive accuracy in task detection. With easy setup via a single line of code, developers can enhance their workflows without the burden of manual...
Source: DigitalOcean Blog
Adil Hafeez
2026-05-13 16:45
Unlocking the potential of AI starts with the right infrastructure. 🌐 DigitalOcean emphasizes that while everyone has access to similar models, success lies in the surrounding infrastructure—routing logic, data pipelines, and scalable solutions without code rewrites. Their recent session showcased how teams can move seamlessly through serverless, dedicated, and routed setups, maximizing efficiency and reducing costs. 💡 Explore the full capabilities of DigitalOcean's AI platform! #AI...
Source: DigitalOcean Blog
Amit Jotwani
2026-04-28 19:14
🚀 DigitalOcean has introduced its AI-Native Cloud, addressing the growing challenges in AI workloads. The shift in AI infrastructure highlights inference as the new focus, with reasoning models and autonomous agents taking center stage. This full-stack solution simplifies development by reducing complexity, allowing developers to concentrate on building rather than integrating. Key features include the Inference Router, dedicated GPU infrastructure, and a wide range of models available for...
Source: DigitalOcean Blog
Paddy Srinivasan
2026-04-28 09:00
🚀 We are excited to announce the launch of DeepSeek V3.2, MiniMax-M2.5, and Qwen 3.5 397B on DigitalOcean Serverless Inference. These models achieve leading performance, with DeepSeek V3.2 delivering 230 output tokens per second and a sub-1-second time to first token for 10,000 input tokens. Fast inference is crucial for modern AI applications, ensuring a seamless user experience. Our optimizations enable businesses to lower costs and maintain high performance. Explore the benchmarks and see...
Source: DigitalOcean Blog
Bhaskar Dutt
2026-04-25 02:51
🚀 DigitalOcean has introduced Dedicated Inference, a managed LLM hosting service designed for teams needing reliable, high-performance inference on dedicated GPUs. It simplifies deployment by handling the orchestration, while users maintain control over model selection and scaling options. This service targets organizations with consistent inference demands, offering predictable costs and performance. Key features include public and private endpoints, Kubernetes-native orchestration, and...
Source: DigitalOcean Blog
dgupta
2026-04-23 19:29
🌐 DigitalOcean is advancing its cloud infrastructure with Project Poseidon, aiming for zero-downtime reliability. This new system uses Machine Learning and Generative AI to identify "at-risk" nodes before server crashes occur. By shifting from reactive monitoring to proactive measures, it enhances operational efficiency. The tiered approach filters out 98% of irrelevant data, focusing only on critical signals. Poseidon is designed to evolve continually, ensuring it adapts to new hardware and...
Source: DigitalOcean Blog
Sartaj
2026-04-23 09:15
📊 DigitalOcean has redefined its approach to measuring availability by shifting from an incident-based metric to Service Level Indicators (SLIs). Initially, availability numbers fluctuated between 99.5% and 99.9%, often not reflecting true customer experience. The new metric, consistently above 99.95%, better represents actual platform performance. Key changes include separating measurements into Control Plane and Data Plane, allowing for more accurate assessments of service health. This...
Source: DigitalOcean Blog
Miguel Carrera
2026-04-22 15:56
Navigating the complexities of Large Language Model (LLM) inference involves understanding the "trilemma" of throughput, latency, and cost. Scaling LLMs isn't as simple as adding more servers; it requires careful optimization. Key cost factors include hardware expenses, electricity, and specialized labor. Each decision impacts the balance between performance and expenses. ⚖️ This comprehensive guide offers insights on optimizing for either throughput or latency, depending on your use case....
Source: DigitalOcean Blog
Balaji Varadarajan
2026-04-21 20:10
The landscape of model deployment is evolving rapidly, with weights now exceeding 700GB and parameters reaching trillions. 🧠 Optimizing storage architecture is crucial to combat "Data Gravity," which can slow down GPU performance and increase operational costs. High-bandwidth storage solutions can significantly reduce deployment latency, impacting overall efficiency. 📈 Cloud providers that offer specialized GPU and storage combinations are essential for managing these large models...
Source: DigitalOcean Blog
Brett Snyder
2026-04-17 20:10
DigitalOcean addresses the growing need for a robust memory layer in AI applications with its Inference Cloud. 🌩️ As AI transitions to production-grade models, the absence of persistent memory can lead to issues like loss of long-term recall and workflow vulnerabilities. DigitalOcean Managed Databases, including PostgreSQL and MongoDB, serve as foundational memory layers to enhance stateful AI applications. This shift to the inference cloud allows developers to focus on building intelligent...
Source: DigitalOcean Blog
Joe Keegan
2026-04-15 19:03
Load balancing for Large Language Models (LLMs) differs significantly from traditional services due to prompt caching. Efficient routing strategies are essential to maximize cache effectiveness and minimize latency. The article explores specialized routers that enhance performance while addressing the limitations of standard load balancing methods. Various inference engines like vLLM and TensorRT streamline the process, allowing for efficient handling of diverse workloads. For optimal...
Source: DigitalOcean Blog
Mohammad Ashar Khan
2026-04-13 16:59
🚀 At DigitalOcean, we've prioritized documentation by creating an AI assistant that helps developers find answers quickly. This tool allows users to ask questions in plain language and receive accurate, actionable responses. Through extensive testing and validation, we improved the assistant's reliability and performance, ensuring it can effectively guide users. Key components include a robust architecture on the Gradient AI Platform and a focus on metrics for continuous improvement. Explore...
Source: DigitalOcean Blog
Anna Lushnikova
2026-04-07 19:11
🌐 Prompt caching optimizes inference requests by reusing computed KV states, enhancing efficiency and reducing costs. However, as systems scale with multiple replicas, cache hit rates drop, posing challenges. 🔄 Implementing session affinity can improve performance by routing requests to the same replica, preserving cached data. 📊 Effective architectural strategies, including tiered caching and proper prompt structure, can significantly boost efficiency. #PromptCaching #AIInference...
Source: DigitalOcean Blog
Andrew Dugan
2026-04-03 15:44
Navigating the cloud AI platform landscape can be challenging. 🖥️ Many developers face significant delays due to unclear documentation, fragmented workflows, and complex setups. Tasks that should take minutes can stretch into hours, impacting productivity and innovation. ⏳ Key factors include the real cost of developer experience, Time-to-First-Value (TTFV), and the hidden complexities of scaling. A seamless integration of tools is essential for faster iterations and successful deployments....
Source: DigitalOcean Blog
Shaoni Mukherjee
2026-04-02 21:30
AI is transforming software development, yet deploying it remains complex. The challenge lies in integration, where various systems must work together seamlessly. Fragmented setups lead to increased developer effort in maintaining glue code, diverting focus from product features. The article discusses the advantages of a vertically integrated cloud model over a neocloud-hyperscaler combo, highlighting reduced complexity and operational costs. By minimizing integration points, developers can...
Source: DigitalOcean Blog
James Skelton
2026-04-02 12:30
🚀 DigitalOcean has acquired Katanemo Labs to enhance its Agentic Inference Cloud. This move aims to simplify the operational layer of agentic systems. 📊 The acquisition addresses the challenge many developers face in transitioning from prototype to production. With observability as a key focus, DigitalOcean is set to deliver essential AI building blocks. 🔍 Katanemo's innovative data plane and observability research will streamline production execution and enhance agent performance. 📅 Join us...
Source: DigitalOcean Blog
Vinay Kumar, DigitalOcean Chief Product & Technology Officer
2026-04-01 20:09
🚀 Exciting news! Arcee AI's Trinity Large-Thinking is now in Public Preview on DigitalOcean’s Agentic Inference Cloud. This model allows developers to run advanced reasoning workloads effortlessly, without managing infrastructure. Trinity Large-Thinking is built for real-world applications, featuring integrated systems for enhanced performance. Key benefits include serverless access, affordable pricing, and full model control via Apache 2.0 licensing. Start your advanced reasoning journey...
Source: DigitalOcean Blog
DigitalOcean
2026-04-01 14:46
🚀 Exciting news for DigitalOcean users! DigitalOcean has launched Cloud Security Posture Management (CSPM) to enhance security across cloud infrastructures. This agentless solution provides in-dashboard visibility, helping teams detect and fix risks without needing external tools. CSPM continuously assesses resources like Droplets and Databases, offering unlimited free scans for all customers. Premium plans unlock advanced rules and automation features. Start your scan today and keep your...
Source: DigitalOcean Blog
Grace Morgan
2026-03-27 19:27
At NVIDIA GTC 2026, a significant shift in AI was highlighted: we are now in the era of production inference. 💻✨ The focus is on operational aspects like latency, reliability, and cost-efficiency, not just chip performance. This change is crucial as AI inference transforms innovation into real products and customer experiences. DigitalOcean introduced a new data center for AI inference and tools to streamline the deployment of AI agents. 🚀 Over 43,000 deployments of OpenClaw demonstrate...
Source: DigitalOcean Blog
Paddy Srinivasan
2026-03-24 02:40
DigitalOcean is celebrating a successful year in India, with significant growth since its expansion into Hyderabad. The team has doubled in size to over 370 employees, contributing to the development of innovative AI solutions. 🌟 The India team plays a crucial role in building DigitalOcean’s Agentic Inference Cloud, launching products like GPU Droplets and Gradient AI. This collaboration emphasizes simplicity and speed in delivering cloud services. DigitalOcean is committed to fostering a...
Source: DigitalOcean Blog
Sujatha R
2026-03-23 19:30
🔐 DigitalOcean has announced a significant upgrade to its security model with user-specific access keys for Functions. This new approach enhances security by shifting access control from a shared model to individual user identities. This means that when a team member leaves, their access is automatically revoked, minimizing disruptions. Teams can now create multiple keys per namespace, improve accountability, and set expiration times for keys. For those using the DigitalOcean Functions API,...
Source: DigitalOcean Blog
Amulya Tomer
2026-03-19 22:13
🚀 Exciting news for DigitalOcean customers! NVIDIA Dynamo 1.0, launched at NVIDIA GTC, is now available, offering a 7x increase in inference performance on NVIDIA GB200 NVL systems. This boosts efficiency while reducing costs. 💰 DigitalOcean's collaboration with NVIDIA has already provided a 67% cost saving for clients like Workato. The new Dynamo allows for seamless deployment as a container image on DigitalOcean Kubernetes. Learn more about optimizing your AI workflows! #NVIDIA...
Source: DigitalOcean Blog
Waverly Swinton
2026-03-17 19:25
🔍 **Understanding Prompt Caching for AI Models** Large Language Models (LLMs) are key in modern AI, but token costs can escalate quickly. With prompt caching, repeated prompt segments can be reused, leading to significant reductions in both latency and costs. Key points include: - **How it Works**: Identical prompt segments are stored and reused across requests. - **Benefits**: Reduces costs by up to 90% and improves processing speed. - **Use Cases**: Effective for applications like ChatGPT...
Source: DigitalOcean Blog
Satyam Namdeo
2026-03-16 20:35
🚀 Exciting updates from DigitalOcean at NVIDIA GTC 2026! DigitalOcean is enhancing its AI capabilities by launching an "AI Factory" aimed at supporting developers in deploying autonomous agents with ease. The partnership with NVIDIA is set to simplify the deployment process and reduce operational costs. 🌐 With the launch of the Richmond data center, equipped with advanced NVIDIA systems, DigitalOcean is positioned to deliver high-performance cloud services tailored for AI. 💡 Builders can now...
Source: DigitalOcean Blog
Vinay Kumar, DigitalOcean Chief Product & Technology Officer
2026-03-16 14:00
🚀 Exciting news for developers! DigitalOcean has launched App Platform Skills, a collection of open-source, AI-native playbooks designed to enhance AI coding assistants. These Skills bridge the gap between coding and deploying applications by injecting up-to-date DigitalOcean knowledge into AI tools. This enables better deployment models and operational patterns. With just one command, AI assistants gain access to 12 specialized skills, covering everything from app design to troubleshooting....
Source: DigitalOcean Blog
Bikram Gupta
2026-03-13 15:49
🚀 As Cloudways scaled to manage over 90,000 servers, the challenge of support requests grew. To address this, they developed an AI-powered Site Reliability Engineer, Cloudways Copilot. 🤖 This tool offers automated insights and troubleshooting, enhancing response times and consistency compared to human agents. 🔍 The AI SRE Agent monitors systems, detects issues, and provides users with detailed diagnosis and remediation steps. 💡 Cloudways leveraged the DigitalOcean Gradient™ AI Platform for...
Source: DigitalOcean Blog
Najmus Saqib
2026-03-05 21:21
🚀 Exciting news for .NET developers! DigitalOcean App Platform now supports native .NET buildpacks. You can deploy .NET applications directly from your Git repository—no Dockerfiles needed. Key benefits include zero configuration, multi-language support for C#, F#, and Visual Basic, and automatic SDK management for .NET versions 8.0, 9.0, and 10.0. Get started easily via the Control Panel, CLI, or API. #DotNet #DigitalOcean #AppPlatform #CloudDevelopment #DevOps
Source: DigitalOcean Blog
Bikram Gupta
2026-03-03 08:34
🚀 Check out the latest insights from our recent article! It covers key points on current trends and developments in the industry. The content provides valuable information for professionals looking to stay updated and informed. Don't miss out on these important takeaways! 📈 #IndustryTrends #StayInformed #ProfessionalDevelopment
Source: DigitalOcean Blog
DigitalOcean