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@faun shared a link, 3 months, 2 weeks ago
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v1.34: Pod Replacement Policy for Jobs Goes GA

ThePod replacement policyin Kubernetes v1.34 just hit GA. Jobs can now hold off on spinning up new Pods until the old ones arefullygone. No more duplicates per index. No more blowing through quotas or stalling schedulers—big win for workloads like ML training. System shift:This rewires how Jobs hand.. read more  

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Reduce Cloud Cross-Zone Data Transfer Costs with Kubernetes 1.33 trafficDistribution

Kubernetes 1.33 drops a new traffic policy that addszone-local routing. With it, kube-proxy now prefers endpoints in the same availability zone. Translation: less cross-AZ chatter, fewer surprise charges. On AWS, that can chop the usual $0.02/GB cross-AZ fee by up to 85%—especially in EKS clusters j.. read more  

Reduce Cloud Cross-Zone Data Transfer Costs with Kubernetes 1.33 trafficDistribution
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@faun shared a link, 3 months, 2 weeks ago
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v1.34: PSI Metrics for Graduates to Beta

Kubernetes v1.34 bumpsPressure Stall Information (PSI) metricsto Beta. Now kubelets expose kernel-level resource pressure—CPU, memory, and I/O—through the Summary API and Prometheus. Instead of just tracking how much a resource gets used, PSI shows how often workloads get throttled or blocked. That .. read more  

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@anjali shared a link, 3 months, 3 weeks ago
Customer Marketing Manager, Last9

Kubernetes Monitoring Metrics That Improve Cluster Reliability

Understand Kubernetes monitoring metrics that help detect issues early, improve reliability, and keep your cluster performing at its best.

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@laura_garcia shared a post, 3 months, 3 weeks ago
Software Developer, RELIANOID

🚀 Strengthening Europe’s Cybersecurity in Space

Just in case you missed it last month: The European Space Agency (ESA) has launched its brand-new Cybersecurity Operations Center (C-SOC) to safeguard satellites, mission control systems, and digital assets against growing cyber threats. 🌍 In today’s space-driven world, initiatives like this — suppo..

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@laura_garcia shared a post, 3 months, 3 weeks ago
Software Developer, RELIANOID

🔐 Cybersecurity Fundamentals: Defensive, Offensive & Hybrid Approaches 🔐

Cybersecurity isn’t just about deploying tools — it’s about knowing how and when to use the right strategies. Defensive security focuses on prevention with technologies like firewalls, antivirus, access control, and system hardening to reduce exposure. Offensive security takes the attacker’s perspec..

Cibersecurity concepts diagram RELIANOID
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@anjali shared a link, 3 months, 3 weeks ago
Customer Marketing Manager, Last9

What is APM Tracing?

Understand APM tracing to see how a request moves through services, helping you spot delays, errors, and bottlenecks quickly.

apm tracing
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@laura_garcia shared a post, 3 months, 3 weeks ago
Software Developer, RELIANOID

✨ In case you missed it ✨

DDoS attacks in 2025 are bigger, smarter, and easier to launch than ever before. From AI-driven attack strategies to IoT-based botnets, the threat landscape is evolving fast. Our latest blog explains what’s happening now — and how RELIANOID helps organizations stay resilient. 🔗 https://www.relianoid..

Blog DDoS Trends RELIANOID
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@laura_garcia shared a post, 3 months, 3 weeks ago
Software Developer, RELIANOID

SourceForge Favorite Award 🏆

We are proud to share that RELIANOID has been recognized with the SourceForge Favorite Award 🏆 This recognition is granted to only a handful of projects out of more than 500,000 open source projects hosted on SourceForge, based on downloads and user engagement. 👉 With nearly 20 million monthly users..

Sourceforge favorite RELIANOID
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@kkz7777 gave 🐾 to 🚀 RELIANOID is heading to Washington, DC! , 3 months, 3 weeks ago.
Vertex AI is Google Cloud’s end-to-end machine learning and generative AI platform, designed to help teams build, deploy, and operate AI systems reliably at scale. It unifies data preparation, model training, evaluation, deployment, and monitoring into a single managed environment, reducing operational complexity while supporting advanced AI workloads.

Vertex AI supports both custom models and foundation models, including Google’s Gemini model family. It enables organizations to fine-tune models, run large-scale inference, orchestrate agentic workflows, and integrate AI into production systems with strong security, governance, and observability controls.

The platform includes tools for AutoML, custom training with TensorFlow and PyTorch, managed pipelines, feature stores, vector search, and online and batch prediction. For generative AI use cases, Vertex AI provides APIs for text, image, code, multimodal generation, embeddings, and agent-based systems, including support for Model Context Protocol (MCP) integrations.

Built for enterprise environments, Vertex AI integrates deeply with Google Cloud services such as BigQuery, Cloud Storage, IAM, and VPC, enabling secure data access and compliance. It is widely used across industries like finance, healthcare, retail, and science for applications ranging from recommendation systems and forecasting to autonomous research agents and AI-powered products.