Operations | Monitoring | ITSM | DevOps | Cloud

jfrog

FrogML SDK: the Gateway to Model Governance

Aug 19, 2025 By Rami Pinku In JFrog
Data-driven decisions are critical. And to support high-stakes decision-making – from fraud detection in credit card transactions to demand forecasting in retail – organizations are increasingly relying on complex models. According to McKinsey, 78% of organizations report using AI in at least one business function, highlighting just how embedded AI and ML models have become in operational and strategic decision-making.
Read Post
cloudzero

Amazon SageMaker Pricing Guide: 2025 Costs (And Savings)

Aug 15, 2025 By CloudZero In CloudZero
Amazon SageMaker makes it easy to prepare data for machine learning (ML) and then train, deploy, and modify ML models. SageMaker is a fully managed service that automates much of the ML lifecycle. So, if you want a single partner to help you through all stages of your Artificial Intelligence (AI) lifecycle, SageMaker might be the answer. Perhaps more important for this post is the promise that Amazon SageMaker can reduce your machine learning model costs. But does SageMaker pricing reflect this?
Read Post
Optimizing Legacy ML Systems with Real-World DevOps Practices

Optimizing Legacy ML Systems with Real-World DevOps Practices

Aug 6, 2025 By OpsMatters In OpsMatters
We chose to feature this article because it reflects exactly what OpsMatters stands for: practitioners solving real problems with practical DevOps thinking. When we came across Ashish's detailed breakdown of his experience modernizing a complex ML environment, it stood out for its clarity and actionable insights. We reached out to him to learn more about the work behind this case study, and with his permission, we are sharing it here so the broader community can benefit from these lessons in observability, cost optimization, and real-world DevOps execution.
Read Post
canonical

Canonical announces Charmed Feast: A production-grade feature store for your open source MLOps stack

Jul 10, 2025 By Canonical In Canonical
July 10, 2025: Today, Canonical announced the release of Charmed Feast, an enterprise solution for feature management with seamless integration with Charmed Kubeflow, Canonical’s distribution of the popular open source MLOps platform. Charmed Feast provides the full breadth of the upstream Feast capabilities, adding multi-cloud capabilities, and comprehensive support.
Read Post
circleci

Automating machine learning security checks using CI/CD

Jun 13, 2025 By Najia Gul In CircleCI
Machine learning (ML) pipelines are increasingly being treated like software; built, tested, deployed, and monitored using automated tooling. But while infrastructure as code and microservices have matured with security best practices, ML systems often lag behind. The truth is, your ML pipeline is part of your software supply chain and it is vulnerable.
Read Post
observo ai

Harnessing Machine Learning for Advanced Threat Detection with Observo AI

Jun 10, 2025 By Edward Johns In Observo.ai
Cyber threats are growing more cunning every day, with attackers even tapping into artificial intelligence to outsmart traditional defenses. Organizations face a flood of security data—logs, alerts, and telemetry—making it nearly impossible to sift through. How do you spot the real dangers amid all that noise? Observo AI’s ML-Powered Threat Insights offers a game-changing answer.
Read Post
observo ai

Taming Telemetry Data Sprawl: How ML Reduces Data 2X Better

May 28, 2025 By Bryan Turriff In Observo.ai
Security and DevOps teams are drowning in data. Fueled by the explosion of cloud-native architectures, microservices, and accelerated software development cycles driven by AI, telemetry volumes are growing faster than ever. For most organizations, security and observability data is now doubling every 2–3 years. At the same time, most of the tools used to analyze that data—SIEMs, log analytics platforms, and cloud-native observability tools—charge based on ingestion volume.
Read Post
influxdata

Forecasting with InfluxDB 3 and HuggingFace

May 20, 2025 By Anais Dotis-Georgiou In InfluxData
Machine learning models must do more than make accurate predictions; they also need to adapt as the world around them changes. In real-world systems, data distributions shift due to seasonality, equipment wear, user behavior changes, or other external forces. If your models can’t keep up, the result is poor predictions. This can lead to outages, inefficiencies, or missed opportunities. That’s why forecasting systems need to be monitored and resilient, not just accurate.
Read Post
Best VPS for Machine Learning

Best VPS for Machine Learning

Apr 16, 2025 By OpsMatters In OpsMatters
When it comes to machine learning, choosing the right Virtual Private Server (VPS) can significantly impact your project's performance, scalability, and cost-effectiveness. A VPS provides dedicated resources that can handle the intensive computational tasks associated with training machine learning models. Here, we explore the best cheap GPU VPS options for machine learning, highlighting the importance of GPUs and introducing Cloudzy as a leading choice.
Read Post
canonical

Announcing Charmed Kubeflow 1.10

Apr 8, 2025 By Stefano Fioravanzo In Canonical
We are thrilled to announce the release of Charmed Kubeflow 1.10, Canonical’s latest update to the widely-adopted open source MLOps platform. This release integrates significant improvements from the upstream Kubeflow 1.10 project, while also bringing a suite of additional capabilities targeted towards enterprise deployments. Charmed Kubeflow 1.10 empowers machine learning practitioners and teams to operationalize machine learning workflows more efficiently, securely, and seamlessly than ever.
Read Post

Copyright © 2026 OpsMatters™. All rights reserved.