InfoQ Homepage DevOps Content on InfoQ
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Making Sense of Application Security
Adib Saikali provides a roadmap for application developers and architects to master application security, identifying the security skills needed as an application developer.
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Prod Lessons - Deployment Validation and Graceful Degradation
Anika Mukherji discusses lessons learned in production at Pinterest: deployment validation framework and product-informed graceful degradation, preventing hundreds of outages.
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Cloud-Native Application Security: Your Attack Surface Just Got Bigger
Brian Vermeer shows common threats, vulnerabilities, and misconfiguration including the recently disclosed issues in Log4j, including actionable remediation and best practices.
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ML Panel: "ML in Production - What's Next?"
The panelists discuss lessons learned with putting ML systems into production, what is working and what is not working, building ML teams, dealing with large datasets, governance and ethics/privacy.
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Full Stack Dart
Chris Swan discusses using a stack of Dart, where Flutter developers can use the same language to build the services behind their apps.
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Unified MLOps: Feature Stores and Model Deployment
Monte Zweben proposes a whole new approach to MLOps that allows to scale models without increasing latency by merging a database, a feature store, and machine learning.
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Reproducible Development with Containers
Avdi Grimm describes the future of development, which is already here. Get a tour of a devcontainer, and contrast it with a deployment container.
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Panel: Secure Systems
The panelists discuss the security for the software supply chain and software security risk measurement.
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MLOps: the Most Important Piece in the Enterprise AI Puzzle
Francesca Lazzeri overviews the latest MLOps technologies and principles that data scientists and ML engineers can apply to their machine learning processes.
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Developing and Deploying ML across Teams with MLOps Automation Tool
Fabio Grätz and Thomas Wollmann discuss the MLOps Automation tool, and how it can be used to perform DevOps tasks on ML across teams.
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Iterating on Models on Operating ML
Monte Zweben and Roland Meertens discuss the challenges in building, maintaining, and operating machine learning models.
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One Ring -3 to Secure Them All: Computing with Hardware Enclaves
Aaron Bedra explores the most widely available options and their usage in IoT and cloud, discussing design trade-offs, security, and performance.
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Close the Information Gap: How to Succeed at Analytics in the Cloud
Download this guide to better understand what a data-driven business looks like and the dangers of having an information gap across data that's distributed, diverse, and dynamic. Download Now.
