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AWS vs Azure vs Google Cloud: What’s the best cloud platform?

Openxcell

Millions of dollars are spent each month on public cloud companies like Amazon Web Services, Microsoft Azure, and Google Cloud by companies of all sizes. These three cloud services are the most secure, adaptable, and dependable cloud services that dominate the public cloud market.

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Cybersecurity Snapshot: Cyber Agencies Offer Secure AI Tips, while Stanford Issues In-Depth AI Trends Analysis, Including of AI Security

Tenable

Part 1 (NTIA) 4 - CIS updates Benchmarks for Cisco, Google, Microsoft, VMware products The Center for Internet Security has announced the latest batch of updates for its widely-used CIS Benchmarks, including new secure-configuration recommendations for Cisco IOS, Google Cloud Platform, Windows Server and VMware ESXi.

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Foote Partners: bonus disparities reveal tech skills most in demand in Q3

CIO

These included metadata design and development, quantitative analysis, regression analysis, continuous integration, data analytics, data strategy, identity and access management, machine learning, natural language processing, and more.

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14 in-demand cloud roles companies are hiring for

CIO

Skills: Knowledge and skills for this role include an understanding of implementation and integration, security, configuration, and knowledge of popular cloud software tools such as Azure, AWS, GCP, Exchange, and Office 365. Role growth: 27% of companies have added cloud systems admin roles as part of their cloud investments.

Cloud 316
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Why Lacework is a Leader in the KuppingerCole Leadership Compass for CNAPP

Lacework

KuppingerCole Analysts AG Leadership Compass: Cloud-Native Application Protection Platforms (CNAPP), 2024 The report highlighted several capabilities CNAPPs should have: Cover and provide visibility of the major cloud services (AWS, Google Cloud, Microsoft Azure, etc.) popular security and incident management tools.

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Contrast launches its security observability platform

TechCrunch

The idea here is to offer developers a single pane of glass to manage an application’s security across its lifecycle, combined with real-time analysis and reporting, as well as remediation tools. “We’re focused on securing all that code that businesses are writing for both automation and digital transformation.”

DevOps 161
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MLOps: Methods and Tools of DevOps for Machine Learning

Altexsoft

It facilitates collaboration between a data science team and IT professionals, and thus combines skills, techniques, and tools used in data engineering, machine learning, and DevOps — a predecessor of MLOps in the world of software development. MLOps lies at the confluence of ML, data engineering, and DevOps. MLOps vs DevOps.