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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

Mastering Microsoft Azure Certification Preparation with Reliable Study Resources

The demand for cloud computing professionals has surged dramatically in recent years, and Microsoft Azure stands out as one of the leading cloud platforms globally. Whether you are a beginner stepping into the IT world or an experienced professional aiming to validate your skills, Azure certifications like AZ-900 and AZ-500 play a crucial role in enhancing your career prospects. Preparing for these exams requires not only dedication but also access to high-quality study materials and reliable practice resources. This is where platforms like Exam-Labs.com become valuable for candidates seeking structured and effective preparation strategies.

AZ-500 and DP-203 Certification Path for Microsoft Azure Security and Data Engineering Careers

Microsoft Azure has become one of the leading cloud platforms in the world, powering businesses of all sizes. As organizations continue to migrate to cloud infrastructure, the demand for certified Azure professionals is increasing rapidly. Among the most valuable certifications in this ecosystem are AZ-500 (Azure Security Engineer Associate) and DP-203 (Azure Data Engineer Associate).

Self-service infrastructure promises speed, but without control, it creates chaos.

In this video, we break down what self-service infrastructure with guardrails actually means and why modern platform teams are adopting it to scale safely. Learn how developers can move faster without waiting on approvals, while organizations maintain control through governance, automation, and policy-based guardrails. We cover: This approach is redefining how infrastructure is delivered across DevOps, platform engineering, and cloud environments.

High-Performance Range Queries in PostgreSQL: Overcoming Bottlenecks in AWS Aurora

Short Summary: PostgreSQL can slow down when range queries and frequent data updates rely on the same indexes. This guide shows how to spot the problem and use Devart tools to reduce B-Tree index conflicts, improve query plans, and manage bi-weekly data updates in AWS Aurora.

Migrating from MySQL to PostgreSQL: Performance and Replication Best Practices

Summary: Today, many teams are moving from MySQL to PostgreSQL as they update their database systems and plan for future growth. However, too often, there is extra work after the migration: for example checking that tables and constraints were copied correctly, tuning performance, and confirming that replication works properly. Devart’s PostgreSQL tools help DBAs with these tasks through features like Schema Compare, Data Compare, and other tools that help review and manage PostgreSQL databases.

AWS Proton End of Life: What Teams Need to Know and Do Before October 2026

AWS Proton is reaching end of life. If you're reading this, you probably just found out — either from the AWS console banner, your account manager, or a panicked Slack message from someone on your platform team. Here's what you need to know: your infrastructure is safe, but the tool you use to manage it is going away. You have until October 7, 2026 to find a replacement. That sounds like plenty of time. It isn't.

The 4 Golden Signals of Monitoring Explained

As a team, we have spent many years troubleshooting performance problems in production systems. Applications have become so complex that you need a standard methodology to understand performance. Our approach to this problem is called the Golden Signals. By measuring these signals and paying very close attention to these four key metrics, providers can simplify even the most complex systems into an understandable corpus of services and systems.

A Tour of Cortex

Get a guided tour of Cortex, the Engineering Operations Platform built to help teams improve operational maturity and reduce developer friction. This video covers the core features of Cortex: the Catalog, Scorecards, Initiatives, engineering metrics, and Workflows. Each one maps to the three things any great EngOps platform needs to do: provide clarity, drive improvement, and remove friction. Ready to see it in action? Visit our website: cortex.io Book a custom demo: cortex.io/demo.

AI Cost Management: How To Track, Allocate And Optimize AI Spend

AI cost management is the practice of tracking, allocating, and optimizing the cloud infrastructure costs tied to building, running, and scaling AI workloads. It differs from traditional cloud cost optimization because AI infrastructure behaves differently at every layer of the stack. The biggest problem isn’t overspending. It’s that most organizations can’t see where their AI spending is going.