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

Why are AI Agents Superior to LLM #speedscale #apitesting #mocks #ai #agents #llm #developers

Matt LeRay explains the key difference: AI agents can perform multi-step processes to solve complex software tasks, unlike simple LLMs that mainly answer questions. Discover how agents go beyond chat to: What are your thoughts on AI agents in software development? Let us know in the comments below!

Optimizing IoT and edge with Ubuntu: secure, simplify, scale

From IoT to edge computing, Ubuntu helps you secure, simplify, and scale device deployments with confidence. In this session, Gabriel Aguiar Noury (Product Manager) and Tabish Khan (Sales Director IoT) from Canonical explore how Ubuntu streamlines the deployment, management, and maintenance of embedded systems, without compromising on reliability or security. Whether you’re building next-gen hardware or optimizing existing infrastructure, this talk offers practical insights and tools to help you succeed.

The Cloud Has Made Us Reckless! It's Time to Reclaim Control

Tim Banks takes the stage at Civo Navigate San Francisco 2025 to explore the unintended consequences of cloud adoption. From runaway AWS bills to vendor lock-in and lost operational skills, Tim offers a thought-provoking look at how convenience in the cloud has come at a cost to resilience, privacy, and sustainability.

Everything You Need to Know About OpenTelemetry Histograms

Modern systems throw off a lot of data—metrics, traces, logs—sometimes more than we know what to do with. When you're trying to understand how values spread out over time (like response times, memory usage, or queue lengths), averages alone don’t tell the full story. OpenTelemetry histograms help fill in those gaps. This guide walks through what they are, why they matter, and how DevOps engineers can use them to improve observability in real systems.

Correlation ID vs Trace ID: Understanding the Key Differences

You’re staring at logs, trying to figure out what caused that odd error in the middle of the night. Or maybe you're following a chain of requests across services, hoping to understand how one user action triggered a series of unexpected behaviors. That’s where distributed tracing and request tracking—specifically, correlation IDs and trace IDs—are invaluable. It’s the kind of detail that can make debugging faster and less painful.

Pager fatigue: Making the invisible work visible

As much as you try to prevent it, your product will break sometimes. While you hope it would have the decency to do so while you are awake and already working, sometimes the product is inconsiderate and decides to break outside your office hours. Being woken up from a page at 3 am sucks, and being woken up again two hours later (when you get pinged for a follow-up issue you missed the first time) sucks even more.

JFrog's Journey with AWS Graviton

Every business strives to optimize operational costs and efficiency. In the DevOps world, where cloud-scale operations are the norm, this becomes even more critical. At JFrog, while delivering a robust and highly scalable SaaS solution to our customers, we are equally focused on optimizing operational costs and maximizing infrastructure efficiency.

Tracking Azure Elastic Jobs using Redgate Monitor

Redgate Monitor has long helped data teams and DBAs keep track of SQL Agent Jobs. Now, with version 14.0.53, it extends that visibility to Azure Elastic Jobs, giving you a centralized view of all your scheduled tasks, whether they run on SQL Server, Azure SQL Managed Instances, or Azure SQL Databases.

OWASP CI/CD Top 10: Inadequate IAM

In the race to ship software faster, many teams have turned to automation, decentralised tools, and powerful pipelines. But lurking under the surface of these streamlined processes is a growing and often invisible Identity and Access Management (IAM) threat vector. — a core vulnerability in modern CI/CD security.

Lessons Learned in LLM Prompt Security: Securing AI with AI

AI is no longer just a buzzword. According to a 2024 McKinsey survey, 72% of companies now use AI in at least one area of their business. By 2027, nearly all executives expect their organizations to use generative AI for both internal and external purposes. However, with this rapid adoption comes significant security risks. As organizations rush to implement AI solutions, many overlook a critical vulnerability: prompt security.