Operations | Monitoring | ITSM | DevOps | Cloud

What is it that makes a high-performing software engineering team successful? This was the challenge undertaken by the DevOps Research and Assessment (DORA) team around 2015, who created a set of metrics that could provide a reliable, data-driven way to measure and improve software delivery performance.

In the past, a cloud architect's pain point was usually deciding between these two options: To tackle this confusion, major cloud service providers (CSPs) launched quotas (in their own words). To give you examples, here are the different terminologies used by the three major public CSPs: The main ingredient of a well-oiled cloud setup that significantly impacts cloud operations is understanding and managing cloud quotas, also known as service quotas.

At CloudZero, our mission has always been clear: power efficient innovation in the cloud by connecting engineering decisions with business outcomes. But here’s the truth — we’re not just solving for visibility. We’re solving for action. In order to turn theoretical savings into actual waste elimination and tangible outcomes, you have to enable engineers to act on cost insights within the tools and workflows they already use. CloudZero’s new Jira integration does just that.

In today’s business landscape, trust and reputation are the foundation upon which organizations are built. A single service outage or poor customer experience can severely damage both revenue and brand reputation. When customers or businesses encounter obstacles with their preferred vendor, they often turn to competitors – and these temporary shifts frequently become permanent changes in loyalty.

Flaky tests are a serious productivity problem. When tests sometimes pass and sometimes fail without code changes, they undermine trust in your CI pipeline and drain time from engineering teams. Debugging them often turns into a slow process of chasing logs, rerunning builds, and trying to guess what went wrong. This post shows how to quickly detect and fix flaky tests directly in your IDE by chatting with an AI assistant.

Agentic AI is coming to financial services. Elastic provides the data foundation and tools to make it work. In a recent talk at Stanford University, Jamie Dimon, chairman and CEO of JPMorganChase, addressed the firm’s use of AI and ended with mentioning that agentic AI was the next frontier of AI at the firm, inferring it wasn’t ready to be deployed yet. Let’s break down why that may be the case and what the financial services industry can do to become more comfortable with agentic AI.

Magento is a powerful eCommerce platform, trusted by businesses large and small for its flexibility and robust feature set. Yet, anyone who has managed a Magento project knows it can be an adventure—especially during deployment. Misconfigured environments, extension conflicts, and unpredictable performance are just a few issues that can turn a routine release into a hair-pulling session.

When you’re running an enterprise-level Magento store, you can’t afford to leave infrastructure decisions to chance. With large product catalogs, high transaction volumes, and complex integrations, your hosting choices can directly impact your bottom line—and your sanity. The right solution gives you the performance, reliability, and scalability you need while reducing complexities, maintenance overhead, and cost.

There are many vendors, Honeycomb included, where actions on the application can emit a web request that goes to another service for coordination or tracking purposes. Many vendors have pre-built integrations, but some have a fallback that says “Custom Webhook” or similar. If you’re looking to create a full picture of your request flow, you would want these other services to show up in your trace waterfall.

Automating SDLC Governance is one of our key use cases. Kosli gathers all of the evidence your engineering teams need for change management and audit by recording every step in their SDLC, from commit to production, across all of their CI/CD tools. But robust SDLC governance doesn’t just depend on gathering all the necessary data - it also depends on controlling who can add to that data. And that’s exactly what our new access control feature solves.