Operations | Monitoring | ITSM | DevOps | Cloud

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

Shift Left: The Public to Private Cloud Evolution

We're taking a look at our clients' journey to a hybrid-cloud architecture, exploring the benefits private cloud boasts over public, and how this helps an organisation's digital transformation. In a previous post, we explored the drivers behind an organisation moving from an on-premise strategy to the use of private clouds.

Dynamic Demands, Dynamic Solutions: IT's Role in the Next AI Workflow Evolution

I have just finished reviewing the Microsoft Work Trend Index Annual Report for 2025, which offers fascinating insights into the next wave of organizational evolution. I am particularly excited about the section titled ‘Journey to the Frontier Firm’ and what is possible in phase three, where employees will harness the power of multiple AI agents, creating an ‘agentic swarm’ capable of executing tasks at a scale and speed previously unimaginable.

Densify and Nutanix Partner to Deliver AI-Driven, Fully Automated Kubernetes Optimization

We’re thrilled to announce our partnership with Nutanix, integrating Densify’s AI-powered Kubernetes optimization solution, Kubex, with the Nutanix Kubernetes Platform (NKP). This collaboration brings together two leading technologies to radically improve how enterprise Kubernetes environments are managed—through AI-driven insights and end-to-end automation of resource optimization.

Streamline your LangChain deployments with Langserve on GCP

Deploying Large Language Model (LLM) applications can transform ideas into valuable services. But, deployment challenges can slow down even experienced developers. In this tutorial, you will build and deploy a LangChain application using LangServe and CircleCI on Google Cloud Run. You will create a text summarization tool powered by Google’s Gemini model. You will use Langserve to expose it as an API. You will automate testing and deployment to Google Cloud Run using CircleCI.

Use AI to resolve CI test failures with zero guesswork

Test failures are inevitable. A broken condition, a missed edge case, or a last-minute refactor can trip up even the most careful changes. That’s part of shipping software. What shouldn’t be part of the job is spending half your afternoon parsing logs and chasing down the root cause. Now, there’s a faster way. This guide shows how to use the CircleCI MCP server to identify, understand, and resolve failing tests in a CI/CD build without ever leaving your editor.

REST v. GraphQL v. gRPC #speedscale #developers #softwaredevelopment #shorts #softwaretesting #api

When it comes to building APIs and enabling communication between different software components, three prominent architectural styles and frameworks often come up: REST, GraphQL, and gRPC. Each has its own approach, strengths, and weaknesses, making them suitable for different use cases.

Azure DevOps agent pools: diving deeper

Most of the time the build and deployment pipelines we create will run on compute provided by the Azure DevOps cloud and the only decision we need to make is whether to select a Windows or Linux Agent. Sometimes though, the specification for the VM that Azure DevOps spins up may not be right for our needs. We may need more memory or a particular OS version. This is when custom agents and Agent Pools come into play.
Sponsored Post

5 Ways Bunnyshell Ephemeral Environments help you ship and deploy faster in the age of Gen Code AI

The way we build software is evolving. Fast. AI-powered development tools like Cursor are transforming how developers write code, solve problems, and iterate on ideas. But as the pace accelerates, so do the challenges. Local machines can't keep up. Testing AI-generated code is time-consuming. Sharing work involves unnecessary friction. And moving from dev to production often means slowing down just when you want to speed up. Ephemeral environments are becoming essential infrastructure for modern development-and Bunnyshell helps teams keep pace without compromise.

Combine the Codefresh GitOps Cloud with your existing Argo CD instance

We recently announced the new Codefresh GitOps Cloud, the easiest way to promote changes across Argo CD applications–even across different clusters. With Codefresh GitOps Cloud, you can model your own promotion flow with a graphical editor (although YAML is still available). You define exactly how an application reaches production, including all the requirements and approval gates your organization needs. With Codefresh, environment information gets modelled in the platform itself.