This guide explains the key aspects of the OpenTelemetry Collector, including its features, use cases, and practical tips for managing telemetry data effectively.

Amazon Web Services (AWS) is a great platform for DevOps and FinOps teams for several reasons. It provides a wide range of services, supports extensive automation, and includes strong collaboration tools. Despite this, AWS can be a complex ecosystem that makes cloud management challenging. The good news is that AWS also offers a suite of tools to help you apply DevOps best practices and cloud cost optimization.

SRE, DevOps and Platform Engineering are important concepts in today's world of software development. There are dedicated teams to manage these areas, each with a unique primary focus, set of responsibilities, tools and metrics used to gauge their performance requirements. This article explains SRE, DevOps, and Platform Engineering, including similarities and differences, and, most importantly, how these teams help streamline modern software development, delivery, and maintenance processes.

This blog post is part of our data centre networking series.

Privileged Access Management (PAM) solutions have become increasingly popular due to their ability to address data security concerns with flexible access control. One essential area for employing PAM solutions is using them alongside database clients (from the simplest ones to full-fledged IDEs) to ensure safe access to databases. StrongDM is a leading PAM solution that supports modern software development infrastructures both on-premises and in the cloud.

GoMock is a powerful tool for generating mock objects in Go, making it an essential asset for developers aiming to write advanced unit tests. By simulating the behavior of real objects, GoMock allows you to test your code in isolation, ensuring that each component functions correctly on its own. This capability is particularly useful in a language like Go, where interfaces play a crucial role in defining the behavior of different components.

Machine learning (ML) models are almost always developed in an offline setting, but they must be deployed into a production environment in order to learn from live data and deliver value. A common complaint among ML teams, however, is that deploying ML models in production is a complicated process. It is such a widespread issue that some experts estimate that as many as 90 percent of ML models never make it into production in the first place.

In this blog, we walk through Atlassian's cloud security practices and the controls we give you inside Bitbucket to maintain enterprise-grade security, without the overhead of managing it internally. Security is an essential part of Atlassian's offerings. We manage code and data for over 300,000 customers who serve hundreds of millions of users. To secure data at the scale we operate, we invest more in security than most individual organizations can.

Azure Cost Optimization is one of the key factors to achieving a solid return on investment using the cloud. The more we use the resources, the more we have to pay increasing the Azure spend. But it is more important to keep an eye on the amount spent on the resources. Azure Cost Optimization is crucial for organizations leveraging Microsoft Azure to ensure they are using cloud resources efficiently, avoiding unnecessary expenses, and maximizing the value of their investment.

Organizations need highly scalable compute capacity in the cloud to handle fluctuating workloads. This ensures they can meet peak demand without over-provisioning resources or incurring unnecessary costs during low activity periods. Amazon EC2 offers one of the most flexible, on-demand infrastructures that can be scaled to meet business needs. Yet, it isn’t suitable for everyone. In this guide, we’ll explore why that is and share the best EC2 alternatives to consider. But first, a quick recap.