From infrastructure and chipsets to data solutions and development tools, it’s clear that artificial intelligence will play a massive role in the future of the cloud. Read Justin Ryburn’s latest recap to learn about many of the exciting unveilings at Google Cloud Next 2024.

AWS’ Relational Database Service (RDS) is a pivotal component for businesses leveraging cloud technology for their database management needs. RDS simplifies a relational database’s setup, operation, and scaling, offering cost-efficiency while automating time-consuming administration tasks like hardware provisioning, database setup, patching, and backups. However, despite its benefits, navigating the cost structure of RDS to ensure efficient spending can be a complex task.

In the ever-evolving landscape of software development, testing plays a crucial role in ensuring the quality, reliability, and performance of applications. As technology continues to advance, the future of testing is deeply intertwined with automation, offering immense potential for improving efficiency, speed, and accuracy in the testing process.

Lumigo has announced the addition of full log management capabilities into its microservices observability and troubleshooting platform, promising customers enormous savings while enabling automatic correlation between log data and distributed traces.

In a recent live stream, Jackie McGuire and I looked into a crucial topic that many IT and security teams face: delivering value in your organization without budget increases. In this age where technology underpins every facet of business, how can teams maximize their impact with finite resources?

Apache Spark is an open-source, distributed application framework designed to run big data workloads at a much faster rate than Hadoop and with fewer resources. Spark leverages in-memory and local disk caching, along with Apache Spark is an open-source, distributed application framework designed to run big data workloads at a much faster rate than Hadoop and with fewer resources.

As complex as Kubernetes is, much of it can be distilled to one simple question: how do we keep containers available for as long as possible? All of the various utilities, features, platform integrations, and observability tools surrounding Kubernetes tend to serve this one goal. Unfortunately, this also means there’s a lot of complexity and confusion surrounding this topic. After all, most people would agree that availability is important, but how exactly do you go about achieving it?

Today, we embark on an exciting journey into the realm of network observability, where the world of network monitoring gets a vibrant makeover. While network monitoring has long been the stalwart guardian of network operations, network observability swoops in like a caped hero, adding a whole new level of awesomeness to the game.

Bitbucket Pipelines has seen amazing adoption over recent years, with millions of developers and teams using it to build better software every day. As part of our ongoing commitment to improving performance and reliability, we are in the process of making enhancements to our cloud infrastructure. These changes will also unlock a range of powerful new capabilities for customers that will turbocharge their CI/CD workloads and empower engineers to focus more of their energy on building great software.

Network performance plays a key role in service delivery, acutely impacting user experience. However, enterprise teams have long struggled with comprehensive insight into network performance and, when necessary, the ability to hold circuit vendors accountable.