Operations | Monitoring | ITSM | DevOps | Cloud

Mark your calendars: From February 1, 2024, AWS is introducing a $0.005 hourly charge for all public IPv4 addresses. With IPv4 addresses becoming rarer and pricier, AWS is pushing us to be more IPv4-efficient and highlights the urgent need for businesses to adopt IPv6. Where’s This Change Happening? This isn’t just a small tweak, it will affect all AWS services that use public IPv4 addresses. We’re talking about everything from EC2 and RDS database instances to EKS nodes.

Developers and SREs choose Microsoft Azure to run their applications because it is a trustworthy world-class cloud platform. It has also proven itself over the years as an extremely powerful and reliable infrastructure for hosting business-critical applications. Elastic Observability offers over 25 out-of-the-box integrations for Microsoft Azure services with more on the way. A full list of Azure integrations can be found in our online documentation.

DevOps emphasizes continuous improvement, rapid delivery, and cost optimization. It does this by recommending several engineering best practices you can implement in your IT environments. DevOps also emphasizes automation to improve efficiency and engineering velocity in software delivery. In this guide, we will cover the importance of DevOps monitoring. This will include what to monitor and a list of some of the best monitoring tools for DevOps teams.

Navigating the cloud computing landscape often involves a delicate balancing act between leveraging available resources and managing costs. Amazon Web Services (AWS), a leader in cloud services, offers an enticing proposition through its Free Tier, especially with services like Amazon EC2 and RDS. These offerings present a unique opportunity for IT professionals to push the boundaries of cloud computing, but they also pose the challenges of staying within budgetary constraints.

Although IT spend, including on cloud services, cooled somewhat in 2023, the second half of the year showed signs of stability, even resilience, buoyed in part by the growing interest in generative AI. For cloud market leader AWS, with 31% global share, the company’s efforts to cut costs and enhance efficiency resulted in substantial profit improvements. Like its peers, AWS also sees great potential in AI and came out with a slew of capabilities towards the end of the year.

Google Cloud Platform (GCP) enables organizations to create and scale applications. Activities in applications, whether on Compute Engine or other services from virtual machines to serverless environments on GCP, produce a significant amount of logs. Logs play a crucial role in helping you achieve effective observability and troubleshooting. But the logs may experience irregular surges in data ingestion during major system events, posing challenges for network overhead.

Sigh...in the blink of an eye, AWS now has hundreds of thousands of SKUs, 180 different types of services, 17 different ways to launch a container, and has dozens upon dozens of regions and availability zones. No wonder AWS billing has become so complex to understand. Is there a fix?

Platform engineers can influence API development by following best practices and implementing DevOps design patterns.

I’m LV, co-founder and CEO of Taloflow, a technology selection platform built for the AI productivity era. I’ve spent more than a year interviewing over 200 enterprise IT procurement professionals and IT and Engineering decision-makers and have found that the space of software selection and procurement is undergoing a sea change in expectations. Based on the interviews, I’ve determined nine steps in the software procurement lifecycle, but these are more fluid than ever.