As the digital landscape evolves at breakneck speed, enterprises face an increasingly complex challenge: how to ensure their systems remain reliable and available amidst the chaos of modern technology. In this journey, Site Reliability Engineering (SRE) emerges as a beacon of hope, offering a pragmatic approach to building a culture of reliability at scale.

It’s never easy when layoffs hit your organization. In addition to the personal impact of losing friends and coworkers from your team, those who remain are left trying to achieve the same business goals with less people and resources. Unfortunately, layoffs and restructuring have become a common part of business. But you’re not alone. Your partners (including Gremlin) are here to help you navigate your new reality.

How does ITIL 4 define the event management practice? And what can we learn from it for our day-to-day monitoring tasks? Let’s find out.

If you deploy container-based services in Kubernetes, chances are you’re also using infrastructure-as-code to help automate the provisioning and maintenance of the cloud environments where your applications will run. Up until recently, Terraform was “the name” in infrastructure-as-code.

As Kubernetes adoption continues to surge across various industries, the need for robust monitoring solutions is more critical than ever. Effective Kubernetes monitoring not only ensures the health and performance of your containerized applications but also provides valuable insights for troubleshooting and optimizing your infrastructure. However, Kubernetes's distributed and dynamic nature presents unique challenges regarding monitoring and observability.

In today's age of cloud services and SaaS platforms, continuous improvement isn't just a goal — it's a necessity. Here at Elastic, we're always on the lookout for ways to fine-tune our systems, be it our internal tools or the Elastic Cloud service. Our recent investigation in performance optimization within our Elastic Cloud QA environment, guided by Elastic Universal Profiling, is a great example of how we turn data into actionable insights.

The Uptime Institute’s 2022 Global Data Center Survey highlights a growing challenge for operators: attracting and retaining qualified staff. With 53% struggling to find skilled employees and 42% losing staff to competitors—a sharp rise from 17% in 2018—there’s a clear need for solutions. DCIM software emerges as a key response, offering a holistic view of data center operations. This includes monitoring power usage, cooling systems, server space, and network operations.

Government agencies are embracing digital modernization to transform the delivery of public services and reimagine the constituent experience. Recent research shows that citizens have a clear preference for engaging with government through websites and mobile applications over in-person or telephone interactions, just as the experience in their everyday life as commercial consumers – creating a win-win for governments and constituents.

While deep learning, machine learning and artificial intelligence (AI) may seem to be used synonymously, there are clear differences. One school of thought is that artificial intelligence is a larger umbrella category under which machine learning falls and deep learning falls under machine learning. Therefore, while everything that is categorized as deep learning or machine learning is part of the artificial intelligence field, not everything that is machine learning will be deep learning.