As organizations move their application workloads to the cloud, understanding the difference between cloud observability vs monitoring is crucial to ensure optimal performance and seamless operations. While both concepts are often mentioned in tandem, they serve different purposes, and mastering each can help organizations thrive in increasingly complex cloud environments.

Kafka brokers are the backbone of your data streaming architecture. They’re responsible for storing, distributing, and managing large amounts of data in real-time. As your Kafka cluster scales, keeping those brokers healthy, optimized, and resilient becomes more critical than ever. Proper broker management ensures that your data streams are running smoothly, that performance is maximized, and that any faults are handled without major interruptions.

Managing your AWS costs is both crucial and complex, and as your AWS environment grows, it becomes harder to know where you can optimize and how to execute the necessary changes. Datadog Cloud Cost Management provides invaluable visibility into your cloud spend that enables you to explore costs and investigate trends that impact your cloud bill.

Kubernetes operators and Helm charts are both tools used for deploying and managing applications within Kubernetes clusters, but they have different strengths, and it can be difficult to determine which one to use for your application. Helm simplifies the deployment and management of Kubernetes resources using templates and version-controlled packages. It excels in scenarios where repeatable deployments and easy upgrades or rollbacks are needed.

It’s no secret that many businesses rely heavily on Amazon Web Services (AWS) for their infrastructure and application needs. While AWS offers scalability, flexibility, and reliability, managing and monitoring cloud resources can be challenging. That’s where AWS monitoring and observability can be a tremendous asset. Today, we will explore how implementing these practices is crucial for ensuring that your cloud environment operates smoothly, efficiently, and securely.

Recently, a striking report published by Omdia and Canonical highlighted that 86% of communication service providers (CSPs) are optimistic about the future of edge computing on telco networks. This is a market that is expected to grow substantially in the coming years, with our report shedding light on the motivation that CPSs are drawing from the enhancements that 5G networks will bring.

Learn how you can modernize your applications at scale for a powerful hybrid multicloud solution. Every network team wants a hybrid multicloud network that is efficient, resilient, secure, and scalable. Megaport has been a part of this journey for years, and many enterprises today leverage Megaport Cloud Router(MCR) for their cross-cloud workloads to achieve their dream networks.

Observo AI is excited to announce that we have partnered with Microsoft and it is now available on the Azure Marketplace. This will make it easier for Azure customers to quickly adopt the AI-Powered Security and Observability Pipeline to help control costs, manage data sprawl, boost productivity, and identify and resolve critical incidents faster. Customers can now deploy Observo AI at speed while benefiting from Azure’s trusted and secure infrastructure, as well as its global commercial footprint.

As AI capabilities become more powerful and expansive across IT operations and use cases, the marketplace has become crowded with contenders looking to provide solutions. But when smart enterprise buyers size up their options, ScienceLogic invariably stands out with key business differentiators that showcase why we win and stand apart from the competition.

Tail latency significantly impacts large-scale systems. This blog covers its importance, contributing factors, and effective reduction strategies.