Operations | Monitoring | ITSM | DevOps | Cloud

Microsoft's Azure and Amazon Web Services (AWS) are the two most popular cloud providers today. They both offer a variety of Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS) solutions. In addition, you'll find products covering multiple computing areas, such as compute, storage, analytics, and networking. You can also deploy AWS or Azure services in the cloud, on-premises, or as a hybrid setup.

Kubernetes has broken down barriers as the cornerstone of cloud-native application infrastructure in recent years. In addition, cloud vendors offer flexibility, speedy operations, high availability, SLAs (service-level agreement) that guarantee your service availability, and a large catalog of embedded services. But as organizations mature in their Kubernetes journey, monitoring and optimizing costs is the next stage in their cloud-native transformation.

As a developer, I love the versatility of Python. Over the years I have used Python for so many different use cases: game development, APIs, IoT, machine learning, and web development. It can scale tall applications in a single bound and take on any challenge faster than you can pip install flask. Something you learn very quickly in the world of app development is to build everything for scale.

Cloud Service Providers (CSPs) offer an ever-expanding array of instance types, ensuring that for any given workload there exists the perfect hosting option that matches the exact needs of that app or business service. But with this expansion comes an ever-increasing challenge to match the workloads to the offerings – there are many things to consider.

TechEx North America 2022’s AI & Big Data Expo, America’s leading enterprise technology exhibition, concluded with incredible insights across ML, cloud infrastructure, and big data analytics industries. Showcasing expert panel discussions, live demos and high-level presentations from over 250+ speakers, the convention highlighted five key takeaways — some innovations, yet some gaps in terms of big data progression.

From Sumo Logic’s inception over a decade ago, we made a strategic bet to go all in with Amazon Web Service (AWS). Today, many of our customers rely on Sumo Logic to gain unified visibility into their growing number of AWS services, cut troubleshooting time and unlock comprehensive root cause analysis for complete issue resolution.

Observability is a measure of how well we are able to infer the internal state of our application from its external outputs. It’s an important measure because it indirectly tells us how well we’d be able to troubleshoot problems that will inevitably arise in production. It’s been one of the hottest buzzwords in the cloud space for the last 5 years and the marketplace is swamped with observability vendors. Different tools employ different methodologies for collecting data.

Companies are increasingly adopting managed Kubernetes services, such as Microsoft Azure Kubernetes Service (AKS), to build container-based applications. Leveraging a managed Kubernetes service is a quick and easy way to deploy an enterprise-grade Kubernetes cluster, offload mundane operations such as provisioning new nodes, upgrading the OS/Kubernetes, and scaling resources according to business needs.