Operations | Monitoring | ITSM | DevOps | Cloud

Kubernetes (K8s) packs a ton of benefits as a container orchestration platform. For instance, K8s is big on automation. This includes automating workload discovery, self-healing, and scaling containerized applications. Yet, Kubernetes isn't always production-ready after a few tweaks. This guide shares crucial Kubernetes best practices you'll want to start using immediately to improve your K8s security, performance, and costs. Let’s get to it!

It’s a wrap! From October 24–28, the Pepperdata team attended KubeCon + CloudNativeCon North America 2022, which brought together top engineers and developers from communities centered around Kubernetes and cloud native. With topics ranging from container observability practices to K8s innovations, Pepperdata unveiled the latest offering of its own: Autonomous FinOps for Kubernetes.

In the fast-growing Azure space, it is essential to scale your business as Azure scales up. Azure is cost efficient by providing a pay-as-you-go model, but it is still necessary for enterprise users to undergo a Cost Analysis to keep their budget at stack. Let us consider a scenario, you’re a manager in your organization, and your team has been using Azure for the last several months. It has created multiple resources that cost money.

From our experience handling Azure Service Bus messages, one frequent suggestion we get from the support person is to download messages from Azure Service Bus entities like Queues and Topic Subscriptions. By downloading the messages as a local copy, it becomes easy for them to debug the messages and use it at a later point in time. Basic knowledge of Azure Service Bus messaging entities is a pre-requisite for the better understanding of this feature.

Don’t forget, it’s the hardware that makes the cloud The main issues we see with clients and cloud implementations are that it can be very difficult for them to get a clear idea of what it is they are buying and how well it will perform. While the consumption and billing models are clear, it can still be hard to know how much you will pay each month. But what is hard is predicting exactly what the level of performance you will get. Some of this is inevitable.

In the last few years, the usage of databases that charge by request, query, or insert—rather than by provisioned compute infrastructure (e.g., CPU, RAM, etc.)—has grown significantly. They’re popular for a lot of the same reasons that serverless compute functions are, as the cost will scale with your usage. No one is using your site? No problem: you’re not charged.

In today’s article, I will be highlighting eG Enterprise’s monitoring capabilities for Amazon’s AWS NICE DCV VDI protocol that was used first in Amazon’s AppStream 2.0 and now subsequently also in WSP 2.0 for the Amazon WorkSpaces service for digital workspaces.

If you’re embarking on a new project and evaluating public clouds, the cost involved will be one of your main considerations. You might decide to use Google Cloud Platform (GCP) as your primary cloud platform. If so, you’ll want to estimate costs based on listed prices. But it might surprise you to find a higher bill than you originally expected.