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.

Visibility into email health and performance is indispensable to any organization seeking to reach its customers through their inboxes. As they work to curtail spam, internet service providers (ISPs) are redefining the standards of deliverability on an ongoing basis, and organizations often struggle to adapt.

As your organization scales its applications across many different cloud and SaaS providers, it becomes more challenging to understand your costs. You likely receive your bill at the end of the month, meaning you don’t have real-time visibility into who’s spending what and which services or applications your teams are spending the most on. Changing service costs also makes it difficult to break down your costs and identify what is driving spend, leaving you unable to take action.

One Ruby feature that embodies the principle of “optimizing for programmer happiness” is how the language uses garbage collection (GC) to automatically manage application memory. But as Ruby apps grow, GC itself can become a big consumer of system resources, and this can lead to high CPU usage and performance issues such as increased latency or reduced throughput.

Elevated connection churn can be a sign of an unhealthy distributed system. Connection churn refers to the rate of TCP client connections and disconnections in a system. Opening a connection incurs a CPU cost on both the client and server side. Keeping those connections alive also has a memory cost. Both the memory and CPU overhead can starve your client and server processes of resources for more important work.

We recently released our initial State of Cloud Costs report, which identified factors shaping the costs of hundreds of organizations that use Datadog Cloud Cost Management to monitor their AWS spend. The report reveals several widely applicable themes, including the ways in which resource utilization, adoption of emerging technologies, and participation in commitment-based discount programs all shape cloud environments and costs.

Oracle Cloud Infrastructure (OCI) provides cloud infrastructure and platform services designed to support a broad spectrum of cloud strategies and workloads. OCI provides enterprise customers with scale-up resource scaling architectures, ultra-low-latency networks, and more to help them migrate legacy workloads to the cloud, while supporting cloud-native applications via an expansive network of cloud partners and services.

Twilio is a customer engagement platform that helps organizations build communication features to meaningfully interact with customers on the channels they prefer. Twilio consists of a set of APIs for integrating communication tools such as voice, SMS, chat, video, and email into applications. Datadog’s Twilio integration collects a wide variety of logs to allow you to analyze performance issues and detect security threats across all of your Twilio resources.

While building our Service Level Objectives (SLO) product, our team at Datadog often needs to consider how error budget and burn rate work in practice. Although error budgets and burn rates are discussed in foundational sources such as Google’s Site Reliability Workbook, for many these terms remain ambiguous. Is an error budget a static quantity or a varying percentage? Does burn rate indicate how fast I’m spending a fixed quantity, or is it just another way to express error rate?

Many organizations use Oracle databases for their ability to be deployed anywhere, embedded security features, robust data analysis capabilities, and scalability. But manually managing Oracle databases can be impractical, requiring constant attention to optimize performance.