Amazon Web Services (AWS) Kinesis is a cloud-based service that can fully manage large distributed data streams in real-time. This serverless data service captures, processes, and stores large amounts of data. It is a functional and secure global cloud platform with millions of customers from nearly every industry. Companies from Comcast to the Hearst Corporation are using AWS Kinesis.

OpenTelemetry (OTEL) is a big data platform that enables the collection and analysis of large-scale telemetry data. Many companies have adopted it for use in their products. In this post, we’ll discuss semantic conventions in OpenTelemetry and how they are used to make data processing easier. We’ll also discuss the different types of semantic conventions and their importance.

The growth of technology has led to more efficient and relevant digital experiences, and customers continue to expect more out of those interactions. That’s true no matter their location and no matter which device they choose to use. Companies that cannot provide these kinds of personalized interactions for their customers find themselves falling behind the competition as technology continues to advance.

The digital database has come a long way since its infancy in the 1960s. Modern databases do much more heavy lifting than their simpler predecessors and have become sophisticated storehouses for both unstructured and structured data. Businesses still rely heavily on databases, and with advances in database monitoring technology, teams can protect their data like never before.

Helm is a deployment tool that simplifies installing, configuring, and managing Kubernetes clusters. Anyone familiar with writing Kubernetes manifests knows how tedious it is to create multiple manifest files using YAML. Even the most basic application has at least 3 manifest files. As the cluster grows, the more unwieldy the configuration becomes. Helm is one of the most useful tools in a developer’s tool belt for managing Kubernetes clusters.

Modern businesses require increasingly complicated tech stacks to keep their teams up and running. What’s more, as businesses try to stay on top of the latest advancements, they wind up with interconnected layers of apps, hardware, and systems that become more and more interdependent on one another. Often, mission-critical technology ends up dependent on various connections, services, and infrastructure components.

LM Envision is a unified observability platform from LogicMonitor that unites comprehensive monitoring and observability capabilities. In this blog post, we’ll show how to integrate Istio service mesh with a LogicMonitor APM so that application traces can be used within LM Envision to better understand, optimize, and troubleshoot application performance.

Azure Active Directory (Azure AD) is a comprehensive cloud-based platform used around the world. It is an identity provider and access management service. If a company employs OneDrive, Skype, or Outlook, they are already using Azure in some capacity. Similarly, if a company uses Microsoft Teams or other applications in the Microsoft Office Suite, they are accessing them by logging into Azure AD.

The heart of any software development operation is infrastructure. This combination of virtual and physical assets ensures that the flow, storage, processing, and analysis of data remains efficient and as seamless as possible. When it comes to selecting a model for managing and deploying infrastructure, IT managers typically have two choices: infrastructure as code (IAC) or infrastructure as a service (IaaS).

The gap between top and low-performing engineering teams is dramatic, whatever angle you look at it from. Whether you analyze their tech stacks and architecture choices, performance metrics, or cultural and team elements, the delta tends to be quite impressive. Despite the wide range of approaches, a few indicators paint a clear picture of the typical characteristics of a well-oiled setup.