We're excited to introduce Check-ins, our no-fuss solution to monitoring your scheduled jobs and continuous processes. AppSignal Check-ins allow you to seamlessly monitor the scheduling, run times, and health of your scheduled jobs and processes, with a simple setup using helpers or API endpoints. In this post, we'll introduce you to the new Check-ins feature and show you how to start monitoring your app's background processes with AppSignal.

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.

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.

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.

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.

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.

With any change, there are risks. Change Management risks refer to potential negative outcomes that could occur during the process of implementing a change. These include things like operational disruptions, financial losses, or security vulnerabilities. When managing a change, it’s crucial not just to focus on the change itself but also to plan for and mitigate these risks. Effective Change Management requires a proactive approach.

In the of IT Service Management (ITSM), balancing performance expectations with actual outcomes can feel like walking a tightrope. Businesses rely heavily on defining measurable targets to ensure smooth operations, and that’s where terms like Service Level Agreement (SLA) and Service Level Objective (SLO) come in. But when we dive into the nitty-gritty, understanding the differences between SLA vs SLO can get tricky.

We are excited to announce the release of Icinga for Kubernetes v0.2.0! This update brings a host of new features and improvements that enhance our monitoring solution for Kubernetes. It makes it easier than ever to analyze problems and understand complex Kubernetes hierarchies.

Health check monitoring is a critical practice for maintaining reliable and high-performing systems. It allows you to proactively identify and address issues before they impact your users. This guide explores the fundamentals of health check monitoring, its importance in modern systems, and practical strategies for implementation. You will also learn how HTTP endpoints can be monitored with OpenTelemetry.