Operations | Monitoring | ITSM | DevOps | Cloud

Kubernetes gives you the amazing power to deploy and manage containerized applications. But this power comes with a trade-off. Instead of letting you focus only on writing code and delivering features, Kubernetes also shifts the burden of resource optimization i.e., cost control, performance, and scalability, directly onto your shoulders. The answer to these challenges is automation. Automated optimization takes the guesswork out of resource allocation.

Quickly deploy a production-ready Amazon EKS cluster in just 10 minutes. This step-by-step guide covers essential setup and best practices for running scalable, secure Kubernetes workloads on AWS.

Accelerate development & testing with ephemeral environments. Explore their benefits, key tools (Docker, Kubernetes, CI/CD), and how Qovery simplifies setup for on-demand, production-like dev environments.

Elasticsearch stands as one of the most robust open-source search engines available today. Built on Apache Lucene, it handles complex search operations, real-time analytics, and large-scale data processing with impressive speed and accuracy. Kubernetes has transformed how we deploy and manage containerized applications. This orchestration platform automates deployment, scaling, and operations of application containers across clusters of hosts.

As Kubernetes environments grow in scale and complexity, platform teams face increasing pressure to secure workloads without slowing down application delivery. But managing and enforcing network policies in Kubernetes is notoriously difficult—especially when visibility into pod-to-pod communication is limited or nonexistent. Teams are often forced to rely on manual traffic inspection, standalone logs, or trial-and-error policy changes, increasing the risk of misconfiguration and service disruption.

What are the best Kubernetes monitoring tools in 2025? And how can you ensure alerts actually drive action when something goes wrong? Kubernetes monitoring is critical for keeping your containerized applications healthy, but alerting is often overlooked. This blog compares popular tools like Prometheus and Datadog and explains why intelligent alerting solutions like OnPage are essential for effective incident response.

As organizations begin to scale their observability strategy, point and click methods of management become increasingly unworkable. This is why Coralogix has now fully released the Coralogix Operator for Kubernetes. Kubernetes operators are control loops that allow users to declare their desired state in their Kubernetes clusters, and the operator is responsible for resolving this state.

Docker Swarm's logging model shifts from individual container logs to service-level aggregation. The docker service logs command batch-retrieves logs present at the time of execution, pulling data from all containers that belong to a service across your cluster. This approach gives you a unified view of distributed applications, but it comes with its patterns and considerations for effective observability.

Google Cloud released Google Kubernetes Engine (GKE) as a commercial version of native Kubernetes (K8s). GKE promises a user-friendly, reliable, and cost-effective service. Yet calculating GKE costs can be daunting, including understanding what you’re paying for and maximizing your return on investment. In this GKE pricing guide, we’ll discuss how GKE pricing works, what it costs, and more.