Top 8 Redis Monitoring Tools in 2025: Features, Pricing & Best Use Cases for Developers
Redis Monitoring tools are essential today as applications demand real-time responsiveness and zero downtime. Redis ranks as the #1 key-value store on DB-Engines, so tracking latency, cache hit ratio, and memory usage is now mission-critical. Yet choosing the right Redis monitoring tools is challenging. Teams face issues like unpredictable costs, limited metric granularity, replication lag […]
Monitoring Kubernetes API Servers: Metrics, Logs & Error Tracking with CubeAPM
Monitoring Kubernetes API Servers is more critical than ever. In 2025, roughly 80% of enterprises report production outages due to system changes in their Kubernetes environments, and many say detection and resolution take over 40 minutes each. These interruptions often trace back to issues in the API Server—its latency, mis-configured auth, etcd bottlenecks—that ripple throughout […]
Monitoring Kubernetes Ingress Controller: Metrics, Logs & Reliability with CubeAPM
Monitoring Kubernetes Ingress Controller is becoming non-optional as clusters power critical systems: your apps, APIs, and customer-facing services, TLS termination, and external traffic management. Over 43% of cloud environments are vulnerable to Remote Code Execution flaws in Ingress-NGINX admission controllers, putting public clusters at severe risk. Many teams suffer when monitoring Kubernetes Ingress Controller: error […]
Top 7 Checkly Alternatives in 2025: Features, Pricing & Comparison
Checkly is well-known for its monitoring-as-code model, offering synthetic API and browser checks, Playwright/Puppeteer scripting, and global uptime coverage. It’s a strong fit for developer workflows, but it stops short of APM, distributed tracing, and infrastructure visibility. CubeAPM is the best alternative to Checkly. It features full MELT (Metrics, Events, Logs, Traces), OpenTelemetry-native ingestion, and […]
Top 9 Snowflake Monitoring Tools in 2025: Query Tracing, Performance & Credit Usage
Snowflake powers modern analytics at scale, with the cloud data warehouse market projected to grow to $155B by 2034. Misconfigured warehouses or runaway queries can quickly inflate bills. Since Snowflake sits at the core of microservice pipelines, even small errors ripple downstream, yet native tools lack real-time anomaly detection and cross-service correlation. CubeAPM fills this gap […]
Top Session Replay Monitoring Tools in 2025: Deep Dive into User Journey Reconstruction and Performance Diagnostics
Session replay monitoring lets teams go beyond crash reports and logs by reconstructing a user’s journey — clicks, scrolls, network calls, UI changes — to uncover why something broke or a user dropped off. It’s increasingly essential: a 2025 market report found that approximately 72% of enterprises are now using session replay tools to enhance […]
Top RabbitMQ Monitoring Tools in 2025: Metrics, Integrations, and Best Fit for Message-Driven
RabbitMQ is a leading open-source message broker with 35,000+ GitHub stars, used from startups to Fortune 500s. In production, teams must go beyond the basic Management UI to track queue depth, consumer lag, and cluster health. With data volumes growing and SaaS costs rising, efficient, correlated monitoring across metrics, traces, and logs has become essential […]
Top SAP Monitoring Tools in 2025: ABAP, HANA, Fiori, RFC & Hybrid Cloud Observability
SAP powers mission-critical business processes, yet monitoring these landscapes is complex. Teams must track ABAP dumps (ST22), background jobs (SM37), HANA health, and hybrid infrastructure in real time.. ITIC reports that over 90% of enterprises face downtime costs above $300,000 per hour, making proactive monitoring essential. CubeAPM solves this by bringing SAP-specific observability into a […]
Monitoring Kubernetes HPA (Horizontal Pod Autoscaler): Metrics, Scaling, and Reliability with CubeAPM
Monitoring Kubernetes HPA (Horizontal Pod Autoscaler) is critical as more than 96% of enterprises run Kubernetes, yet average CPU utilization sits at just 13%, highlighting wasted resources and unstable scaling practices. Without proper HPA monitoring, autoscaling often fails to match real workload patterns. The pain point for teams is unpredictable scaling: pods spike and drop […]