Operations | Monitoring | ITSM | DevOps | Cloud

Have you noticed your storage costs rising even when you're keeping an eye on them? The reason might be something easy to overlook: high cardinality data. For data engineers and developers balancing performance and costs, understanding its impact isn’t just useful—it’s key to avoiding unnecessary spending and system slowdowns.

Need to list all the keys in your Redis database? If you're debugging an issue or just checking what's stored, retrieving all keys is a useful skill for any developer. This guide covers everything you need to know—from the basic commands to the performance implications—so you can query Redis efficiently without slowing things down.

Have you ever looked at your monitoring dashboard and wondered, "Why is my Kafka consumer lag spiking again?" It’s a common frustration. Consumer lag isn’t just an inconvenience—it’s a sign that something’s wrong with your data pipeline. When lag builds up, you're facing delayed data processing and the risk of system failures.

Server uptime monitoring is critical for ensuring the reliability and availability of your infrastructure and services. By keeping track of server uptime, you may be able to identify and address potential issues before they impact your end-users. Why just “may be able to”? Because “it depends”. It depends on whether your infrastructure/applications/deployments are built with redundancy in mind. Even if you have a redundant setup, it depends whether it actually works.

For B2B SaaS companies, downtime isn’t just an inconvenience—it’s a direct threat to customer satisfaction and revenue. Unlike consumer applications, they serve a mix of power users pushing the system to its limits and new users expecting a seamless experience from day one. Reliability isn’t just about keeping services online—it’s about ensuring every user interaction runs smoothly. A minor hiccup for one customer might be a major disruption for another.

Today, the workforce is more geographically dispersed than ever before. In the past, remote access was primarily used by IT teams or freelancers who needed to access specific resources from afar. For several years, remote work has been gaining traction, and the COVID-19 pandemic accelerated the adoption of remote and hybrid work environments. Now, businesses of all sizes rely on remote access software to empower employees, maintain productivity, and stay connected across various locations and time zones.

Datadog is the leader in monitoring software. But that doesn't mean it's the best choice for everyone. And if you're reading this, you probably have your doubts. While Datadog used to be the default choice for DevOps teams, today's organizations often struggle to justify its complex pricing model and steep learning curve. Many companies that started with Datadog have found it becoming prohibitively expensive and harder to use as they scale.

Cloud computing offers many advantages over on-premises environments, including scalability, flexibility, and cost-efficiency. Yet, simply using a “lift and shift” strategy — moving your application as-is from an on-premise environment to the cloud with minimal modification can lead to several issues (such as inefficient design, bloated costs, etc.). If you design software or applications for the cloud, it is often best to consider making them cloud-native.