Operations | Monitoring | ITSM | DevOps | Cloud

As more organizations move their databases to cloud-native environments, effectively managing and monitoring these systems becomes crucial. According to Coroot’s anonymous usage statistics, 64% of projects use PostgreSQL, making it the most popular RDBMS among our users, compared to 14% using MySQL. This is not surprising since it is also the most widely used open-source database worldwide.

As the Product Manager for Honeycomb’s new frontend product, Honeycomb for Frontend Observability, I’ve had the joy this past year of speaking to dozens of frontend engineering teams about observability. Many frontend teams come from worlds where they either rely on QA and customer reports to identify issues in production, or they use real use monitoring (RUM) and error monitoring tools to catch the most egregious issues.

Just like how the filling makes a sandwich, an application's performance is closely tied to how effectively its middle-tier components function. While the front-end is what users see and interact with (UI), and the back-end deals with data storage, the middle tier forms the vital core where the real magic happens—processing, logic implementation, and enforcement of business rules.

DataDog and Prometheus are both popular monitoring solutions used to collect and analyze metrics and monitor the performance of systems, but Prometheus is open source and Datadog is proprietary. Datadog provides a unified platform for monitoring, troubleshooting, and optimizing modern cloud-native applications and infrastructure. Prometheus is the most popular tool for monitoring time series metrics. So, how to choose between Datadog and Prometheus?

The stress, sudden disruptions, and high stakes of resolving issues while on call is one of the most challenging aspects of an engineer’s job. Many organizations, from startups to large enterprises, still struggle with their on-call experience, which leads to longer resolution times and lower employee retention rates. Constant context switching, managing multiple tools, and racing against time to resolve issues can cause frustration, burnout, and inefficiency.

Jaeger and Prometheus are both popular open source monitoring systems, but they serve different purposes and focus on different aspects of observability in a distributed system. Learn how these tools are similar, how they're different, and when you should use each one.

We love to talk about the value of observability in accelerating feedback loops by enabling teams to understand what changes they need to make to software. But a barrier that often holds teams back from completing the feedback loop is how long it takes to actually get feedback on code under development, or push code into production.

Splunk is a powerful tool for data analysis and monitoring, but its high costs and complex implementation can be challenging for many organizations. Here are 13 proven Splunk alternatives that provide robust monitoring capabilities, comprehensive data analysis, and more cost-effective solutions for organizations of all sizes.

There is a phenomenal amount of Observability tools on the market, coming in all shapes and sizes, offering many tools and approaches to solve what seems to be an endless number of problems. It also can be overwhelming to use, hard to set up and expensive to run, especially if you are going with SaaS based market leaders like DataDog.

Gearset has been revolutionizing Salesforce DevOps since its founding in 2015. The Cambridge-based team set out with a clear mission: to make Salesforce deployments simpler, faster, and more reliable for every team. Today, Gearset’s powerful product suite is trusted by over 2,500 companies worldwide to deploy metadata, automate CI/CD pipelines, seed sandboxes, and secure critical customer data.