Operations | Monitoring | ITSM | DevOps | Cloud

The goal of capacity planning is to match resources with demand. There are essentially three outcomes from this analysis. You can underestimate the resources you need (underprovision), which can hurt performance. You can overestimate (overprovision), which adds unnecessary costs. Or you can get it just right (rightsized). And, of course, you want to be rightsized at the lowest possible cost. Because many factors go into cloud capacity planning, it can feel like more of an art than a science.

Five worthy reads is a regular column on five noteworthy items we have discovered while researching trending and timeless topics. This week we are exploring the multi-cloud strategy and why its the next biggest thing in cloud computing. In an age where digital innovations happen at breakneck speed, the cloud has become crucial to every enterprise.

In modern business environments, where everything is fast-paced and data-centric, companies need to be able to track and analyze data quickly and efficiently to stay competitive. Metrics play a crucial role in this, providing valuable insights into product performance, user behavior, and system health. By tracking metrics, companies can make data-driven decisions to improve their product and grow their business.

In the previous blog in our root cause analysis with logs series, we explored how to analyze logs in Elastic Observability with Elastic’s anomaly detection and log categorization capabilities. Elastic’s platform enables you to get started on machine learning (ML) quickly. You don’t need to have a data science team or design a system architecture. Additionally, there’s no need to move data to a third-party framework for model training.

As the complexity of modern applications continues to increase, so too does the demand for comprehensive observability solutions. Organizations looking to enhance their applications’ performance, reliability, and scalability need powerful tools that allow them to monitor, analyze, and visualize their infrastructure. One such tool is InfluxDB 3.0, a time series database designed to handle large-scale monitoring and analytics workloads.