Operations | Monitoring | ITSM | DevOps | Cloud

We introduced Grafana Alloy last year in an effort to create the best possible open source “big tent” telemetry collector. A continuation of our work on Grafana Agent Flow, we designed Alloy to simplify observability at scale and to easily integrate with the OpenTelemetry and Prometheus ecosystems. We’ve seen lots of interest since Alloy was announced at GrafanaCON 2024, and industry observers are taking notice, too.

In system monitoring and observability, understanding the differences between metric types is critical for building robust and insightful monitoring solutions. Prometheus, a powerful open-source monitoring system, offers several metric types, with Gauges and Counters being two of the most fundamental and frequently used.

Enterprise IT departments ended 2024 under more pressure than ever to ensure excellent Microsoft Teams and Microsoft 365 performance. With hybrid work booming, AI everywhere, and businesses increasingly concerned about rising costs, expectations are only likely to intensify in the year ahead.

SaaS tools enable companies of all sizes to get to market quickly, enhance their service delivery, and improve efficiency. By leveraging “ready-to-go” and “proven” platforms, SaaS companies can also avoid building systems from scratch, which is time-consuming and costly. Yet, 61% of companies have over 100 SaaS applications, which can be overwhelming to manage. Orphaned subscriptions are also common. Most companies regularly use only about half of their SaaS stack.

InfluxDB is a purpose-built time series database designed to handle high-write throughput and large volumes of time-stamped data. From monitoring system metrics to tracking IoT device readings and analyzing financial trends, it excels in scenarios where time is a fundamental factor. With the release of InfluxDB v3, users now benefit from dual query language support: SQL and InfluxQL.

Explore the pros and cons of monolithic vs. microservices architectures to find the best fit for your project's needs and scalability.

Learn how to identify and fix common Python errors like SyntaxError, TypeError, and NameError with this quick guide!