With the development and increased usage of cloud-native technologies, containers, and microservices-based architectures, log monitoring has become a fundamental component of effective management for organizations. Logs offer users insights into occurring issues and assist them in understanding how their software performs over time, where it excels, and where it fails.

In today’s digital era, data has become an integral part of every organization. The exponential growth of data continues to accelerate, with projections indicating a compound annual growth rate of 28% for data creation. While this surge in data presents vast opportunities, it also brings substantial challenges in terms of management and value extraction. This is where the concept of a data engine comes in. It serves as the core of your data infrastructure, functioning like a central nervous system.

Michal Vaško is a DevOps engineer at cloudWerkstatt, with a passion for open source technology and a deep love for observability. While operations or platform teams have long relied on visibility into metrics to react swiftly, the idea of doing the same thing with logs was once just a dream. Thankfully, Grafana Loki has revolutionized the logging stack, giving you the same level of visibility with logs that you get with metrics.

Apache Kafka has risen as a pivotal element in modern distributed systems, transforming data processing, storage, and distribution across diverse applications. Kafka, developed by Kafka, is an open-source distributed event streaming platform. It is designed to efficiently manage high volumes of real-time data, acting as a distributed messaging system.

Splunk Observability Cloud is a full-stack observability solution, combining purpose-built systems for application, infrastructure and end-user monitoring, pulled together by a common data model, in a unified interface. This provides essential end-to-end visibility across complex tech stacks and various data types, such as metrics, events, logs, and traces (MELT), as well as end-user sessions, database queries, stack traces and more.

If your organization has an observability practice, it’s likely that the end goal was to increase system reliability and customer satisfaction. But balancing reliability needs with the need to innovate to meet ever-increasing customer expectations remains a challenge for most.

A vital aspect of working in IT is that you need to effectively monitor a broad range of KPIs and metrics to ensure the smooth operation of your IT infrastructure. IT dashboards streamline this process as they are specialized dashboards designed to offer insights and track key performance indicators (KPIs) related to numerous aspects of IT operations and infrastructure.

Observability costs are exploding as businesses strive to deliver maximum customer satisfaction with high performance and 24/7 availability. Global annual spending on observability in 2024 is well over 2.4 billion USD and is expected to reach 4.1 billion USD by 2028. On an individual company basis, this is reflected by observability costs ranging from 10-30% of overall infrastructure spend. These costs will undoubtedly rise with digital environments expanding and becoming ever more complex.

Cloud migration has become a crucial strategy for businesses aiming to capitalize on scalability, flexibility, and cost-saving opportunities. As organizations transition from traditional data centers to cloud infrastructure, these companies can access advanced cloud services, enhance operational efficiency, and ensure seamless data and application management. However, cloud migration challenges can be difficult to solve.