Best Observability Tools for Scala

New Relic's enterprise-grade Observability solution offers an all-encompassing platform to gain profound insights into the functionality and dynamics of your software systems. Tailored for extensive operations, our integrated data platform consolidates telemetry information from your entire technological ecosystem, presenting robust full-stack analysis tools that provide in-depth understanding of system performance, interdependencies, and behavior. Featuring real-time monitoring, automated notifications, and customizable dashboards, New Relic empowers you to proactively detect and resolve issues, enhance performance, and ensure outstanding customer experiences. Streamline observability, boost operational efficiency, and foster innovation with New Relic's cutting-edge Observability offerings.

Sematext Cloud provides all-in-one observability solutions for modern software-based businesses. It provides key insights into both front-end and back-end performance. Sematext includes infrastructure, synthetic monitoring, transaction tracking, log management, and real user & synthetic monitoring. Sematext provides full-stack visibility for businesses by quickly and easily exposing key performance issues through a single Cloud solution or On-Premise.

Identify and resolve performance issues and errors within your microservices architecture. Establish connections between root causes by analyzing traces, logs, and metrics. Reduce your costs associated with OpenTelemetry traces through Aspecto's integrated remote sampling feature. The way OTel data is visualized plays a crucial role in enhancing your troubleshooting efficiency. Transition seamlessly from a broad overview to intricate details using top-tier visualization tools. Link logs directly to their corresponding traces effortlessly, maintaining context to expedite issue resolution. Utilize filters, free-text searches, and grouping options to navigate your trace data swiftly and accurately locate the source of the problem. Optimize expenses by sampling only essential data, allowing for trace sampling based on programming languages, libraries, specific routes, and error occurrences. Implement data privacy measures to obscure sensitive information within traces, specific routes, or other critical areas. Moreover, integrate your everyday tools with your operational workflow, including logs, error monitoring, and external event APIs, to create a cohesive and efficient system for managing and troubleshooting issues. This holistic approach not only improves visibility but also empowers teams to tackle problems proactively.

Keep a close eye on your data health and the performance of your pipelines. Achieve comprehensive oversight for pipelines utilizing cloud-native technologies such as Apache Airflow, Apache Spark, Snowflake, BigQuery, and Kubernetes. This observability platform is specifically designed for Data Engineers. As the challenges in data engineering continue to escalate due to increasing demands from business stakeholders, Databand offers a solution to help you keep pace. With the rise in the number of pipelines comes greater complexity. Data engineers are now handling more intricate infrastructures than they ever have before while also aiming for quicker release cycles. This environment makes it increasingly difficult to pinpoint the reasons behind process failures, delays, and the impact of modifications on data output quality. Consequently, data consumers often find themselves frustrated by inconsistent results, subpar model performance, and slow data delivery. A lack of clarity regarding the data being provided or the origins of failures fosters ongoing distrust. Furthermore, pipeline logs, errors, and data quality metrics are often gathered and stored in separate, isolated systems, complicating the troubleshooting process. To address these issues effectively, a unified observability approach is essential for enhancing trust and performance in data operations.