Best Container Monitoring Software for GitLab

The Dynatrace software intelligence platform. Transform faster with unparalleled observability, automation, and intelligence in one platform. Leave the bag of tools behind, with one platform to automate your dynamic multicloud and align multiple teams. Spark collaboration between biz, dev, and ops with the broadest set of purpose-built use cases in one place. Harness and unify even the most complex dynamic multiclouds, with out-of-the box support for all major cloud platforms and technologies. Get a broader view of your environment. One that includes metrics, logs, and traces, as well as a full topological model with distributed tracing, code-level detail, entity relationships, and even user experience and behavioral data – all in context. Weave Dynatrace’s open API into your existing ecosystem to drive automation in everything from development and releases to cloud ops and business processes.

Sedai is an autonomous cloud management platform powered by AI/ML delivering continuous optimization for cloud operations teams to maximize cloud cost savings, performance and availability at scale. Sedai enables teams to shift from static rules and threshold-based automation to modern ML-based autonomous operations. Using Sedai, organizations can reduce cloud cost by up to 50%, improve performance by up to 75%, reduce failed customer interactions (FCIs) by 75% and multiply SRE productivity by up to 6X for their modern applications. Sedai can perform work equivalent to a team of cloud engineers working behind the scenes to optimize resources and remediate issues, so organizations can focus on innovation.

OverOps instantly pinpoints at runtime why critical issues break backend Java and .NET applications, eliminating the detective-work of searching logs to reproduce critical errors. Unlike logs, static testing, and APM, that require foresight, OverOps analyzes code at runtime. OverOps requires no code changes, integrates into your existing CI/CD tooling, and does so continuously, from pre-prod through production.