Best Observability Tools for AWS Fargate

Find and compare the best Observability tools for AWS Fargate in 2024

Use the comparison tool below to compare the top Observability tools for AWS Fargate on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    IBM Instana Reviews
    IBM®, Instana®, is the gold-standard of incident prevention. It offers automated full-stack transparency, 1-second granularity, and 3-second notification. In today's highly complex and dynamic cloud environments, an hour of downtime could cost you six figures or more. Traditional application performance monitoring tools (APMs) are not fast enough to keep pace or comprehensive enough to contextualize issues identified. They are also typically only available to super users, who must undergo months of training. IBM Instana Observability is a solution that goes beyond traditional APM by democratizing observability. Anyone in DevOps or SRE, Platform Engineering, ITOps, and Development can access the data they need with the context needed. Instana delivers high-fidelity data with a 1-second granularity, and end-toend traces, as well as the context of logical, physical, and mobile dependencies, across applications, web, and infrastructure.
  • 2
    Elastic Observability Reviews

    Elastic Observability

    Elastic

    $16 per month
    The most widely used observability platform, built on the ELK Stack, is the best choice. It converges silos and delivers unified visibility and actionable insight. All your observability data must be in one stack to effectively monitor and gain insight across distributed systems. Unify all data from the application, infrastructure, user, and other sources to reduce silos and improve alerting and observability. Unified solution that combines unlimited telemetry data collection with search-powered problem resolution for optimal operational and business outcomes. Converge data silos with the ingesting of all your telemetry data from any source, in an open, extensible and scalable platform. Automated anomaly detection powered with machine learning and rich data analysis can speed up problem resolution.
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