Best Data Observability Tools for Hybrid Environments

In the ever-evolving landscape of IT infrastructure, the need for robust, comprehensive observability tools has never been more critical. Additionally, the complexity of integrating traditional mainframes with distributed computing environments continues to challenge IT professionals worldwide. This guide is designed to navigate the intricate world of observability tools that are equipped to manage these hybrid ecosystems effectively.

Focusing on the latest innovations and advancements, we will explore a selection of the Top 4 leading solutions, including their capabilities to integrate and analyze mainframe data alongside distributed systems. From the specialized insights offered by mainframe-first-focused platforms like Zetaly to the AI-driven analytics of broader tools like Dynatrace and Splunk, this guide aims to equip IT and operations professionals with the knowledge to select the observability solution that best fits their unique ecosystem.

Zetaly

Zetaly is a specialized observability and operational analytics platform, with a strong expertise on IBM Z mainframes data. It offers a comprehensive suite of solutions for performance monitoring, capacity planning, and cost management. By providing insights into both real-time and historical data, Zetaly aims to enhance operational efficiency and cost-effectiveness for IT environments.

Pros:

• Mainframe expertise: Zetaly's long experience on IBM Z mainframes ensures deep, actionable insights specific to mainframe operations.
• Financial analytics: Zetaly goes beyond IT metrics with features dedicated to managing and optimizing software licensing costs, which are critical in mainframe operations.
• Ecosystem integration: Offers integration with distributed system data for a unified view of hybrid ecosystems. Zetaly’s API system works both ways – from data collection into the solution to the integration of Zetaly’s data into any other analytics platforms.
• Plug-and-Play: Zetaly’s solutions all come with pre-defined dashboards ready to use from day one.
• Cost: Thanks to its subscription-based pricing model, Zetaly's cost adapts to each need and is more affordable than big players’ solutions. This means that all organizations can benefit from complete observability, even with a limited budget.

Cons:

• Mainframe-first oriented: Zetaly may not seem relevant to organizations that do not possess any mainframe system as it is their strongest expertise.
• Independent player: the fact that the solution does not have a strong market visibility may scare potential users even if existing customers currently express a high satisfaction rate for Zetaly’s products.

Splunk

Splunk is a well-known observability and security platform that offers extensive logging, monitoring, and analytics capabilities across various computing environments, including support for mainframe data integration.

Pros:

• Extensive ecosystem: Splunk has a vast ecosystem of apps and integrations, enabling comprehensive monitoring across hybrid environments.
• Advanced analytics: Offers powerful analytics and machine learning capabilities for predictive insights across systems.
• Scalability: Highly scalable, capable of handling vast amounts of data from both mainframes and distributed systems.

Cons:

• Cost: The pricing model, based on data ingestion rates, can become prohibitive for large-scale deployments with high data volumes.
• Mainframe data integration: Integrating mainframe data to Splunk requires third-party solutions such as IBM z Common Data Provider.
• Complexity: Configuring and managing Splunk requires a lot of service packages to answer specific needs, considerably raising the TCO of the solution.

Dynatrace

Dynatrace provides an all-in-one observability platform with advanced AI capabilities. It supports a wide range of technologies, including mainframe data integration, offering seamless visibility across entire software stacks in hybrid ecosystems.

Pros:

• AI-powered analysis: Offers root cause analysis and problem resolution using AI, reducing manual effort.
• Full-stack observability: Provides insights into applications, infrastructure, and networks, including mainframe and distributed components.
• Ease of use: Emphasizes a user-friendly interface and automated discovery of components for simplified monitoring.

Cons:

• Cost: While offering a comprehensive solution, the cost can be significant, especially for large enterprises.
• Mainframe data: Need the assistance of other solutions to collect mainframe data
• Mainframe depth: May not offer as deep mainframe-specific insights as platforms like Zetaly, given its broader focus.

Datadog

Datadog is a monitoring and security platform that provides observability across cloud, on-premises, and hybrid environments. It includes capabilities for integrating mainframe data, facilitating comprehensive oversight across diverse IT landscapes.

Pros:

• Wide-ranging integrations: Supports a broad array of services and platforms, ensuring flexible integration capabilities in hybrid ecosystems.
• Real-time analytics: Provides real-time analytics and monitoring for immediate insight into performance issues.
• User experience: Focuses on a user-friendly interface and straightforward setup, enhancing accessibility for teams.

Cons:

• Cost at Scale: Datadog’s pricing model is based on data volume and the number of hosts, which can become expensive as usage grows, particularly for large organizations with extensive monitoring needs.
• Mainframe integration complexity: Integrating mainframe data can require additional configuration and adaptation, potentially complicating setup.
• Depth of mainframe insights: While offering broad observability, it may lack the depth of mainframe-specific analytics compared to more specialized tools.

When choosing an observability tool for hybrid ecosystems involving mainframes and distributed computers, it's crucial to consider the unique needs of your environment, including the depth of mainframe integration required, cost implications, scalability needs, and the skill set of your team. This guide provides a starting point, but detailed evaluation and possibly a trial period with these tools will be necessary to make the best choice for your specific requirements.

To learn more about what Zetaly can do for your mainframe, contact us here.