How to Fairly Evaluate an Observability POC ?

How to Fairly Evaluate an Observability POC A short product demo isn’t enough to evaluate an observability platform. A demo shows screens and features. A POC answers a more important question: Does the platform work for our systems and our teams’ day-to-day needs? To answer fairly, comparing product names or feature lists isn’t enough. You need to test the scenarios your teams actually handle under comparable conditions. Start by understanding how you use your current platform Before the POC begins, identify the work your teams currently do with their platform:

• How do you find the source of a slowdown?
• Can you investigate traces, logs, and metrics together?
• How do you track service dependencies and user experience?
• Which alerts and dashboards do teams use in daily operations?
• Which integrations do teams rely on during an incident?
• Which applications use modern architectures, and which run on legacy systems? This helps define the POC around real needs. A feature’s presence on a product list shouldn’t be a deciding factor if your team doesn’t use it. Set the scope and success criteria in advance Before the evaluation starts, agree on the POC’s duration, participants, and success criteria. For example, you might set a two-to-four-week period and involve the developers and operations staff who respond to incidents, along with the people who will make the decision. Write down the evaluation criteria before the POC begins. Instead of relying on people’s recollections at the end, fill in this table separately for each platform: Criterion What to record during the POC Scenario coverage Which applications and incidents were tested? Data visibility Which traces, logs, and metrics were available? Investigation process What steps did the team take to find the source of the issue? Time to identify the likely cause How long did it take from the start of the investigation to record a likely cause supported by evidence? Setup time How long did it take for the first meaningful data to reach the platform? Implementation effort How much work was required for setup and instrumentation? Operational fit Were security, access, and data-retention requirements met? Cost What was the total license and service cost for the same scope of use? Open items Which requirements weren’t met or require additional work?

Test the same scenarios on both platforms Choose two or three real use cases for the POC. For example, you could examine how teams find the source of a delay in a payment flow. Evaluate the same application and incident scenario under similar traffic and conditions. Also record each platform’s data-collection method and the work required to support it. Follow these steps on both platforms:

1. How easily can the team access the relevant traces, logs, and metrics?
2. Which services did the request pass through, and where did the delay begin?
3. How quickly can the team connect the findings?
4. If AI-assisted analysis is available, what does it recommend and which signals support the recommendation?
5. Can the engineer see the evidence needed to verify the recommendation?
6. If an action is needed, can it be performed within the required approval and permission controls?
7. Can the team verify whether the action improved the situation? IyziTrace focuses on investigating traces, logs, and metrics together, with AI Investigations supporting the analysis process. Evaluate its AI recommendations against the same incident scenario. Record which data supports each recommendation and whether an engineer can verify it. You can include the next step in the evaluation as well. IYZI Remedy carries out a recommended action with team approval and defined permissions, and helps verify recovery afterward. Measure setup and data coverage too A platform’s value isn’t determined only by how it looks once data arrives. Include how the data gets from your applications to the platform in the POC. How many applications and services were connected? Which signals arrived completely? How long did setup take? Were code changes or additional instrumentation required? Which methods were used for legacy applications? OpenTelemetry support can make it easier to collect data from different applications and infrastructure. Still, don’t assume every application can be instrumented equally easily. Measure the additional work required for legacy systems as part of the POC. Define security and operational requirements upfront Before the POC starts, agree on the deployment model—SaaS or on-premises—where data will be stored and for how long, and how access roles and permissions will work. Discuss how sensitive data will be handled. For AI analysis, decide which model and API key will be used. Confirm whether data leaves the organization. Also consider the daily operational effort required to run the observability setup. This ensures that the evaluation reflects your organization’s actual security and operational requirements, not just the product screens. Compare licenses and costs on the same basis Use the same assumptions for each platform: the applications and host or node count to be monitored, data volume, retention period, required modules, support, and implementation services. Licensing models can differ. Instead of comparing list prices alone, document what each offer covers and whether the features tested in the POC are included. Include discounts, additional modules, and service fees in the total cost. When evaluating IyziTrace’s host/node-based licensing, clearly state the host and node scope tested in the POC and which features are included in the license. This keeps the cost comparison grounded in a similar use case. The goal of a POC is to make the right decision A fair POC doesn’t try to prove a predetermined outcome. It shows what teams use their current tools for and how well a new platform meets those needs. When evaluating IyziTrace, consider data visibility, the investigation process, implementation effort, security requirements, and total cost across real scenarios. The findings can then guide a decision about a full transition, use with selected applications, or continued use alongside the current platform. A good POC produces more than a product decision. It gives teams a concrete view of what they monitor, what they need, and how they can improve their operations. Request a demo to plan a POC around your use cases.