Datadog vs. ignio AIOps

Datadog works really well with complex microservices architecture like any E-commerce platform which will be having multiple services but they all are interdependent to others so in this scenario Datadog will be best to monitor these as it will show the transactions also between those microservices. If you are using multiple services in your architecture whether it will be cloud services or on prem services Datadog will be the best choice to monitor all those service with in Datadog so that you can see everything in a single place. But if you are having small architecture and few services in that then in that scenario you can use Datadog but it will be little costly as compared to other but obviously the features are very well.

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It's good for issue resolution, user access request automation, standard report generation, health checks, executing self-healing as configured in the attributes. Currently not good at real-time monitoring to trigger an action. Health checks have to be on a scheduled basis.

• Create Dashboards as per application, environments, and Custom metrics in one panel.
• Log aggregation, one-stop Application monitoring tools for the whole infrastructure.
• Playbooks, SLA definition, success and error quotas, request visualizations.
• DB monitoring, Serverless stack monitoring.
• Alerting of Production incidents so we can quickly resolve the issues on time.

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• ignio handles 100+ use cases covering the entire organization including applications and infrastructure.
• Centralize the dashboard to view and executed the health of systems in our environment.
• It handles CA services desk Incidents and requests. Using automated tools with power shell scripts.
• ignio event management helps the organization to manage the alerts well and make an informed decision.

• Alert windows cause lag in notifications (e.g. if the alert window is X errors in 1 hour, we won't get alerted until the end of the 1 hour range)
• I would appreciate more supportive examples for how to filter and view metrics in the explorer
• I would like a more clear interface for metrics that are missing in a time frame, rather than only showing tags/etc. for metrics that were collected within the currently viewed time frame

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• There is a lot more the desktop tool can do. For example, we need to apply an upgrade to get the tool to talk to our infrastructure while employees are working from home. The tool was initially installed with the assumption that the desktops would be in UserLand. Instead after COVID-19 the desktop/laptops have been used for over a year on people's home networks. As of right now, we have to sync when the devices are connected to VPN. Moving forward with the upgrade, we will be getting this data over TLS when they are connected to the untrusted networks.
• The concept of ignio AlOps requires OCM efforts within most operational teams. This isn't necessarily the fault of the tool itself, but when implementing ignio, or any AIOps tool, the team will get a lot of pushback as an outside team is centralizing the operational improvements. The tool should have a centralized intake process that will allow the collection, ranking, and management of automation opportunities. ignio AlOps should then simulate the proposed efficiencies from implementing something within the backlog. Right now a lot of local teams are having a hard time getting on the same page as the enterprise teams, and a common methodology for prioritizing (even if overly simplistic) would go a long way to enterprise planning.
• These tools are very new and things get added to them all the time. There should be a way for the product's stakeholders and process owners to understand the additional value ignio AlOps is gaining over time.

It is a very good product and it helps our organization.

There is some room for improvement, but the Datadog team sends out updates frequently, and the UI is user-friendly for engineers, with no significant loading issues or region-specific problems. That was one of the key reasons we preferred Datadog; our company has employees worldwide, and it wasn't difficult to transition to the tool.

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ignio AIOps version upgrades were a heavy lift. Having to learn a new language versus an industry standard language took time. More consideration on overall internal long-term support needs to be determined.

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It was up than Dynatrace

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We had performance issues in older version butterfly. But the new version cheetah is simply amazing

The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.

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We have built a healthy relationship with the vendor support team throughout the implementation phase, all incidents raised were resolved within the SLA without a fail

Implementation team has provided necessary training & enablement.

Online training materials are shared by the implementation team and it was good.

I am happy with the way team has implemented and shared the product for our organization. However, would like to see it get extended to the other line of business too.

We are still trying other products, but people still like Datadog. After setting up a dashboard, it's great for monitoring instances on Datadog. Also, the DevOps team had a good time setting up Datadog. It means Datadog was way easier to set up compared to those others.

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Self HEAL OOB Capabilites

Quite Scalable!

• Saved us (time & money) from developing our own monitoring utilities that would pale in comparison
• Alerts allow us to remedy issues before our customers even know about them
• Tracking resource usage over time allows us to better plan for future needs, before it becomes a pain-point.

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• ignio has had a positive impact on our organization by saving 7,000+ hours within Operations and automatically resolving 84% of our service requests.
• ignio has increased our alert coverage by over 60%.