Eco4Cloud Workload Consolidation vs. New Relic

Eco4Cloud is well suited in VMware farms that have standard VM deployments, especially with small VMs, with nothing blocking vMotion and hardware fully compatible with IPMI 2.0 (minimum). It doesn't work well if many VMs are nodes in a Microsoft cluster because they would be unmovable and therefore their host would never be put in stand-by mode. If every host in the cluster has at least one guest VM that is a node of a Microsoft cluster, no host in the cluster will ever be put in stand-by mode.

New Relic its an excellent tool for monitoring services used on the SAAS universe, like web servers, relational and nosql dbms, reverse proxies, text databases, etc. Its also a powerful tool to monitor resource usage on said servers. However, its not well fitted to monitor custom services - if you need to generate alerts based on logs or database information, for example

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• It consolidates workloads in VMware clusters using an algorithm that seems to work better than VMware DRS. It keeps headroom for workload peaks and to withstand the number of host failures set for the cluster in vCenter.
• If the workload is very variable, Eco4Cloud will not continuously turn a host on and off but it will settle to keep the host running. It sort of "rightsizes" the cluster keeping only the right number of hosts running. This is another main difference when comparing Eco4Cloud with VMware DRS/DPM which strictly follows the workload and sometimes isn't fast enough in turning on the hosts when the workload is ramping-up.
• To do a good job Eco4Cloud needs to analyze the hosts and the VMs. Therefore, the troubleshooting component of Eco4Cloud can figure out if there are problems in the configuration of the hosts (e.g. vMotion settings). It can also determine if a VM is stuck and can't vMotion (e.g. using the physical CD-ROM) or if it's oversized or undersized.
• Something Eco4Cloud has and others don't is a technology named Smart Ballooning. With Smart Ballooning Eco4Cloud recovers unused RAM from the VMs and gives it back to the host way before the host goes over the 94% RAM threshold. This allows us to reach higher levels of overbooking.

• It gives us insights of applications, infrastructure, clouds very well.
• The alerting system in New Relic helps us to easily identify the root cause which reduces the MTTR.
• It has new features related to AI which helps to troubleshoot any problem in a very short time it gives future predictions also.

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• It would be useful to have a version that works with OpenStack.
• It should be made compatible with VMware VSAN.
• It would be useful to have a version that works with hybrid clouds using the new "vMotion anywhere" or share nothing vMotion feature.

• And while powerful, building tailored dashboards with organ-specific metrics (such as energy load variance across regions) can be difficult to navigate. The UI isn't as drag-and-drop easy, and query-based widgets typically involve some trial and error for non-devs.
• Alerts may be hypersensitive or over general. I We often get a spam of non-critical alerts while doing load testing, all overhauling to me alone and making it difficult to identify actual issues especially in energy systems where spikes are very common.
• With our expanding fleet of Iot devices, the per-host pricing model is becoming expensive, quickly. More detailed billing based on microservices, or that works at sensor level, would make it more adaptable for energy platforms.

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The only issue that we have had with New Relic is that the price might be a little expensive for smaller companies. The amount of data you store in New Relic impacts the cost, and can get away from you if you don't work closely with the vendor. Overall though the application is top notch.

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I have given this much rating as I am used New Relic in different sectors and for different use cases like its K8s monitoring, infra monitoring, full stack monitoring as compare to other tools New Relic gives data in a formatted and connected way, and also it is giving us value for money. It also launches new features day by day which helps users to track the issue very quickly. It also supports OTel integrations which is the latest trend of observability tools. thats why I had given this much rating to New Relic.

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Never observed an outage

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there are times where browser cache will cause issues that require you to clear your browser before continuing.

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The support team has been really helpful and resolved most of the issues on time. However, for a couple of issues, several follow-ups were needed to elicit a reasonable response. The issue was deeply technical and could have been investigated only by their Architects, and bringing them into the ticket took longer than needed

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It's better to start by implementing New Relic in one project and test everything. Try to follow best recommended practices and read all the official documentation. Everything seems well tested. Then, start by installing agents to the rest of your projects and keep a close look to all logs and metrics New Relic gives you.

We compared the consolidation feature and we obtained exactly the same amount of servers in stand-by. The main difference was that Eco4Cloud turned off the unneeded hosts in 2 days while VMTurbo Operations Manager required one day per host. This behavior is caused by the different algorithms implemented by these two products. Compared to Eco4Cloud, VMware DRS/DPM was very aggressive (we tried it in vSphere 5.0). We haven't tested it with vSphere 6 yet.

Data Dog has solutions that look more attractive, but not at their price point. We have also tried to build a solution straight from the Cloud, where our business is built, but some things are too hard to replicate. This shows that New Relic is useful and helps our efficiency.

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Agent deployment is easily integrated into our workflow. Adding the agent to new servers is quick and painless

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• Eco4Cloud causes a reduction in power consumption both on old VMware clusters and especially on new ones.
• It also causes a delay in CapEx investments because you buy more hosts only when really needed.

• We were able to quickly identify our most time consuming APIs. In some cases we were able to bring down times for some apis from 4s to 200ms.
• We were able to identify our slowest database queries and optimize them for quicker response times.

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