Foglight is a database performance management suite from Quest, with modules to perform cloud analytics, network performance monitoring and virtualization management, scaling to a broad, cloud / virtualization focused IT infrastructure monitoring solution.
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Google Kubernetes Engine
Score 8.1 out of 10
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Google Kubernetes Engine supplies containerized application management powered by Kubernetes which includes Google Cloud services including load balancing, automatic scaling and upgrade, and other Google Cloud services.
Foglight is a tool that allows productivity to advance quickly and safely, offering data monitoring and optimization, guaranteeing the success of our business. It is a solution that provides relevant data for strategy and data analysis without losing sight of the final …
Foglight was chosen years ago as a replacement for Groundwork. After 2.5 years of implementing Groundwork things were still not complete and the decision to go with a more formalized solution was made. Foglight installed easily and quickly nearly across the board and the full …
We selected Foglight almost 6 years ago for its advancements in the APM space, moving toward a single pane of glass and their SaaS development. They have since abandoned the APM and SaaS offerings to focus solely on Database and Compute monitoring. This is why we are migrating …
We were previously using Oracle to monitor resources across servers and networks. In general, that product was alright but the Foglight alerts are far superior to Oracle. The business goal of using Foglight is really to minimize business interruption costs so the faster and …
We have a CICD pipeline, which we wrote using the Gitlab CI file. This is connected directly to our GKE cluster. So, any change in our code will directly start the CICD pipeline. The pipeline first tests the deployment on testing environments. We are also using Helm charts to …
We had to move several products to Google Cloud, and the Google Kubernetes Engine was the option recommended to us, so we investigated it and ran with it. Back then (2019), we were not aware of Cloud Run-provisioned K8s clusters, so our other option was a completely …
GKE spins up new nodes a LOT faster than AKS. GKE's auto scaler runs a lot smoother than AKS. GKE has a lot more Kubernetes features baked in natively.
In comparison to functionality with EKS and AKS, it has a better upgrade path and the price is lower. Not sure why flannel is the primary overlay network provider but network policies are supported as well.
Google Kubernetes Engine has better upgrades and auto-scale management. Google Kubernetes Engine is also the cheapest option for managed Kubernetes, and Google is the principal contributor to the Kubernetes project.
Our organization went with Google's Kubernetes Engine because we are already significantly invested in the Google Cloud Platform. In our evaluation of Amazon's Elastic Kubernetes Service we were turned off by recent concerns about Amazon becoming overly dominant in the cloud …
It really depends on why my colleague is evaluating Foglight. If it is for Database monitoring and management, I highly recommend it. If it is for anything else, I would encourage them to look at others in this space.
Google Kubernetes Engine is well suited for dynamic and large workloads since it can scale up with usage. It is easily configurable, which allows for flexibility. User interface is simple to navigate, which reduces roadblocks for a team with people unfamiliar with Kubernetes. Great if you are already using other GCP services as it integrates well with that.
Foglight allows detecting and diagnosing performance problems simplifying hybrid environments, it is a solution that has perfect features which work in a flexible and intuitive way, it allows database performance in a safe and fast way. It works perfectly with nothing else to add.
It's a great product if you learn it. It has flexibility and is very strong. Autoscaling and Resource management make running huge applications a breeze. Using Helm with Kubernetes and Terraform for infrastructure creation can totally automate your CICD pipeline. You also get easy access to CUDA cores for machine learning.
Foglight was chosen years ago as a replacement for Groundwork. After 2.5 years of implementing Groundwork things were still not complete and the decision to go with a more formalized solution was made. Foglight installed easily and quickly nearly across the board and the full implementation for complex infrastructure was completed (with no Professional Services) by us in under 4 months. Nagios is a wonderful toolkit but you have to be ready to build what you need. It's flexibility and breadth are excellent features but with that comes the need to define things very tightly lest you embark on the project that never ends (see above about Groundwork). Dynatrace is an excellent APM tool and has advanced analytics but as a general infrastructure monitoring tool it is actually very expensive and to be honest does not have the same focus and full feature set that it does on it's APM (which to be fair is it's wheelhouse). vROPs (we also have) is a wonderful tool but focused (and rightly so) on satisfying the VMware engineers in the crowd and doesn't put itself out there too far to make things palatable for the non-engineering crowd.
We had to move several products to Google Cloud, and the Google Kubernetes Engine was the option recommended to us, so we investigated it and ran with it. Back then (2019), we were not aware of Cloud Run-provisioned K8s clusters, so our other option was a completely self-managed K8s cluster on Compute Engine VMs, which we did not have the knowledge of and capacity to handle.