Foglight vs. Google Kubernetes Engine

Strengths [Foglight]

• Monitoring, Alerting and Management of on-prem virtualization and physical servers
• Historical trending and baselining are excellent and being able to compare a problem period against the same sets of data for a period when there was no issue is especially helpful as part of troubleshooting.
• Ease of use for end users is appreciated

Weaknesses [of Foglight]

• Creation and management of custom monitors is a developer level activity requiring Groovy skillset
• Less useful for management of an environment where there is a large amount of custom implementations
• Commitment to longevity of cartridges/packs for specific subsystems
• Ability to create custom schedules/alerts/escalations is only available via a 3rd party product (from a former Quest developer) and is not particularly easy to manage/manipulate
• Lack of API accessibility for external integrations to other analytics (splunk, etc.)

Incentivized

If your application is complex, if it's planet-scale, or if you need autoscaling, then Kubernetes is best suited. If your application is straightforward, you can opt for App Engine or Cloud Run. In many cases, you can prefer to run the cloud on GKE. But once you deploy on Kubernetes, you get the flexibility to try different things. But if you don't seek flexibility, it's not an option for you.

Incentivized

• Database monitoring
• Database management suite
• Customization (both monitors and dashboards)

Incentivized

• Engine upgrade rollout strategy - well documented and configurable
• Integration with other Google Cloud services like the Compute Engine, SaaS databases, and some cloud networking like Cloud Armor
• Graphical interface for a lot of operations - either for a quick peek/overview or actual work done by administrators and/or developers (via the Google Cloud Console, for example)

Incentivized

• There are not many problems with this product
• Limited ability to use Foglight itself to solve problems it identifies

Incentivized

• Support of IPv6.
• Better GitOps.
• A "serverless" Kubernetes so we can install Google config connector will be really awesome.
• Container-native load balancers do not support internal TCP/UDP load balancers or network load balancers.

Incentivized

• Google Kubernetes Engine has a good UI and documentation that facilitates setup and helps get projects moving along quickly
• Its built-in logging integrations with StackDriver make it easier to monitor the application and log issues quickly
• Automated orchestration, deployment, and scaling of nodes and networking are all easily configurable with yaml files

Incentivized

Very good Kubernetes distribution with a reasonable total price. Integration with storage and load balancer for ingress and services speed up every process deployment.

Incentivized

Incentivized

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.

Incentivized

• When issues came up, we reached out to some folks at GCP and they seemed to be very prompt and attentive to our needs. They were always willing to help and provide additional details or recommendations or links to resources. This kind of support is very helpful as it allows us to navigate GKE with more confidence.

Incentivized

• Foglight has a positive impact on my company by being a complete monitoring platform that specializes in risk assessment, user diagnosis and management, and server monitoring ensuring a secure business infrastructure through predictive analytics, query analysis, anomaly detection, behavior tracking, troubleshooting, automated discovery, and more.

Incentivized

• Reduced cloud computing costs.
• Easier management of applications.
• Extra time investment to learn how to setup applications in Google versus Amazon.

Incentivized