Foglight vs. Google Cloud Run

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

Microservices and RestFul API application as it is fast and reliant. Seamless integration with event triggers such as pubsub or event arc, so you can easily integrate that with usecases with file uploads, database changes, etc. Basically great with short-lived tasks, if however, you have long-running processses, Cloud Run might not be idle for this. For example if you have a long running data processing task, other solutions such as kubeflow pipelines or dataflow are more suited for this kind of tasks. Cloud Run is also stateless, so if you need memory, you will have to connect an external database.

Incentivized

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

Incentivized

• Auto scaling is the best one
• provide direct VPC connectivity and rigid network
• Cloud SQL and Pub/Sub services
• Handling latency issues

Incentivized

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

Incentivized

• The UI can be made simpler. Currently the UI is bloated and it takes time to find out what you want
• More integrations with container registry providers (ECR, dockerhub)
• Better permissions UX. Currently GCP requires service accounts to be used with cloud products, the experience adding/removing permissions is difficult to navigate

Incentivized

We definitely need to renew it because we dont own our own infrastructure and storage and we are happy with Cloud Run features

Incentivized

The UI/console is great... the documentation is top-notch for developers, but the CLI itself when you have to script around it is very complex and easy to forget some options... the downside of a generic command line client.

Incentivized

Not seen any major issues when we run applications its good

Incentivized

Initially we felt slow but slowly it picked up and easy to manage

Incentivized

I was involved in the initial implementation setup, Its easy with the given documentaiton we can do ourself. Not that critical

Incentivized

Incentivized

AWS Lambda supports code zip package, enabling lower cold start time. Also, AWS Lambda pricing is much simpler, easier to understand.

Other than that, the 2 products are very similar, including the Docker image support: the image must be built based on proprietary base image.

Obviously, if your other services are running in GCP, then Google Cloud Run is your only choice for tight integration, & private networking.

Incentivized

Not part of purchase.

Incentivized

It has good auto scale feature and reliable also

Incentivized

We have very good support when needed

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

• Built in support for auto scaling helps reduce operational overhead
• Any application performance issues can be addressed quickly by allocating more resources while a proper fix can be planned and rolled out later
• Using Google Cloud Run enables development of microservices which provides granular control for scaling critical services in the platform

Incentivized