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.
N/A
Kubernetes
Score 9.1 out of 10
N/A
Kubernetes is an open-source container cluster manager.
Kubernetes is really great and their community is growing really fast (Google influence). We evaluated it in the beginning and it would fit for our web applications workload. We decided to proceed with Mesos because it has more potential. You may use a different framework for …
Kubernetes is by far the best choice. More reliable and better developer experience. Mesos is prone to sporadic failures and not really designed to handle CI/CD-based deployments. Docker Cloud once shut down our entire cluster for "upgrades" without giving us any warning.
Kubernetes is a great alternative to cloud hosted expensive solutions. It is extremely well documented and maintained. It is probably the best home-grown solution available for container infrastructure management.
There's really no reason to ever use Mesos. We switched over to Kubernetes and it's been a breath of fresh air - better CD support, easy CLI for browsing logs, no mysterious dangling redeploys. If you're looking for a tool to manage a fleet of Docker containers on VMs, Kubernetes beats Mesos by a wide margin.
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.)
K8s should be avoided - If your application works well without being converted into microservices-based architecture & fits correctly in a VM, needs less scaling, have a fixed traffic pattern then it is better to keep away from Kubernetes. Otherwise, the operational challenges & technical expertise will add a lot to the OPEX. Also, if you're the one who thinks that containers consume fewer resources as compared to VMs then this is not true. As soon as you convert your application to a microservice-based architecture, a lot of components will add up, shooting your resource consumption even higher than VMs so, please beware. Kubernetes is a good choice - When the application needs quick scaling, is already in microservice-based architecture, has no fixed traffic pattern, most of the employees already have desired skills.
Mesos may have many frameworks. If you have Mesos installed on your servers, you may use it for many kinds of tasks. Today we're running only web applications but the idea is to install a different framework for big data soon.
Unreliable deployments that would fail for no good reason. Sometimes our Docker container would be "restarting" forever because Mesos thought it didn't have enough resources to start the container.
Impossibly slow UI. Built in React under the hood with a lot of bloatware backed in, so loading the Mesos UI on a slow internet connection was painful.
No real logging solution - it would stream "console.log()" output to the UI, but searching for logs wasn't really possible without downloading a huge file.
No built-in support for redeploying containers from a CI. We had to create a service whose whole job was to expose an HTTP endpoint that restarted a container, and then made Circle CI ping the endpoint whenever we wanted to redeploy.
Local development, Kubernetes does tend to be a bit complicated and unnecessary in environments where all development is done locally.
The need for add-ons, Helm is almost required when running Kubernetes. This brings a whole new tool to manage and learn before a developer can really start to use Kubernetes effectively.
Finicy configmap schemes. Kubernetes configmaps often have environment breaking hangups. The fail safes surrounding configmaps are sadly lacking.
The Kubernetes is going to be highly likely renewed as the technologies that will be placed on top of it are long term as of planning. There shouldn't be any last minute changes in the adoption and I do not anticipate sudden change of the core underlying technology. It is just that the slow process of technology adoption that makes it hard to switch to something else.
It is an eminently usable platform. However, its popularity is overshadowed by its complexity. To properly leverage the capabilities and possibilities of Kubernetes as a platform, you need to have excellent understanding of your use case, even better understanding of whether you even need Kubernetes, and if yes - be ready to invest in good engineering support for the platform itself
Kubernetes is really great and their community is growing really fast (Google influence). We evaluated it in the beginning and it would fit for our web applications workload. We decided to proceed with Mesos because it has more potential. You may use a different framework for different kinds of tasks on Mesos. There is a Kubernetes framework for Mesos, by the way.
Most of the required features for any orchestration tool or framework, which is provided by Kubernetes. After understanding all modules and features of the K8S, it is the best fit for us as compared with others out there.
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.
