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We’ve conservatively saved 80-90% of our observability costs and engineering time spent compared to our previous observability solution.


Kloudfuse unified observability datalake solved our ever growing problem of logs volume, metrics cardinality and large volume of data for APM at a cost which is significantly lesser.




Kloudfuse's observability suite was used to successfully migrate over data from dashboards and alerts to open standards (promQL, Grafana) for Workday, minimizing the time required for this large migration without losing any functionality
Kloudfuse's observability suite was used to successfully migrate over data from dashboards and alerts to open standards (promQL, Grafana) for Workday, minimizing the time required for this large migration without losing any functionality
Kloudfuse’s observability suite not only consolidated observability data, but also applied advanced functions to analyze the data to reduce the toil involved in troubleshooting.


Kloudfuse unified observability datalake was deployed with GEHC VPC so that all MELT data was completely secure, compliant and significantly reduced the cost of the overall solution for increased volume of data.
Kloudfuse unified observability datalake was deployed with GEHC VPC so that all MELT data was completely secure, compliant and significantly reduced the cost of the overall solution for increased volume of data.






Kloudfuse unified observability datalake consolidated all our internal solutions which were different open source offerings and for each stream of observability and significantly increased the productivity of our engineers.
Kloudfuse unified observability datalake consolidated all our internal solutions which were different open source offerings and for each stream of observability and significantly increased the productivity of our engineers.






Kloudfuse unified observability datalake unified all the data from various sources and significantly reduced the cost of observability for our increased cardinality of our MELT data when we moved to kubernetes deployments.
Kloudfuse unified observability datalake unified all the data from various sources and significantly reduced the cost of observability for our increased cardinality of our MELT data when we moved to kubernetes deployments.






We’ve conservatively saved 80-90% of our observability costs and engineering time spent compared to our previous observability solution.
We’ve conservatively saved 80-90% of our observability costs and engineering time spent compared to our previous observability solution.






We’ve conservatively saved 80-90% of our observability costs and engineering time spent compared to our previous observability solution.
We’ve conservatively saved 80-90% of our observability costs and engineering time spent compared to our previous observability solution.
Kloudfuse unified observability datalake solved our ever growing problem of logs volume, metrics cardinality and large volume of data for APM at a cost which is significantly lesser.





Observe. Analyze. Automate
Unlimit your Observability, Limit your Cost.


Observe. Analyze. Automate
Unlimit your Observability, Limit your Cost.


Observe. Analyze. Automate
Unlimit your Observability, Limit your Cost.