Due to data privacy regulations, every customer on-boarding the platform receives an isolated OD (On-Demand) EC2 environment, which resulted in ever-growing compute costs.
Liran Ben Abu
Head of DevOps
Due to data privacy regulations, every customer on-boarding the platform receives an isolated OD (On-Demand) EC2 environment, which resulted in ever-growing compute costs.
Liran Ben Abu
Head of DevOps
Due to data privacy regulations, every customer on-boarding the platform receives an isolated OD (On-Demand) EC2 environment, which resulted in ever-growing compute costs.
Liran Ben Abu
Head of DevOps
Due to data privacy regulations, every customer on-boarding the platform receives an isolated OD (On-Demand) EC2 environment, which resulted in ever-growing compute costs.
Liran Ben Abu
Head of DevOps
Due to data privacy regulations, every customer on-boarding the platform receives an isolated OD (On-Demand) EC2 environment, which resulted in ever-growing compute costs.
Liran Ben Abu
Head of DevOps
Customer
Brief
Voyager Labs is a world leader in AI-driven advanced technologies for human behavior analysis. The company has developed a proprietary AI-based technology that harnesses billions of data points from unstructured data to reveal deep actionable insights.
Their unique technology searches, aggregates and fuses data points and human behavior indicators from multiple data sources, intelligently processing, and analyzing them to provide a holistic view of reality from insights that were previously unattainable.
Their offices are located in Washington DC, New York City, Singapore, Mexico, Spain, India, and Israel.
Key
Challenges
Due to the complexity of forecasting based on the various RI characteristics (Standard\Convertible, Cross AZ, Tenancy, Upfront), engineers spent a significant time designing, planning, and purchasing commitment plans.
Key
Challenges
Since implementing Zesty, around 1 year ago, Voyager Labs slashed their EC2 costs by over 35%.
In addition, their engineering team no longer had to manually forecast, plan, and mitigate to capacity changes
The Challenge:
Ever since Voyager Labs began its journey with AWS, its cutting edge AI technology progressed, its product portfolio expanded, and they grew tremendously. Nowadays, hundreds of customers leverage Voyager Labs’ advanced analytics capabilities. But with high growth comes more complexity in cloud infrastructure.
In order to manage their large-scale cloud infrastructure, Voyager Labs’ engineers use a cloud management solution that allows them to map their resources, receive right-sizing recommendations, and identify idle and unused resources.
Still, up until the latest version of their product, Voyager Labs’ cloud environments were comprised of thousands of On-Demand EC2 instances, which skyrocketed their AWS bill.
After redesigning their cloud infrastructure, their engineering teams began forecasting compute usage in order to purchase RIs (Reserved Instances) to significantly reduce their EC2 costs.
They came across several challenges when manually purchasing commitments:
- The complexity of forecasting based on RI characteristics like Standard\Convertible, Cross AZ, Tenancy, and Upfront resulted in engineers spending far too much time designing, planning, and purchasing commitment plans.
- Purchasing RIs was useful for the baseline of Voyager Labs’ cloud architecture, but once there were compute usage peaks, they were forced to launch new instances to facilitate the demand which were not covered by savings.
Zesty’s Solution:
Unlike other cloud management solutions that are dependent on CUR data (which has a 2-3 day data delay), Zesty’s unique technology enabled Voyager Labs to get a real-time overview of their AWS infrastructure in terms of cost and resource allocation.
The Zesty platform enabled the engineering team to maximize its potential savings by constantly purchasing and selling commitment plans. It also eliminated the risk of over-provisioning by guaranteeing a buy-back of any
over-provisioned servers, which was a win-win for the Voyager Labs team.
The Result:
Significant Cost Reduction
After implementing Zesty about one year ago, Voyager Labs was able to slash their EC2 costs by more than 35%.
Besides significantly reducing the costs of their EC2 fleet, Zesty relieved engineering teams from forecasting, planning, and mitigating capacity changes, thanks to its real-time AI engine.
Customer
Brief
Voyager Labs is a world leader in AI-driven advanced technologies for human behavior analysis. The company has developed a proprietary AI-based technology that harnesses billions of data points from unstructured data to reveal deep actionable insights.
Their unique technology searches, aggregates and fuses data points and human behavior indicators from multiple data sources, intelligently processing, and analyzing them to provide a holistic view of reality from insights that were previously unattainable.
Their offices are located in Washington DC, New York City, Singapore, Mexico, Spain, India, and Israel.
Key
Challenges
Due to the complexity of forecasting based on the various RI characteristics (Standard\Convertible, Cross AZ, Tenancy, Upfront), engineers spent a significant time designing, planning, and purchasing commitment plans.
Key
Challenges
Since implementing Zesty, around 1 year ago, Voyager Labs slashed their EC2 costs by over 35%.
In addition, their engineering team no longer had to manually forecast, plan, and mitigate to capacity changes
Due to data privacy regulations, every customer on-boarding the platform receives an isolated OD (On-Demand) EC2 environment, which resulted in ever-growing compute costs.
Liran Ben Abu
Head of DevOps
Ever since Voyager Labs began its journey with AWS, its cutting edge AI technology progressed, its product portfolio expanded, and they grew tremendously. Nowadays, hundreds of customers leverage Voyager Labs’ advanced analytics capabilities. But with high growth comes more complexity in cloud infrastructure.
In order to manage their large-scale cloud infrastructure, Voyager Labs’ engineers use a cloud management solution that allows them to map their resources, receive right-sizing recommendations, and identify idle and unused resources.
Still, up until the latest version of their product, Voyager Labs’ cloud environments were comprised of thousands of On-Demand EC2 instances, which skyrocketed their AWS bill.
After redesigning their cloud infrastructure, their engineering teams began forecasting compute usage in order to purchase RIs (Reserved Instances) to significantly reduce their EC2 costs.
They came across several challenges when manually purchasing commitments:
- The complexity of forecasting based on RI characteristics like Standard\Convertible, Cross AZ, Tenancy, and Upfront resulted in engineers spending far too much time designing, planning, and purchasing commitment plans.
- Purchasing RIs was useful for the baseline of Voyager Labs’ cloud architecture, but once there were compute usage peaks, they were forced to launch new instances to facilitate the demand which were not covered by savings.
Due to data privacy regulations, every customer on-boarding the platform receives an isolated OD (On-Demand) EC2 environment, which resulted in ever-growing compute costs.
Liran Ben Abu
Head of DevOps
The Result:
Unlike other cloud management solutions that are dependent on CUR data (which has a 2-3 day data delay), Zesty’s unique technology enabled Voyager Labs to get a real-time overview of their AWS infrastructure in terms of cost and resource allocation.
The Zesty platform enabled the engineering team to maximize its potential savings by constantly purchasing and selling commitment plans. It also eliminated the risk of over-provisioning by guaranteeing a buy-back of any
over-provisioned servers, which was a win-win for the Voyager Labs team.
Zesty’s Solution:
Significant Cost Reduction
After implementing Zesty about one year ago, Voyager Labs was able to slash their EC2 costs by more than 35%.
Besides significantly reducing the costs of their EC2 fleet, Zesty relieved engineering teams from forecasting, planning, and mitigating capacity changes, thanks to its real-time AI engine.
Due to data privacy regulations, every customer on-boarding the platform receives an isolated OD (On-Demand) EC2 environment, which resulted in ever-growing compute costs.
Liran Ben Abu
Head of DevOps
