Meet Malt
The workplace is changing fast, and it's not just about remote working. The pandemic has accelerated the shift to freelancing, with the number of freelancers in the French digital sector growing by 92% in the past decade. Digital marketplace Malt helps connect 300,000 freelancers with 40,000 businesses, using AI to analyze business requirements and recommend the best freelance candidates for roles.
The Challenge
Malt needed to scale its AI-powered search and recommendation engine infrastructure to support ambitious growth plans. After migrating to Google Cloud and containerizing applications with Google Kubernetes Engine, the company required cost optimization and technical expertise to efficiently manage their expanding infrastructure across multiple countries.
The Solution
DoiT provided immediate cost savings through optimized billing and commitment plans for Google Cloud services. The partnership included access to granular cost management technology for department-level spending analysis and dedicated technical support for infrastructure automation best practices, including guidance on Preemptible VM instances and autoscaling.
Results
- Achieved immediate 6% reduction in Google Cloud costs through optimized billing
- Gained granular cost visibility with department-level spending breakdowns
- Received expert technical support for Google Kubernetes Engine optimization
- Freed up budget to reinvest in development teams and growth initiatives
We worked together with DoiT to transition smoothly and immediately benefited from a 6% reduction in our costs.
Hugo Lassiège, Co-fondateur, CTO
Technical Support and Expertise
DoiT's expertise in Google Cloud supported Malt's expansion by providing insights into infrastructure automation best practices. The dedicated support services enabled quick responses to Google Cloud infrastructure questions, including advice on using Preemptible VM instances as Nodes in Google Kubernetes Engine and troubleshooting autoscaling queries.
Results and Investment
Optimizing costs through DoiT freed money for Malt to invest in development teams. For a rapidly growing business, investment goes principally into people, and the infrastructure cost savings are being reinvested into teams. The partnership provides confidence in scaling capabilities for future expansion beyond Europe.
What's Next
Malt plans to maximize DoiT's optimization tools while improving CI infrastructure by migrating from hosted Bamboo to GitLab CI on Google Kubernetes Engine and migrating to Looker. The key goal is moving quickly and simplifying operations, with cloud work supported by DoiT enabling this strategic approach to growth and expansion.
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What they say
What I really like about DoiT's approach is that you're very hands-on and proactive. Satyam would ping me a few times a sprint, letting me know about the most current features, checking in on how things are going. When we are going through a peak time, that proactiveness makes a real difference. Satyam always comes through whenever we need support and helps us leverage the right experts to get us where we need to be.
Chiamaka Ibeme, Engineering Manager, Platform
SELECT has made important cost data readily accessible. I will often pull it up during engineering design reviews so we can quickly evaluate cost impact and projections and factor that into our design decisions.
Douglas Zickuhr, Senior Data Platform Engineer at Personio
I love clicking through SELECT to understand how our environment and workloads are evolving. I probably check it every day. It's coffee and SELECT for me every morning.
Ian Fahey, Senior Analytics Engineer at Loop
You guys have the best UI experience that I've had of any software. It's like you just read my mind where, like, oh, I wish I could click there. Oh, I can
Diana Koshy, Sr. Director of Data Engineering at Kargo
SELECT feels like exactly what Paul and I would have built if we had locked ourselves in a room for 18 months to create our ideal monitoring solution.
Devin McGee, Data Engineering Lead at Home Chef
SELECT dramatically lowers the cognitive load to understanding Snowflake costs. I'm able to sit there and easily understand what's driving the cost. Not to blow smoke up your ass, but it's just so easy to do in your platform
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